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Jing Li

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cond-mat.mtrl-sci Computer Vision math.AP astro-ph.GA astro-ph.EP math.NA cond-mat.mes-hall Information Theory math.IT Computation and Language astro-ph.SR Artificial Intelligence Machine Learning quant-ph math-ph math.MP Numerical Analysis physics.optics astro-ph.HE cond-mat.other cond-mat.soft Cryptography and Security physics.flu-dyn astro-ph.IM cond-mat.quant-gas cond-mat.str-el Distributed, Parallel, and Cluster Computing hep-ph nlin.CD physics.chem-ph astro-ph eess.SP Information Retrieval math.CO math.OC math.PR math.RA Multimedia Networking and Internet Architecture nlin.PS nucl-th physics.comp-ph physics.ed-ph Robotics Social and Information Networks astro-ph.CO Biomolecules cond-mat.supr-con cs.CY Data Structures and Algorithms Databases gr-qc hep-ex Human-Computer Interaction math.DS math.GT Multiagent Systems physics.ao-ph physics.class-ph physics.med-ph physics.plasm-ph q-fin.PM q-fin.RM q-fin.ST Systems and Control

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preprint2026arXiv

Personalizing LLMs with Binary Feedback: A Preference-Corrected Optimization Framework

Large Language Model (LLM) personalization aims to align model behaviors with individual user preferences. Existing methods often focus on isolated user histories, neglecting the essential role of inter-user differences. We propose C-BPO, a framework that personalizes LLMs via preference-calibrated binary signals. By treating target user data as positive feedback and other users' data as an auxiliary set of implicit negative signals, C-BPO captures distinct inter-user differences. To mitigate the preference overlap issue, where shared task knowledge is erroneously penalized, we derive an objective grounded in Positive-Unlabeled (PU) learning theory. This approach purifies negative signals by subtracting ``positive bias'', ensuring alignment with unique idiosyncrasies without compromising general helpfulness. Empirical experiments across various personalization tasks and backbone LLMs show C-BPO consistently outperforms baselines, demonstrating the efficacy of preference-calibrated binary signals in modeling inter-user differences.

preprint2026arXiv

PPU-Bench:Real World Benchmark for Personalized Partial Unlearning in Vision Language Models

Multimodal Large Language Models (MLLMs) may memorize sensitive cross-modal information during pretraining. However, existing MLLM unlearning benchmarks rely on synthetic knowledge injection or complete subject-level deletion, which fail to capture realistic, personalized deletion requests that require fine-grained factual control. In this paper, we introduce PPU-Bench, a real-world and fine-tuning-free benchmark for personalized partial unlearning in MLLMs. PPU-Bench contains 24K multimodal and unimodal samples derived from pre-existing knowledge of 500 public figures under three progressively challenging settings: Complete, Selective, and Personalized unlearning. The benchmark evaluates whether methods can remove target knowledge while preserving non-target facts, model utility, and cross-modal consistency. Extensive experiments show that Complete Unlearning often suppresses visual identity rather than factual knowledge, while Selective and Personalized Unlearning expose significant forget--retain trade-offs and challenges in intra-subject factual boundaries. Robustness analysis under cross-image and prompt-based attacks reveals distinct vulnerabilities across different unlearning settings. Motivated by these findings, we propose Boundary-Aware Optimization (BAO), which explicitly models intra-subject forget-retain boundaries. Experimental results on two representative methods demonstrate that BAO can effectively enforce intra-subject factual boundaries.

preprint2026arXiv

Team-Based Self-Play With Dual Adaptive Weighting for Fine-Tuning LLMs

While recent self-training approaches have reduced reliance on human-labeled data for aligning LLMs, they still face critical limitations: (i) sensitivity to synthetic data quality, leading to instability and bias amplification in iterative training; (ii) ineffective optimization due to a diminishing gap between positive and negative responses over successive training iterations. In this paper, we propose Team-based self-Play with dual Adaptive Weighting (TPAW), a novel self-play algorithm designed to improve alignment in a fully self-supervised setting. TPAW adopts a team-based framework in which the current policy model both collaborates with and competes against historical checkpoints, promoting more stable and efficient optimization. To further enhance learning, we design two adaptive weighting mechanisms: (i) a response reweighting scheme that adjusts the importance of target responses, and (ii) a player weighting strategy that dynamically modulates each team member's contribution during training. Initialized from a SFT model, TPAW iteratively refines alignment without requiring additional human supervision. Experimental results demonstrate that TPAW consistently outperforms existing baselines across various base models and LLM benchmarks. Our code is publicly available at https://github.com/lab-klc/TPAW.

preprint2025arXiv

Physical properties and first-principles calculations of an altermagnet candidate Cs$_{1-δ}$V$_2$Te$_2$O

We report the crystal growth, structure, physical properties, and first-principles calculations of a vanadium-based oxytelluride Cs$_{1-δ}$V$_2$Te$_2$O. The material possesses two-dimensional V$_2$O square nets sandwiched by tellurium layers, with local crystallographic symmetry satisfying the spin symmetry for a $d$-wave altermagnet. An antiferromagnetic transition at 293 K is unambiguously evidenced from the measurements of magnetic susceptibility and specific heat. In addition, a secondary transition at $\sim$70 K is also observed, possibly associated with a Lifshitz transition. The first-principles calculations indicate robust Néel-type collinear antiferromagnetism in the V$_2$O plane. Consequently, spin splittings show up in momentum space, in relation with the real-space mirror/rotation symmetry. Interestingly, the V-$d_{yz}/d_{xz}$ electrons, which primarily contribute the quasi-one-dimensional Fermi surface, turns out to be fully orbital- and spin-polarized, akin to the case of a half metal. Our work lays a solid foundation on the potential applications utilizing altermagnetic properties in vanadium-based oxychalcogenides.

preprint2024arXiv

Distinguishing the Topological Charge of Vortex Beam via Fourier Back Plane Imaging with Chiral Gammadion Structure

In recent years, research on the interaction between Orbital Angular Momentum (OAM) and matter has seen a continuous influx of investigations. OAM possesses distinct properties, such as additional degrees of freedom, vortex characteristics, and topological properties, which expand its applications in optical communication, optical sensing, and optical force. Through experiments involving the interaction of a chiral metal swastika structure with a SAM-OAM beam generated by a q-plate, we have observed a phenomenon does not present in pure SAM beams. Fourier back focal plane (FBP) imaging under SAM beam excitation easily identifies the chirality and geometric properties of the structure. When the SAM-OAM beam excites the structure, FBP not only identifies its chirality and geometric properties but also distinguishes different OAM topological charges and signs, as well as the degree of elliptic polarization. The stokes parametric FBP imaging reveals asymmetric polarization distribution resulting from the interaction between a vortex beam and the chiral structure. Moreover, it clearly reflects the conversion process of SAM to OAM. The experimental results align well with simulation results. These findings hold valuable insights for the advancement of optical information storage and communication using OAM, opening up new possibilities for further exploration in this field.

preprint2023arXiv

Audio2Gestures: Generating Diverse Gestures from Audio

People may perform diverse gestures affected by various mental and physical factors when speaking the same sentences. This inherent one-to-many relationship makes co-speech gesture generation from audio particularly challenging. Conventional CNNs/RNNs assume one-to-one mapping, and thus tend to predict the average of all possible target motions, easily resulting in plain/boring motions during inference. So we propose to explicitly model the one-to-many audio-to-motion mapping by splitting the cross-modal latent code into shared code and motion-specific code. The shared code is expected to be responsible for the motion component that is more correlated to the audio while the motion-specific code is expected to capture diverse motion information that is more independent of the audio. However, splitting the latent code into two parts poses extra training difficulties. Several crucial training losses/strategies, including relaxed motion loss, bicycle constraint, and diversity loss, are designed to better train the VAE. Experiments on both 3D and 2D motion datasets verify that our method generates more realistic and diverse motions than previous state-of-the-art methods, quantitatively and qualitatively. Besides, our formulation is compatible with discrete cosine transformation (DCT) modeling and other popular backbones (\textit{i.e.} RNN, Transformer). As for motion losses and quantitative motion evaluation, we find structured losses/metrics (\textit{e.g.} STFT) that consider temporal and/or spatial context complement the most commonly used point-wise losses (\textit{e.g.} PCK), resulting in better motion dynamics and more nuanced motion details. Finally, we demonstrate that our method can be readily used to generate motion sequences with user-specified motion clips on the timeline.

preprint2023arXiv

Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm

Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learning (ML) models to quantify intra-tumoral genetic heterogeneity for each patient. This capability holds great promise for enabling better therapeutic selection to improve patient outcomes. We proposed a novel Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) to predict regional genetic alteration status within each GBM tumor using MRI. WSO-SVM was applied to a unique dataset of 318 image-localized biopsies with spatially matched multiparametric MRI from 74 GBM patients. The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA, and PTEN) based on features extracted from the corresponding region of five MRI contrast images. For comparison, a variety of existing ML algorithms were also applied. The classification accuracy of each gene was compared between the different algorithms. The SHapley Additive exPlanations (SHAP) method was further applied to compute contribution scores of different contrast images. Finally, the trained WSO-SVM was used to generate prediction maps within the tumoral area of each patient to help visualize the intra-tumoral genetic heterogeneity. This study demonstrated the feasibility of using MRI and WSO-SVM to enable non-invasive prediction of intra-tumoral regional genetic alteration for each GBM patient, which can inform future adaptive therapies for individualized oncology.

preprint2022arXiv

A Blind All-sky Search for Star Clusters in Gaia EDR3: 886 Clusters within 1.2 kpc of the Sun

Although previous searches for star clusters have been very successful, many clusters are likely still omitted, especially at high Galactic latitude regions. In this work, based on the astrometry of Gaia EDR3, we searched nearby (parallax > 0.8 mas) all-sky regions, obtaining 886 star clusters, of which 270 candidates have not been cataloged before. At the same time, we have presented the physical parameters of the clusters by fitting theoretical isochrones to their optical magnitudes. More halo members and expanding structures in many star clusters were also found. Most of the new objects are young clusters that are less than 100 million years old. Our work greatly increased the sample size and physical parameters of star clusters in the solar neighborhood, in particular, 46 clusters are newly found with |b| > 20 deg, which represents an increase of nearly three fold of cluster numbers at high Galactic latitude regions. The cluster parameters and member stars are available at CDS via https://cdsarc.u-strasbg.fr/ftp/vizier.submit//hezh22b/, and the cluster figure sets are available via https://doi.org/10.12149/101133.

preprint2022arXiv

A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict

Sarcasm employs ambivalence, where one says something positive but actually means negative, and vice versa. The essence of sarcasm, which is also a sufficient and necessary condition, is the conflict between literal and implied sentiments expressed in one sentence. However, it is difficult to recognize such sentiment conflict because the sentiments are mixed or even implicit. As a result, the recognition of sophisticated and obscure sentiment brings in a great challenge to sarcasm detection. In this paper, we propose a Dual-Channel Framework by modeling both literal and implied sentiments separately. Based on this dual-channel framework, we design the Dual-Channel Network~(DC-Net) to recognize sentiment conflict. Experiments on political debates (i.e. IAC-V1 and IAC-V2) and Twitter datasets show that our proposed DC-Net achieves state-of-the-art performance on sarcasm recognition. Our code is released to support research.

preprint2022arXiv

A Knowledge Distillation-Based Backdoor Attack in Federated Learning

Federated Learning (FL) is a novel framework of decentralized machine learning. Due to the decentralized feature of FL, it is vulnerable to adversarial attacks in the training procedure, e.g. , backdoor attacks. A backdoor attack aims to inject a backdoor into the machine learning model such that the model will make arbitrarily incorrect behavior on the test sample with some specific backdoor trigger. Even though a range of backdoor attack methods of FL has been introduced, there are also methods defending against them. Many of the defending methods utilize the abnormal characteristics of the models with backdoor or the difference between the models with backdoor and the regular models. To bypass these defenses, we need to reduce the difference and the abnormal characteristics. We find a source of such abnormality is that backdoor attack would directly flip the label of data when poisoning the data. However, current studies of the backdoor attack in FL are not mainly focus on reducing the difference between the models with backdoor and the regular models. In this paper, we propose Adversarial Knowledge Distillation(ADVKD), a method combine knowledge distillation with backdoor attack in FL. With knowledge distillation, we can reduce the abnormal characteristics in model result from the label flipping, thus the model can bypass the defenses. Compared to current methods, we show that ADVKD can not only reach a higher attack success rate, but also successfully bypass the defenses when other methods fails. To further explore the performance of ADVKD, we test how the parameters affect the performance of ADVKD under different scenarios. According to the experiment result, we summarize how to adjust the parameter for better performance under different scenarios. We also use several methods to visualize the effect of different attack and explain the effectiveness of ADVKD.

preprint2022arXiv

A Multi-Behavior Planning Framework for Robot Guide

The guiding task of a mobile robot requires not only human-aware navigation, but also appropriate yet timely interaction for active instruction. State-of-the-art tour-guide models limit their socially-aware consideration to adapting to users' motion, ignoring the interactive behavior planning to fulfill the communicative demands. We propose a multi-behavior planning framework based on Monte Carlo Tree Search to better assist users to understand confusing scene contexts, select proper paths and timely arrive at the destination. To provide proactive guidance, we construct a sampling-based probability model of human motion to consider the interrelated effects between robots and humans. We validate our method both in simulation and real-world experiments along with performance comparison with state-of-the-art models.

preprint2022arXiv

A physical perturbation based study on the prediction of free-fall disks with chaotic modes in the water

We report a phenomenon that physical perturbations sometimes can benefit the certainty of a free-fall motion with chaotic modes, albeit, as commonly believed, they can ruin it. We statistically compare those factors that may lead to uncertainty, by which we find that the growth of the standard deviation of the landing locations is directly determined by the physical perturbations. A significant yardstick is defined in the meantime. This temporal criterion is of big relevance to the replicability of such problems experimentally, although they are inherently chaotic. Our hypothesis is verified by experiments from other literature. This outcome also provides a practical strategy to evaluate the credible prediction time by estimating the disturbances from physical parameters as a priori.

preprint2022arXiv

Absorbance Enhancement of Monolayer MoS$_2$ in a Perfect Absorbing System

We reveal numerically and experimentally that dielectric resonance can enhance the absorbance and emission of monolayer MoS$_2$. By quantifying the absorbance of the Si disk resonators and the monolayer MoS$_2$ separately, a model taking into account of absorbance as well as quantum efficiency modifications by the dielectric disk resonators successfully explains the observed emission enhancement under the normal light incidence. It is demonstrated that the experimentally observed emission enhancement at different pump wavelength results from the absorbance enhancement, which compensates the emission quenching by the disk resonators. In order to further maximize the absorbance value of monolayer MoS$_2$, a perfect absorbing structure is proposed. By placing a Au mirror beneath the Si nanodisks, the incident electromagnetic power is fully absorbed by the hybrid monolayer MoS$_2$-disk system. It is demonstrated that the electromagnetic power is re-distributed within the hybrid structure and 53\% of the total power is absorbed by the monolayer MoS$_2$ at the perfect absorbing wavelength.

preprint2022arXiv

Adversarial Attacks and Defense Methods for Power Quality Recognition

Vulnerability of various machine learning methods to adversarial examples has been recently explored in the literature. Power systems which use these vulnerable methods face a huge threat against adversarial examples. To this end, we first propose a signal-specific method and a universal signal-agnostic method to attack power systems using generated adversarial examples. Black-box attacks based on transferable characteristics and the above two methods are also proposed and evaluated. We then adopt adversarial training to defend systems against adversarial attacks. Experimental analyses demonstrate that our signal-specific attack method provides less perturbation compared to the FGSM (Fast Gradient Sign Method), and our signal-agnostic attack method can generate perturbations fooling most natural signals with high probability. What's more, the attack method based on the universal signal-agnostic algorithm has a higher transfer rate of black-box attacks than the attack method based on the signal-specific algorithm. In addition, the results show that the proposed adversarial training improves robustness of power systems to adversarial examples.

preprint2022arXiv

An Efficient Coarse-to-Fine Facet-Aware Unsupervised Summarization Framework based on Semantic Blocks

Unsupervised summarization methods have achieved remarkable results by incorporating representations from pre-trained language models. However, existing methods fail to consider efficiency and effectiveness at the same time when the input document is extremely long. To tackle this problem, in this paper, we proposed an efficient Coarse-to-Fine Facet-Aware Ranking (C2F-FAR) framework for unsupervised long document summarization, which is based on the semantic block. The semantic block refers to continuous sentences in the document that describe the same facet. Specifically, we address this problem by converting the one-step ranking method into the hierarchical multi-granularity two-stage ranking. In the coarse-level stage, we propose a new segment algorithm to split the document into facet-aware semantic blocks and then filter insignificant blocks. In the fine-level stage, we select salient sentences in each block and then extract the final summary from selected sentences. We evaluate our framework on four long document summarization datasets: Gov-Report, BillSum, arXiv, and PubMed. Our C2F-FAR can achieve new state-of-the-art unsupervised summarization results on Gov-Report and BillSum. In addition, our method speeds up 4-28 times more than previous methods.\footnote{\url{https://github.com/xnliang98/c2f-far}}

preprint2022arXiv

An inverse random source problem for the Helium production-diffusion equation driven by a fractional Brownian motion

In this paper, we consider the prediction of the helium concentrations as function of a spatially variable source term perturbed by fractional Brownian motion. For the direct problem, we show that it is well-posed and has a unique mild solution under some conditions. For the inverse problem, the uniqueness and the instability are given. In the meanwhile, we determine the statistical properties of the source from the expectation and covariance of the final-time data u(r,T). Finally, numerical implements are given to verify the effectiveness of the proposed reconstruction.

preprint2022arXiv

Analyzing the Intensity of Complaints on Social Media

Complaining is a speech act that expresses a negative inconsistency between reality and human expectations. While prior studies mostly focus on identifying the existence or the type of complaints, in this work, we present the first study in computational linguistics of measuring the intensity of complaints from text. Analyzing complaints from such perspective is particularly useful, as complaints of certain degrees may cause severe consequences for companies or organizations. We create the first Chinese dataset containing 3,103 posts about complaints from Weibo, a popular Chinese social media platform. These posts are then annotated with complaints intensity scores using Best-Worst Scaling (BWS) method. We show that complaints intensity can be accurately estimated by computational models with the best mean square error achieving 0.11. Furthermore, we conduct a comprehensive linguistic analysis around complaints, including the connections between complaints and sentiment, and a cross-lingual comparison for complaints expressions used by Chinese and English speakers. We finally show that our complaints intensity scores can be incorporated for better estimating the popularity of posts on social media.

preprint2022arXiv

Attention-based Multimodal Feature Representation Model for Micro-video Recommendation

In recommender systems, models mostly use a combination of embedding layers and multilayer feedforward neural networks. The high-dimensional sparse original features are downscaled in the embedding layer and then fed into the fully connected network to obtain prediction results. However, the above methods have a rather obvious problem, that is, the features directly input are treated as independent individuals, and in fact there are internal correlations between features and features, and even different features have different importance in the recommendation. In this regard, this paper adopts a self-attentive mechanism to mine the internal correlations between features as well as their relative importance. In recent years, as a special form of attention mechanism, self-attention mechanism is favored by many researchers. The self-attentive mechanism captures the internal correlation of data or features by learning itself, thus reducing the dependence on external sources. Therefore, this paper adopts a multi-headed self-attentive mechanism to mine the internal correlations between features and thus learn the internal representation of features. At the same time, considering the rich information often hidden between features, the new feature representation obtained by crossover between the two is likely to imply the new description of the user likes the item. However, not all crossover features are meaningful, i.e., there is a problem of limited expression of feature combinations. Therefore, this paper adopts an attention-based approach to learn the external cross-representation of features.

preprint2022arXiv

Continuous Sign Language Recognition via Temporal Super-Resolution Network

Aiming at the problem that the spatial-temporal hierarchical continuous sign language recognition model based on deep learning has a large amount of computation, which limits the real-time application of the model, this paper proposes a temporal super-resolution network(TSRNet). The data is reconstructed into a dense feature sequence to reduce the overall model computation while keeping the final recognition accuracy loss to a minimum. The continuous sign language recognition model(CSLR) via TSRNet mainly consists of three parts: frame-level feature extraction, time series feature extraction and TSRNet, where TSRNet is located between frame-level feature extraction and time-series feature extraction, which mainly includes two branches: detail descriptor and rough descriptor. The sparse frame-level features are fused through the features obtained by the two designed branches as the reconstructed dense frame-level feature sequence, and the connectionist temporal classification(CTC) loss is used for training and optimization after the time-series feature extraction part. To better recover semantic-level information, the overall model is trained with the self-generating adversarial training method proposed in this paper to reduce the model error rate. The training method regards the TSRNet as the generator, and the frame-level processing part and the temporal processing part as the discriminator. In addition, in order to unify the evaluation criteria of model accuracy loss under different benchmarks, this paper proposes word error rate deviation(WERD), which takes the error rate between the estimated word error rate (WER) and the reference WER obtained by the reconstructed frame-level feature sequence and the complete original frame-level feature sequence as the WERD. Experiments on two large-scale sign language datasets demonstrate the effectiveness of the proposed model.

preprint2022arXiv

Critiquing-based Modeling of Subjective Preferences

Applications designed for entertainment and other non-instrumental purposes are challenging to optimize because the relationships between system parameters and user experience can be unclear. Ideally, we would crowdsource these design questions, but existing approaches are geared towards evaluation or ranking discrete choices and not for optimizing over continuous parameter spaces. In addition, users are accustomed to informally expressing opinions about experiences as critiques (e.g. it's too cold, too spicy, too big), rather than giving precise feedback as an optimization algorithm would require. Unfortunately, it can be difficult to analyze qualitative feedback, especially in the context of quantitative modeling. In this article, we present collective criticism, a critiquing-based approach for modeling relationships between system parameters and subjective preferences. We transform critiques, such as "it was too easy/too challenging", into censored intervals and analyze them using interval regression. Collective criticism has several advantages over other approaches: "too much/too little"-style feedback is intuitive for users and allows us to build predictive models for the optimal parameterization of the variables being critiqued. We present two studies where we model: (i) aesthetic preferences for images generated with neural style transfer, and (ii) users' experiences of challenge in the video game Tetris. These studies demonstrate the flexibility of our approach, and show that it produces robust results that are straightforward to interpret and inline with users' stated preferences.

preprint2022arXiv

Cross-domain Trajectory Prediction with CTP-Net

Most pedestrian trajectory prediction methods rely on a huge amount of trajectories annotation, which is time-consuming and expensive. Moreover, a well-trained model may not effectively generalize to a new scenario captured by another camera. Therefore, it is desirable to adapt the model trained on an annotated source domain to the target domain. To achieve domain adaptation for trajectory prediction, we propose a Cross-domain Trajectory Prediction Network (CTP-Net). In this framework, encoders are used in both domains to encode the observed trajectories, then their features are aligned by a cross-domain feature discriminator. Further, considering the consistency between the observed and the predicted trajectories, a target domain offset discriminator is utilized to adversarially regularize the future trajectory predictions to be in line with the observed trajectories. Extensive experiments demonstrate the effectiveness of our method on domain adaptation for pedestrian trajectory prediction.

preprint2022arXiv

Decoupled IoU Regression for Object Detection

Non-maximum suppression (NMS) is widely used in object detection pipelines for removing duplicated bounding boxes. The inconsistency between the confidence for NMS and the real localization confidence seriously affects detection performance. Prior works propose to predict Intersection-over-Union (IoU) between bounding boxes and corresponding ground-truths to improve NMS, while accurately predicting IoU is still a challenging problem. We argue that the complex definition of IoU and feature misalignment make it difficult to predict IoU accurately. In this paper, we propose a novel Decoupled IoU Regression (DIR) model to handle these problems. The proposed DIR decouples the traditional localization confidence metric IoU into two new metrics, Purity and Integrity. Purity reflects the proportion of the object area in the detected bounding box, and Integrity refers to the completeness of the detected object area. Separately predicting Purity and Integrity can divide the complex mapping between the bounding box and its IoU into two clearer mappings and model them independently. In addition, a simple but effective feature realignment approach is also introduced to make the IoU regressor work in a hindsight manner, which can make the target mapping more stable. The proposed DIR can be conveniently integrated with existing two-stage detectors and significantly improve their performance. Through a simple implementation of DIR with HTC, we obtain 51.3% AP on MS COCO benchmark, which outperforms previous methods and achieves state-of-the-art.

preprint2022arXiv

Designer magnetic topological graphene nanoribbons

The interplay of magnetism and topology lies at the heart of condensed matter physics, which offers great opportunities to design intrinsic magnetic topological materials hosting a variety of exotic topological quantum states including the quantum anomalous Hall effect (QAHE), axion insulator state, and Majorana bound states. Extending this concept to one-dimension (1D) systems offers additional rich quantum spin physics with great promise for molecular-scale spintronics. Despite recent progress in the discovery of symmetry-protected topological quantum phases in 1D graphene nanoribbons (GNRs), the rational design and realization of magnetic topological GNRs (MT-GNRs) represents a grand challenge, as one must tackle multiple dimensions of complexity including time-reversal symmetry (TRS), spatial symmetry (width, edge, end geometry) and many-electron correlations. Here, we devised a new route involving the real- and reciprocal-space descriptions by unifying the chemists and physicists perspectives, for the design of such MT-GNRs with non-trivial electronic topology and robust magnetic terminal. Classic Clar's rule offers a conceptually qualitative real-space picture to predict the transition from closed-shell to open-shell with terminal magnetism, and band gap reopening with possible non-trivial electronic topology in a series of wave-like GNRs, which are further verified by first principle calculations of band-structure topology in a momentum-space. With the advance of on-surface synthesis and careful design of molecular precursors, we have fabricated these MT-GNRs with observation of topological edge bands, whose terminal pi-magnetism can be directly captured using a single-nickelocene spin sensor. Moreover, the transition from strong anti-ferromagnetic to weak coupling (paramagnetism-like) between terminal spins can be controlled by tuning the length of MT-GNRs.

preprint2022arXiv

Discovery of extended structure around open cluster COIN-Gaia 13 based on Gaia EDR3

COIN-Gaia 13 is a newly discovered open cluster revealed by Gaia DR2 data. It is a nearby open cluster with a distance of about 513 pc. Combined with the five-dimensional astrometric data of Gaia EDR3 with higher accuracy, we use the membership assignment algorithm (pyUPMASK) to determine the membership of COIN-Gaia 13 in a large extended spatial region. The cluster has found 478 candidate members. After obtaining reliable cluster members, we further study its basic properties and spatial distribution. Our results show that there is an obvious extended structure of the cluster in the X-Y plane. This elongated structure is distributed along the spiral arm, and the whole length is about 270 pc. The cluster age is 250 Myr, the total mass is about 439 M$_\odot$, and the tidal radius of the cluster is about 11 pc. Since more than half of the member stars (352 stars) are located outside twice the tidal radius, it is suspected that this cluster is undergoing the dynamic dissolution process. Furthermore, the spatial distribution and kinematic analysis indicate that the extended structure in COIN-Gaia 13 is more likely to be caused by the differential rotation of the Galaxy.

preprint2022arXiv

Doctor Recommendation in Online Health Forums via Expertise Learning

Huge volumes of patient queries are daily generated on online health forums, rendering manual doctor allocation a labor-intensive task. To better help patients, this paper studies a novel task of doctor recommendation to enable automatic pairing of a patient to a doctor with relevant expertise. While most prior work in recommendation focuses on modeling target users from their past behavior, we can only rely on the limited words in a query to infer a patient's needs for privacy reasons. For doctor modeling, we study the joint effects of their profiles and previous dialogues with other patients and explore their interactions via self-learning. The learned doctor embeddings are further employed to estimate their capabilities of handling a patient query with a multi-head attention mechanism. For experiments, a large-scale dataset is collected from Chunyu Yisheng, a Chinese online health forum, where our model exhibits the state-of-the-art results, outperforming baselines only consider profiles and past dialogues to characterize a doctor.

preprint2022arXiv

Domain Invariant Model with Graph Convolutional Network for Mammogram Classification

Due to its safety-critical property, the image-based diagnosis is desired to achieve robustness on out-of-distribution (OOD) samples. A natural way towards this goal is capturing only clinically disease-related features, which is composed of macroscopic attributes (e.g., margins, shapes) and microscopic image-based features (e.g., textures) of lesion-related areas. However, such disease-related features are often interweaved with data-dependent (but disease irrelevant) biases during learning, disabling the OOD generalization. To resolve this problem, we propose a novel framework, namely Domain Invariant Model with Graph Convolutional Network (DIM-GCN), which only exploits invariant disease-related features from multiple domains. Specifically, we first propose a Bayesian network, which explicitly decomposes the latent variables into disease-related and other disease-irrelevant parts that are provable to be disentangled from each other. Guided by this, we reformulate the objective function based on Variational Auto-Encoder, in which the encoder in each domain has two branches: the domain-independent and -dependent ones, which respectively encode disease-related and -irrelevant features. To better capture the macroscopic features, we leverage the observed clinical attributes as a goal for reconstruction, via Graph Convolutional Network (GCN). Finally, we only implement the disease-related features for prediction. The effectiveness and utility of our method are demonstrated by the superior OOD generalization performance over others on mammogram benign/malignant diagnosis.

preprint2022arXiv

Estimating accurate reddening values of LAMOST M dwarfs

M dwarfs are the dominating type of stars in the solar neighbourhood. They serve as excellent tracers for the study of the distribution and properties of the nearby interstellar dust. In this work, we aim to obtain high accuracy reddening values of M dwarf stars from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Data Release 8 (DR8). Combining the LAMOST spectra with the high-quality optical photometry from the Gaia Early Data Release 3 (Gaia EDR3), we have estimated the reddening values $E(G_{\rm BP}-G_{\rm RP})$ of 641,426 M dwarfs with the machine-learning algorithm Random Forest regression. The typical reddening uncertainty is only 0.03 mag in $E(G_{\rm BP}-G_{\rm RP})$. We have obtained the reddening coefficient $R_{(G_{\rm BP}-G_{\rm RP})}$, which is a function of the stellar intrinsic colour $(G_{\rm BP}-G_{\rm RP})_0$ and reddening value $E(B-V)$. The values of $E(B-V)$ are also provided for the individual stars in our catalogue. Our resultant high accuracy reddening values of M dwarfs, combined with the Gaia parallaxes, will be very powerful to map the fine structures of the dust in the solar neighbourhood.

preprint2022arXiv

Fermi Observations of GRB 220426A: a burst similar to GRB 090902B

We report on a very bright, long-duration gamma-ray burst (GRB), GRB~220426A, observed by \emph{Fermi} satellite. GRB~220426A with total duration of $T_{90}=6$~s is composed with two main pulses and some sub-peaks. The spectral analysis of this burst with Band function reveals that both the time-integrated and the time-resolved spectra are very narrow with high $α\gtrsim 0.2$ and low $β\lesssim -3.1$. It is strong reminiscent of GRB~090902B, a special GRB with identification of the photospheric emission. Then, we perform the spectral analysis of this burst based on a non-dissipated photospheric emission, which can be well modelled as the multicolor-blackbody with a cutoff power-law distribution of the thermal temperature. The spectral fittings reveal that the photospheric emission can well describe the radiation spectrum of this burst. We conclude that this burst would be a second burst in the class of GRB~090902B observed by \emph{Fermi} satellite. We also discuss the physics of photosphere and the origin of the high-energy component in GRB~220426A .

preprint2022arXiv

Global Classical Solutions to the Full Compressible Navier-Stokes System in 3D Exterior Domains

The full compressible Navier-Stokes system (FNS) describing the motion of a viscous, compressible, heat-conductive, and Newtonian polytropic fluid in a three-dimensional (3D) exterior domain is studied. For the initial-boundary-value problem with the slip boundary conditions on the velocity and the Neumann one on the temperature, it is shown that there exists a unique global classical solutions with the initial data which are of small energy but possibly large oscillations. In particular, both the density and temperature are allowed to vanish initially. This is the first result about classical solutions of FNS system in 3D exterior domain.

preprint2022arXiv

Global Existence of Classical Solutions to Full Compressible Navier-Stokes System with Large Oscillations and Vacuum in 3D Bounded Domains

The full compressible Navier-Stokes system describing the motion of a viscous, compressible, heat-conductive, and Newtonian polytropic fluid is studied in a three-dimensional simply connected bounded domain with smooth boundary having a finite number of two-dimensional connected components. For the initial-boundary-value problem with slip boundary conditions on the velocity and Neumann boundary one on the temperature, the global existence of classical and weak solutions which are of small energy but possibly large oscillations is established. In particular, both the density and temperature are allowed to vanish initially. Finally, the exponential stability of the density, velocity, and temperature is also obtained. Moreover, it is shown that for the classical solutions, the oscillation of the density will grow unboundedly in the long run with an exponential rate provided vacuum appears (even at a point) initially. This is the first result concerning the global existence of classical solutions to the full compressible Navier-Stokes equations with vacuum in general three-dimensional bounded smooth domains.

preprint2022arXiv

Hubble Space Telescope Observations of Active Asteroid P/2020 O1 (Lemmon-PANSTARRS)

We present Hubble Space Telescope observations of active asteroid P/2020 O1 taken to examine its development for a year after perihelion. We find that the mass loss peaks <~1 kg/s in 2020 August and then declines to nearly zero over four months. Long-duration mass loss (~180 days) is consistent with a sublimation origin, indicating that this object is likely an ice-bearing main-belt comet. Equilibrium sublimation of water ice from an area as small as 1580 m^2 can supply the observed mass loss. Time-series photometry shows tentative evidence for extremely rapid rotation (double-peaked period < 2 hr) of the small nucleus (effective radius ~420 m). Ejection velocities of 0.1 mm particles are comparable to the 0.3 m/s gravitational escape speed from the nucleus, while larger particles are ejected at speeds less than the escape velocity. These properties are consistent with the sublimation of near-surface ice aided by centripetal acceleration. If water ice sublimation is confirmed, P/2020 O1 would be the icy asteroid with the smallest semimajor axis (highest temperature), setting new bounds on the distribution of ice in the asteroid belt.

preprint2022arXiv

Many-body exciton and inter-valley correlations in heavily electron-doped WSe$_2$ monolayers

In monolayer transition-metal dichalcogenide semiconductors, many-body correlations can manifest in optical spectra when photoexcited electron-hole pairs (excitons) are introduced into a 2D Fermi sea of mobile carriers. At low carrier densities, the formation of positively and negatively charged excitons ($X^\pm$) is well documented. However, in WSe$_2$ monolayers, an additional absorption resonance, often called $X^{-\prime}$, emerges at high electron density. Its origin is not understood. Here we investigate the $X^{-\prime}$ state via polarized absorption spectroscopy of electrostatically-gated WSe$_2$ monolayers in high magnetic fields to 60~T. Field-induced filling and emptying of the lowest optically-active Landau level in the $K'$ valley causes repeated quenching of the corresponding optical absorption. Surprisingly, however, these quenchings are accompanied by absorption changes to higher-lying Landau levels in both $K'$ and $K$ valleys, which are unoccupied. These results cannot be reconciled within a single-particle picture, and demonstrate the many-body nature and inter-valley correlations of the $X^{-\prime}$ quasiparticle state.

preprint2022arXiv

Mobility Support for Millimeter Wave Communications: Opportunities and Challenges

Millimeter-wave (mmWave) communication technology offers a potential and promising solution to support 5G and B5G wireless networks in dynamic scenarios and applications. However, mobility introduces many challenges as well as opportunities to mmWave applications. To address these problems, we conduct a survey of the opportunities and technologies to support mmWave communications in mobile scenarios. Firstly, we summarize the mobile scenarios where mmWave communications are exploited, including indoor wireless local area network (WLAN) or wireless personal area network (WPAN), cellular access, vehicle-to-everything (V2X), high speed train (HST), unmanned aerial vehicle (UAV), and the new space-air-ground-sea communication scenarios. Then, to address users' mobility impact on the system performance in different application scenarios, we introduce several representative mobility models in mmWave systems, including human mobility, vehicular mobility, high speed train mobility and ship mobility. Next we survey the key challenges and existing solutions to mmWave applications, such as channel modeling, channel estimation, anti-blockage, and capacity improvement. Lastly, we discuss the open issues concerning mobility-aware mmWave communications that deserve further investigation. In particular, we highlight future heterogeneous mobile networks, dynamic resource management, artificial intelligence (AI) for mobility and integration of geographical information, deployment of large intelligent surface and reconfigurable antenna technology, and finally, the evolution to Terahertz (THz) communications.

preprint2022arXiv

Multi-scale temporal network for continuous sign language recognition

Continuous Sign Language Recognition (CSLR) is a challenging research task due to the lack of accurate annotation on the temporal sequence of sign language data. The recent popular usage is a hybrid model based on "CNN + RNN" for CSLR. However, when extracting temporal features in these works, most of the methods using a fixed temporal receptive field and cannot extract the temporal features well for each sign language word. In order to obtain more accurate temporal features, this paper proposes a multi-scale temporal network (MSTNet). The network mainly consists of three parts. The Resnet and two fully connected (FC) layers constitute the frame-wise feature extraction part. The time-wise feature extraction part performs temporal feature learning by first extracting temporal receptive field features of different scales using the proposed multi-scale temporal block (MST-block) to improve the temporal modeling capability, and then further encoding the temporal features of different scales by the transformers module to obtain more accurate temporal features. Finally, the proposed multi-level Connectionist Temporal Classification (CTC) loss part is used for training to obtain recognition results. The multi-level CTC loss enables better learning and updating of the shallow network parameters in CNN, and the method has no parameter increase and can be flexibly embedded in other models. Experimental results on two publicly available datasets demonstrate that our method can effectively extract sign language features in an end-to-end manner without any prior knowledge, improving the accuracy of CSLR and achieving competitive results.

preprint2022arXiv

On genuine entanglement for tripartite systems

We investigate the genuine entanglement in tripartite systems based on partial transposition and the norm of correlation tensors of the density matrices. We first derive an analytical sufficient criterion to detect genuine entanglement of tripartite qubit quantum states combining with the partial transposition of the density matrices. Then we use the norm of correlation tensors to study genuine entanglement for tripartite qudit quantum states and obtain a genuine entanglement criterion by constructing certain matrices. With detailed examples our results are seen to be able to detect more genuine tripartite entangled states than previous studies.

preprint2022arXiv

p-orbital disclination states in non-Euclidean geometries

Disclinations are ubiquitous lattice defects existing in almost all crystalline materials. In two-dimensional nanomaterials, disclinations lead to the warping and deformation of the hosting material, yielding non-Euclidean geometries. However, such geometries have never been investigated experimentally in the context of topological phenomena. Here, by creating the physical realization of disclinations in conical and saddle-shaped acoustic systems, we demonstrate that disclinations can lead to topologically protected bound modes in non-Euclidean surfaces. In the designed honeycomb sonic crystal for p-orbital acoustic waves, non-Euclidean geometry interplay with the p-orbital physics and the band topology, showing intriguing emergent features as confirmed by consistent experiments and simulations. Our study opens a pathway towards topological phenomena in non-Euclidean geometries that may inspire future studies on, e.g., electrons and phonons in nanomaterials with curved surfaces.

preprint2022arXiv

Pasta phases in neutron stars under strong magnetic fields

In the present work, we consider nuclear matter in the innermost crust of neutron stars under the presence of a strong magnetic field within the framework of a relativistic mean-field description. Two models with a different slope of the symmetry energy are considered in order to discuss the density-dependence of the equation of state on the crust structure. The non-homogeneous matter in $β$-equilibrium is described within the coexisting phases method, and the effect of including the anomalous magnetic moment is discussed. Five different geometries for the pasta structures are considered. It is shown that strong magnetic fields cause an extension of the inner crust of the neutron stars, with the occurrence of a series of disconnected non-homogeneous matter regions above the one existing for a null magnetic field. Moreover, we observed that in these disconnected regions, for some values of the magnetic field, all five different cluster geometrical shapes occur, and the gas density is close to the cluster density. Also, the pressure at the neutron star crust-core transition much larger than the pressure obtained for a zero magnetic field. Another noticeable effect of the presence of strong magnetic fields is the increase of the proton fraction, favoring the appearance of protons in the gas background.

preprint2022arXiv

Performance evaluation of baseline-dependent averaging based onfull-scale SKA1-LOW simulation

The Square Kilometre Array (SKA) is the largest radio interferometer under construction in the world. Its immense amount of visibility data poses a considerable challenge to the subsequent processing by the science data processor (SDP). Baseline dependent averaging (BDA), which reduces the amount of visibility data based on the baseline distribution of the radio interferometer, has become a focus of SKA SDP development. This paper developed and implemented a full-featured BDA module based on Radio Astronomy Simulation, Calibration and Imaging Library (RASCIL). Simulated observations were then performed with RASCIL based on a full-scale SKA1-LOW configuration. The performance of the BDA was systematically investigated and evaluated based on the simulated data. The experimental results presented that the amount of visibility data is reduced by about 50\% to 85\% for different time intervals ($Δt_{max}$). In addition, different $Δt_{max}$ have a significant effect on the imaging quality. The smaller the $Δt_{max}$, the smaller the degradation of the imaging quality.

preprint2022arXiv

Quantum control and quantum speed limits in supersymmetric potentials

Supersymmetry allows one to build a hierarchy of Hamiltonians that share the same spectral properties and which are pairwise connected through common superpotentials. The iso-spectral properties of these Hamiltonians imply that the dynamics and therefore control of different eigenstates are connected through supersymmetric intertwining relations. In this work we explore how this enables one to study general dynamics, shortcuts to adiabaticity (STA) and quantum speed limits for distinct states of different supersymmetric partner potentials by using the infinite box as an example.

preprint2022arXiv

Recognition of Handwritten Chinese Text by Segmentation: A Segment-annotation-free Approach

Online and offline handwritten Chinese text recognition (HTCR) has been studied for decades. Early methods adopted oversegmentation-based strategies but suffered from low speed, insufficient accuracy, and high cost of character segmentation annotations. Recently, segmentation-free methods based on connectionist temporal classification (CTC) and attention mechanism, have dominated the field of HCTR. However, people actually read text character by character, especially for ideograms such as Chinese. This raises the question: are segmentation-free strategies really the best solution to HCTR? To explore this issue, we propose a new segmentation-based method for recognizing handwritten Chinese text that is implemented using a simple yet efficient fully convolutional network. A novel weakly supervised learning method is proposed to enable the network to be trained using only transcript annotations; thus, the expensive character segmentation annotations required by previous segmentation-based methods can be avoided. Owing to the lack of context modeling in fully convolutional networks, we propose a contextual regularization method to integrate contextual information into the network during the training stage, which can further improve the recognition performance. Extensive experiments conducted on four widely used benchmarks, namely CASIA-HWDB, CASIA-OLHWDB, ICDAR2013, and SCUT-HCCDoc, show that our method significantly surpasses existing methods on both online and offline HCTR, and exhibits a considerably higher inference speed than CTC/attention-based approaches.

preprint2022arXiv

Rethinking Attention-Model Explainability through Faithfulness Violation Test

Attention mechanisms are dominating the explainability of deep models. They produce probability distributions over the input, which are widely deemed as feature-importance indicators. However, in this paper, we find one critical limitation in attention explanations: weakness in identifying the polarity of feature impact. This would be somehow misleading -- features with higher attention weights may not faithfully contribute to model predictions; instead, they can impose suppression effects. With this finding, we reflect on the explainability of current attention-based techniques, such as Attentio$\odot$Gradient and LRP-based attention explanations. We first propose an actionable diagnostic methodology (henceforth faithfulness violation test) to measure the consistency between explanation weights and the impact polarity. Through the extensive experiments, we then show that most tested explanation methods are unexpectedly hindered by the faithfulness violation issue, especially the raw attention. Empirical analyses on the factors affecting violation issues further provide useful observations for adopting explanation methods in attention models.

preprint2022arXiv

Saliency in Augmented Reality

With the rapid development of multimedia technology, Augmented Reality (AR) has become a promising next-generation mobile platform. The primary theory underlying AR is human visual confusion, which allows users to perceive the real-world scenes and augmented contents (virtual-world scenes) simultaneously by superimposing them together. To achieve good Quality of Experience (QoE), it is important to understand the interaction between two scenarios, and harmoniously display AR contents. However, studies on how this superimposition will influence the human visual attention are lacking. Therefore, in this paper, we mainly analyze the interaction effect between background (BG) scenes and AR contents, and study the saliency prediction problem in AR. Specifically, we first construct a Saliency in AR Dataset (SARD), which contains 450 BG images, 450 AR images, as well as 1350 superimposed images generated by superimposing BG and AR images in pair with three mixing levels. A large-scale eye-tracking experiment among 60 subjects is conducted to collect eye movement data. To better predict the saliency in AR, we propose a vector quantized saliency prediction method and generalize it for AR saliency prediction. For comparison, three benchmark methods are proposed and evaluated together with our proposed method on our SARD. Experimental results demonstrate the superiority of our proposed method on both of the common saliency prediction problem and the AR saliency prediction problem over benchmark methods. Our dataset and code are available at: https://github.com/DuanHuiyu/ARSaliency.

preprint2022arXiv

Searching Extra-tidal Features around the Globular Cluster Whiting 1

Whiting 1 is a faint and young globular cluster in the halo of the Milky Way, and was suggested to have originated in the Sagittarius spherical dwarf galaxy (Sgr dSph). In this paper, we use the deep DESI Legacy Imaging Surveys to explore tentative spatial connection between Whiting 1 and the Sgr dSph. We redetermine the fundamental parameters of Whiting 1 and use the best-fitting isochrone (age $τ$=6.5 Gyr, metalicity Z=0.005 and $\rm d_{\odot}$=26.9 kpc) to construct a theoretical matched filter for the extra-tidal features searching. Without any smooth technique to the matched filter density map, we detect a round-shape feature with possible leading and trailing tails on either side of the cluster. This raw image is not totally new compared to old discoveries, but confirms that no more large-scale features can be detected under a depth of r<=22.5 mag. In our results, the whole feature stretches 0.1-0.2 degree along the orbit of Whiting 1, which gives a much larger area than the cluster core. The tails on both sides of the cluster align along the orbital direction of the Sgr dSph as well as the cluster itself, which implies that these debris are probably stripped remnants of Whiting 1 by the Milky Way.

preprint2022arXiv

Single-stage Rotate Object Detector via Two Points with Solar Corona Heatmap

Oriented object detection is a crucial task in computer vision. Current top-down oriented detection methods usually directly detect entire objects, and not only neglecting the authentic direction of targets, but also do not fully utilise the key semantic information, which causes a decrease in detection accuracy. In this study, we developed a single-stage rotating object detector via two points with a solar corona heatmap (ROTP) to detect oriented objects. The ROTP predicts parts of the object and then aggregates them to form a whole image. Herein, we meticulously represent an object in a random direction using the vertex, centre point with width, and height. Specifically, we regress two heatmaps that characterise the relative location of each object, which enhances the accuracy of locating objects and avoids deviations caused by angle predictions. To rectify the central misjudgement of the Gaussian heatmap on high-aspect ratio targets, we designed a solar corona heatmap generation method to improve the perception difference between the central and non-central samples. Additionally, we predicted the vertex relative to the direction of the centre point to connect two key points that belong to the same goal. Experiments on the HRSC 2016, UCASAOD, and DOTA datasets show that our ROTP achieves the most advanced performance with a simpler modelling and less manual intervention.

preprint2022arXiv

SPTS: Single-Point Text Spotting

Existing scene text spotting (i.e., end-to-end text detection and recognition) methods rely on costly bounding box annotations (e.g., text-line, word-level, or character-level bounding boxes). For the first time, we demonstrate that training scene text spotting models can be achieved with an extremely low-cost annotation of a single-point for each instance. We propose an end-to-end scene text spotting method that tackles scene text spotting as a sequence prediction task. Given an image as input, we formulate the desired detection and recognition results as a sequence of discrete tokens and use an auto-regressive Transformer to predict the sequence. The proposed method is simple yet effective, which can achieve state-of-the-art results on widely used benchmarks. Most significantly, we show that the performance is not very sensitive to the positions of the point annotation, meaning that it can be much easier to be annotated or even be automatically generated than the bounding box that requires precise positions. We believe that such a pioneer attempt indicates a significant opportunity for scene text spotting applications of a much larger scale than previously possible. The code is available at https://github.com/shannanyinxiang/SPTS.

preprint2022arXiv

Successful New-entry Prediction for Multi-Party Online Conversations via Latent Topics and Discourse Modeling

With the increasing popularity of social media, online interpersonal communication now plays an essential role in people's everyday information exchange. Whether and how a newcomer can better engage in the community has attracted great interest due to its application in many scenarios. Although some prior works that explore early socialization have obtained salient achievements, they are focusing on sociological surveys based on the small group. To help individuals get through the early socialization period and engage well in online conversations, we study a novel task to foresee whether a newcomer's message will be responded to by other participants in a multi-party conversation (henceforth Successful New-entry Prediction). The task would be an important part of the research in online assistants and social media. To further investigate the key factors indicating such engagement success, we employ an unsupervised neural network, Variational Auto-Encoder (VAE), to examine the topic content and discourse behavior from newcomer's chatting history and conversation's ongoing context. Furthermore, two large-scale datasets, from Reddit and Twitter, are collected to support further research on new-entries. Extensive experiments on both Twitter and Reddit datasets show that our model significantly outperforms all the baselines and popular neural models. Additional explainable and visual analyses on new-entry behavior shed light on how to better join in others' discussions.

preprint2022arXiv

Testing the seesaw mechanisms via displaced right-handed neutrinos from a light scalar at the HL-LHC

We investigate the pair production of right-handed neutrinos from the decay of a light $B-L$ scalar in the $U(1)_{B-L}$ model. The $B-L$ scalar mixes to the SM Higgs, and the physical scalar is required to be lighter than the observed Higgs. The produced right-handed neutrinos are predicted to be long-lived according to the type-I seesaw mechanism, and yield potentially distinct signatures such as displaced vertex and time-delayed leptons at the CMS/ATLAS/LHCb, as well as signatures at the far detectors including the CODEX-b, FACET, FASER, MoEDAL-MAPP and MATHUSLA. We analyze the sensitivity reach at the HL-LHC for the right-handed neutrinos with masses of 2.5 $\sim$ 30 GeV, showing that the active-sterile mixing to muons can be probed to $V_{μN} \sim 10^{-5}$ at the CMS/ATLAS/LHCb using the displaced vertex searches, and one magnitude lower at the MATHUSLA/CMS using time-delayed leptons searches, reaching the parameter space interesting for type-I seesaw mechanisms.

preprint2022arXiv

Topological equivalence canonical forms for linear multivariable systems without control

In this paper, we discuss the classification problem for linear time-invariant multivariable systems without control. It turns out that the observability and stability are invariant for topological equivalent systems. Abstract results concerning system decomposition according to eigenvalues and observability are obtained. Finally, as concrete examples, the topological equivalence canonical forms for a three dimensional system equipped with a scalar observation are presented explicitly.

preprint2022arXiv

TVShowGuess: Character Comprehension in Stories as Speaker Guessing

We propose a new task for assessing machines' skills of understanding fictional characters in narrative stories. The task, TVShowGuess, builds on the scripts of TV series and takes the form of guessing the anonymous main characters based on the backgrounds of the scenes and the dialogues. Our human study supports that this form of task covers comprehension of multiple types of character persona, including understanding characters' personalities, facts and memories of personal experience, which are well aligned with the psychological and literary theories about the theory of mind (ToM) of human beings on understanding fictional characters during reading. We further propose new model architectures to support the contextualized encoding of long scene texts. Experiments show that our proposed approaches significantly outperform baselines, yet still largely lag behind the (nearly perfect) human performance. Our work serves as a first step toward the goal of narrative character comprehension.

preprint2021arXiv

Accurate predictions of chaotic motion of a free fall disk

It is important to know the accurate trajectory of a free fall object in fluid (such as a spacecraft), whose motion might be chaotic in many cases. However, it is impossible to accurately predict its chaotic trajectory in a long enough duration by traditional numerical algorithms in double precision. In this paper, we give the accurate predictions of the same problem by a new strategy, namely the Clean Numerical Simulation (CNS). Without loss of generality, a free fall disk in water is considered, whose motion is governed by the Andersen-Pesavento-Wang model. We illustrate that convergent and reliable trajectories of a chaotic free fall disk in a long enough interval of time can be obtained by means of the CNS, but different traditional algorithms in double precision give disparate trajectories. Besides, unlike the traditional algorithms in double precision, the CNS can predict the accurate posture of the free fall disk near the vicinity of the bifurcation point of some physical parameters in a long duration. Therefore, the CNS can provide reliable prediction of chaotic systems in a long enough interval of time.

preprint2021arXiv

Global Existence of Strong and Weak Solutions to 2D Compressible Navier-Stokes System in Bounded Domains with Large Data and Vacuum

We study the barotropic compressible Navier-Stokes system where the shear viscosity is a positive constant and the bulk one proportional to a power of the density with the power bigger than one and a third. The system is subject to the Navier-slip boundary conditions in a general two-dimensional bounded simply connected domain. For initial density allowed to vanish, we establish the global existence of strong and weak solutions without any restrictions on the size of initial value. To get over the difficulties brought by boundary, on the one hand, we apply Riemann mapping theorem and the pull back Green's function method to get a pointwise representation of the effective viscous flux. On the other hand, observing that the orthogonality is preserved under conformal mapping due to its preservation on the angle, we use the slip boundary conditions to reduce the integral representation to the desired commutator form whose singularities can be cancelled out by using the estimates on the spatial gradient of the velocity.

preprint2021arXiv

Hydrogen molecule spectrum by many-body GW and Bethe-Salpeter equation

We check the ab initio GW approximation and Bethe-Salpeter equation (BSE) many-body methodology against the exact solution benchmark of the hydrogen molecule H$_2$ ground state and excitation spectrum, and in comparison with the configuration interaction (CI) and time-dependent Hartree-Fock methods. The comparison is made on all the states we could unambiguously identify from the excitonic wave functions' symmetry. At the equilibrium distance $R = 1.4 \, a_0$, the GW+BSE energy levels are in good agreement with the exact results, with an accuracy of 0.1~0.2 eV. GW+BSE potential-energy curves are also in good agreement with the CI and the exact result up to $2.3 \, a_0$. The solution no longer exists beyond $3.0 \, a_0$ for triplets ($4.3 \, a_0$ for singlets) due to instability of the ground state. We tried to improve the GW reference ground state by a renormalized random-phase approximation (r-RPA), but this did not solve the problem.

preprint2021arXiv

Mimicing the Kane-Mele type spin orbit interaction by spin-flexual phonon coupling in graphene devices

On the efforts of enhancing the spin orbit interaction (SOI) of graphene for seeking the dissipationless quantum spin Hall devices, unique Kane-Mele type SOI and high mobility samples are desired. However, common external decoration often introduces extrinsic Rashba-type SOI and simultaneous impurity scattering. Here we show, by the EDTA-Dy molecule decorating, the Kane-Mele type SOI is mimicked with even improved carrier mobility. It is evidenced by the suppressed weak localization at equal carrier densities and simultaneous Elliot-Yafet spin relaxation. The extracted spin scattering time is monotonically dependent on the carrier elastic scattering time, where the Elliot-Yafet plot gives the interaction strength of 3.3 meV. Improved quantum Hall plateaus can be even seen after the external operation. This is attributed to the spin-flexural phonon coupling induced by the enhanced graphene ripples, as revealed by the in-plane magnetotransport measurement.

preprint2021arXiv

Minority Oversampling for Imbalanced Time Series Classification

Many important real-world applications involve time-series data with skewed distribution. Compared to conventional imbalance learning problems, the classification of imbalanced time-series data is more challenging due to high dimensionality and high inter-variable correlation. This paper proposes a structure preserving Oversampling method to combat the High-dimensional Imbalanced Time-series classification (OHIT). OHIT first leverages a density-ratio based shared nearest neighbor clustering algorithm to capture the modes of minority class in high-dimensional space. It then for each mode applies the shrinkage technique of large-dimensional covariance matrix to obtain accurate and reliable covariance structure. Finally, OHIT generates the structure-preserving synthetic samples based on multivariate Gaussian distribution by using the estimated covariance matrices. Experimental results on several publicly available time-series datasets (including unimodal and multimodal) demonstrate the superiority of OHIT against the state-of-the-art oversampling algorithms in terms of F1, G-mean, and AUC.

preprint2021arXiv

Quantum Gaussian process regression

In this paper, a quantum algorithm based on gaussian process regression model is proposed. The proposed quantum algorithm consists of three sub-algorithms. One is the first quantum subalgorithm to efficiently generate mean predictor. The improved HHL algorithm is proposed to obtain the sign of outcomes. Therefore, the terrible situation that results is ambiguous in terms of original HHL algorithm is avoided, which makes whole algorithm more clear and exact. The other is to product covariance predictor with same method. Thirdly, the squared exponential covariance matrices are prepared that annihilation operator and generation operator are simulated by the unitary linear decomposition Hamiltonian simulation and kernel function vectors is generated with blocking coding techniques on covariance matrices. In addition, it is shown that the proposed quantum gaussian process regression algorithm can achieve quadratic faster over the classical counterpart.

preprint2021arXiv

Reducibility of relativistic Schrödinger equation with unbounded perturbations

In this paper, we prove a reducibility result for a relativistic Schrödinger equation on torus with time quasi-periodic unbounded perturbations of order 1/2, and finally conjugate the original equation to a time independent, 2\times 2 block diagonal one.

preprint2021arXiv

Spatial Curvature and Large Scale Lorentz Violation

The tension between the Hubble constant obtained from the local measurements and from cosmic microwave background (CMB) measurements motivated us to consider the cosmological model beyond $Λ$CDM one. We investigate the cosmology in the large scale Lorentz violation model with non-vanishing spatial curvature. The degeneracy among spatial curvature, cosmological constant and cosmological contortion distribution makes the model viable in describing the known observation date. We get some constraints on the spatial curvature by the comparison of the relation between measured distance modulus and red-shift with the predicted one, the evolution of matter density over time and the evolution of effective cosmological constant. The performance of large scale Lorentz violation model with non-vanishing spatial curvature under these constrains is discussed.

preprint2020arXiv

A Feshbach engine in the Thomas-Fermi regime

Bose-Einstein condensates can be used to produce work by tuning the strength of the interparticle interactions with the help of Feshbach resonances. In inhomogeneous potentials, these interaction ramps change the volume of the trapped gas allowing one to create a thermodynamic cycle known as the Feshbach engine. However, in order to obtain a large power output, the engine strokes must be performed on a short timescale, which is in contrast with the fact that the efficiency of the engine is reduced by irreversible work if the strokes are done in a non-adiabatic fashion. Here we investigate how such an engine can be run in the Thomas-Fermi regime and present a shortcut to adiabaticity that minimizes the irreversible work and allows for efficient engine operation.

preprint2020arXiv

A Resource Allocation and Coordinated Transmission Scheme for Large Cellular Networks

With the increasing number of user equipment (UE) and data demands, denser access points (APs) are being employed. Resource allocation problems have been extensively researched with interference treated as noise. It is well understood that the overall spectral efficiency can be significantly improved if multiple terminals coordinate their transmissions either coherently or non-coherently.The focus of this paper is to study how to select pairs of APs for coordination and allocate resources accordingly. An optimization problem is formulated to maximize the network utility function by optimizing AP paring, spectrum allocation, user association, and power management in a flexible manner. A scalable and efficient algorithm is proposed based on iterative scheme pursuit and fractional programming. Numerical results demonstrate substantial gains in the network utility due to coordinated transmission in a network of 128 APs and 384 UE.

preprint2020arXiv

An Attention Based Neural Network for Jet Tagging

Convolutional neural networks are basic structures using jet images as input for the jet tagging problems. However, what they have learned during the training process is always difficult to understand just through feature maps. Inspired by the attention mechanism popular in machine learning fields, we propose a novel attention-based neural network (ABNN) to get insight of this problem. The ABNN combines a jet image with average jet images from the signal and the background to generate attention maps which show clearly the relevant importance according to the different origination of jets. Compared with networks in the similar architecture, this network achieves better performance, which indicates the potential of attention mechanism to use in other works.

preprint2020arXiv

Charge detection in an array of CMOS quantum dots

The recent development of arrays of quantum dots in semiconductor nanostructures highlights the progress of quantum devices toward large scale. However, how to realize such arrays on a scalable platform such as silicon is still an open question. One of the main challenge resides in the detection of charges within the array. It is a prerequisite functionality to initialize a desired charge state and readout spins through spin-to-charge conversion mechanisms. In this paper, we use two methods based on either a single-lead charge detector, or a reprogrammable single electron transistor. Thanks to these methods, we study the charge dynamics and sensitivity by performing single shot detection of the charge. Finally, we can probe the charge stability at any node of a linear array and assess the Coulomb disorder in the structure. We find an electrochemical potential fluctuation induced by charge noise comparable to that reported in other silicon quantum dots.

preprint2020arXiv

Constructive and Destructive Interference of Kerker-type Scattering in an Ultra-thin Silicon Huygens Metasurface

High refractive index dielectric nanoparticles have provided a new platform for exotic light manipulation through the interference of multipole modes. The Kerker effect is one example of a Huygens source design. Rather than exploiting interference between the electric dipole and magnetic dipole, as in many conventional Huygens source designs, we explore Kerker-type suppressed backward scattering mediated by the dominant electric dipole, toroidal dipole and magnetic quadrupole. These modes are provided by a designed and fabricated CMOS compatible ultra-thin Silicon nanodisk metasurface with a suppressed magnetic dipole contribution, and verified through multipole decomposition. The non-trivial substrate effect is considered using a semi-analytical transfer matrix model. The model successfully predicts the observed reflection dip. By applying a general criterion for constructive and destructive interference, it is shown that while constructive interference occurs between the electric and toroidal dipole contributions, the experimentally observed suppressed backward Kerker-type scattering arises from the destructive interference between backward scattered contributions due to the total electric dipole and the magnetic quadrupole. Our study paves the way towards new types of Huygens sources or metasurface design, such as for peculiar transverse Kerker scattering.

preprint2020arXiv

Continuous-Time Analysis of the Bitcoin and Prism Backbone Protocols

Bitcoin is a peer-to-peer payment system proposed by Nakamoto in 2008. Based on the Nakamoto consensus, Bagaria, Kannan, Tse, Fanti, and Viswanath proposed the Prism protocol in 2018 and showed that it achieves near-optimal blockchain throughput while maintaining a similar level of security as bitcoin. Previous probabilistic security guarantees for the bitcoin and Prism backbone protocols were either established under a simplified discrete-time model or expressed in terms of exponential order results. This paper presents a streamlined and strengthened analysis under a more realistic continuous-time model. A fully rigorous model for blockchains is developed with no restrictions on adversarial miners except for an upper bound on their aggregate mining rate. The only assumption on the peer-to-peer network is that all block propagation delays are upper bounded by a constant. A new notion of "t-credible blockchains" is introduced, which, together with some carefully defined "typical" events concerning block production over time intervals, is crucial to establish probabilisitic security guarantees in continuous time. A blockchain growth theorem, a blockchain quality theorem, and a common prefix theorem are established with explicit probability bounds. Moreover, under a certain typical event which occurs with probability close to $1$, a valid transaction that is deep enough in one credible blockchain is shown to be permanent in the sense that it must be found in} in all future credible blockchains.

preprint2020arXiv

Double spin asymmetry in dihadron production in SIDIS off the longitudinally polarized nucleon target

In this paper we study the double longitudinal spin asymmetry of dihadron production in semi-inclusive deep inelastic scattering (SIDIS). We calculate a unknown twist-3 dihadron fragmentation function $\widetilde{D}^\sphericalangle$ within a spectator model which has been used successfully in describing the dihadron production in both the unpolarized and the single polarized processes. The collinear picture, in which the transverse momentum of the final state hadron pair is integrated out, has been considered. The $\cosϕ_R$ azimuthal asymmetry arises from the coupling $e_L H_1^\sphericalangle$ and the coupling $g_1 \widetilde{D}^\sphericalangle$ is studied. We estimate the $\cosϕ_R$ asymmetry at the kinematics of COMPASS and compare with the data. The prediction at the future Electron Ion Collider (EIC) has also been presented.

preprint2020arXiv

Effects of coherence on quantum speed limits and shortcuts to adiabaticity in many-particle systems

We discuss the effects of many-body coherence on the speed of evolution of ultracold atomic gases and the relation to quantum speed limits. Our approach is focused on two related systems, spinless fermions and the bosonic Tonks-Girardeau gas, which possess equivalent density dynamics but very different coherence properties. To illustrate the effect of the coherence on the dynamics we consider squeezing an anharmonic potential which confines the particles and find that the speed of the evolution exhibits subtle, but fundamental differences between the two systems. Furthermore, we explore the difference in the driven dynamics by implementing a shortcut to adiabaticity designed to reduce spurious excitations. We show that collisions between the strongly interacting bosons can lead to changes in the coherence which results in different evolution speeds and therefore different fidelities of the final states.

preprint2020arXiv

Efficient implementation of immersed boundary-lattice Boltzmann method for massive particle-laden flows Part I: Serial computing

Immersed boundary-lattice Boltzmann method (IB-LBM) has been widely used for simulation of particle-laden flows recently. However, it was limited to small-scale simulations with no more than O(103) particles. Here, we expand IB-LBM for massive particle-laden flows with more than O(104) particles by two sequential works. First is the Part I: serial computing on a single CPU core and following the Part II: parallel computing on many CPU cores. In this Part I paper, a highly efficient and localized implementation of IB-LBM is proposed for serial computing. We optimize in three main aspects: swap algorithm for incompressible LBM, local grid-to-point algorithm for IBM and improved grid search algorithm for particle pair short-range interaction. In addition, symmetry algorithm is proposed for the half-calculation of LB collision and external force term. The computational performance on a single CPU core is analyzed. Different scales of two dimensional (2D) and three-dimensional (3D) particles settling in closed cavities are used for testing. The solid volume fraction is varied from 0 to 0.40. Simulation results demonstrate that all calculation parts are dramatically decreased by the improved algorithm. For the particle-free flows, the Mega Lattice Site Update per Second (MLUPS) can be achieved up to 36 (2D) and 12 (3D) using the improved algorithm. For the particle-laden flows, MLUPS can be achieved no lower than 15 (2D) and 7 (3D) in the simulations of dense flows. At last, we discuss the potential of the new algorithms for the high-performance computation of the large-scale systems of particle-laden flows with MPI parallel technique.

preprint2020arXiv

Fairness Constraints in Semi-supervised Learning

Fairness in machine learning has received considerable attention. However, most studies on fair learning focus on either supervised learning or unsupervised learning. Very few consider semi-supervised settings. Yet, in reality, most machine learning tasks rely on large datasets that contain both labeled and unlabeled data. One of key issues with fair learning is the balance between fairness and accuracy. Previous studies arguing that increasing the size of the training set can have a better trade-off. We believe that increasing the training set with unlabeled data may achieve the similar result. Hence, we develop a framework for fair semi-supervised learning, which is formulated as an optimization problem. This includes classifier loss to optimize accuracy, label propagation loss to optimize unlabled data prediction, and fairness constraints over labeled and unlabeled data to optimize the fairness level. The framework is conducted in logistic regression and support vector machines under the fairness metrics of disparate impact and disparate mistreatment. We theoretically analyze the source of discrimination in semi-supervised learning via bias, variance and noise decomposition. Extensive experiments show that our method is able to achieve fair semi-supervised learning, and reach a better trade-off between accuracy and fairness than fair supervised learning.

preprint2020arXiv

GPM: A Generic Probabilistic Model to Recover Annotator's Behavior and Ground Truth Labeling

In the big data era, data labeling can be obtained through crowdsourcing. Nevertheless, the obtained labels are generally noisy, unreliable or even adversarial. In this paper, we propose a probabilistic graphical annotation model to infer the underlying ground truth and annotator's behavior. To accommodate both discrete and continuous application scenarios (e.g., classifying scenes vs. rating videos on a Likert scale), the underlying ground truth is considered following a distribution rather than a single value. In this way, the reliable but potentially divergent opinions from "good" annotators can be recovered. The proposed model is able to identify whether an annotator has worked diligently towards the task during the labeling procedure, which could be used for further selection of qualified annotators. Our model has been tested on both simulated data and real-world data, where it always shows superior performance than the other state-of-the-art models in terms of accuracy and robustness.

preprint2020arXiv

GRB 140423A: A Case of Stellar Wind to Interstellar Medium Transition in the Afterglow

We present very early ground-based optical follow-up observations of GRB~140423A, which was discovered by \emph{Swift}/BAT and by {\it Fermi}/GBM. Its broadband afterglow was monitored by {\it Swift}/XRT and ground-based optical telescopes from $T_0+$70.96~s to 4.8~d after the {\it Swift}/BAT trigger. This is one more case of prompt optical emission observation. The temporal and spectral joint fit of the multiwavelength light curves of GRB 140423A reveals that achromatic behavior is consistent with the external shock model including a transition from a stellar wind to the interstellar medium (ISM) and energy injection. In terms of the optical light curves, there is an onset bump in the early afterglow with a rising index $α_{\rm O,I} = -0.59 \pm 0.04$ (peaking at $t_{\rm peak}-T_0 \approx 206$~s). It then decays with a steep index $α_{\rm O,II} = 1.78 \pm 0.03$, and shows a steeper to flatter "transition" with $α_{\rm O,III} = 1.13 \pm 0.03$ at around $T_0 + 5000$~s. The observed X-ray afterglow reflects an achromatic behavior, as does the optical light curve. There is no obvious evolution of the spectral energy distribution between the X-ray and optical afterglow, with an average value of the photon index $Γ\approx 1.95$. This "transition" is consistent with an external shock model having the circumburst medium transition from a wind to the ISM, by introducing a long-lasting energy injection with a Lorentz factor stratification of the ejecta. The best parameters from Monte Carlo Markov Chain fitting are $E_{\rm K,iso} \approx 2.14\times10^{55}$ erg, $Γ_0 \approx 162$, $ε_e \approx 0.02$, $ε_B \approx 1.7\times10^{-6}$, $A_\ast \approx 1.0$, $R_t \approx 4.1\times10^{17}$ cm, $n \approx 11.0 \rm\ cm^{-3}$, $L_0 \approx 3.1\times10^{52} \rm\ erg\ s^{-1}$, $k \approx 1.98$, $s \approx 1.54$, and $θ_j > 0.3$ rad.

preprint2020arXiv

Ground-state correlation energy of beryllium dimer by the Bethe-Salpeter equation

Since the '30s the interatomic potential of the beryllium dimer Be$_2$ has been both an experimental and a theoretical challenge. Calculating the ground-state correlation energy of Be$_2$ along its dissociation path is a difficult problem for theory. We present ab initio many-body perturbation theory calculations of the Be$_2$ interatomic potential using the GW approximation and the Bethe-Salpeter equation (BSE). The ground-state correlation energy is calculated by the trace formula with checks against the adiabatic-connection fluctuation-dissipation theorem formula. We show that inclusion of GW corrections already improves the energy even at the level of the random-phase approximation. At the level of the BSE on top of the GW approximation, our calculation is in surprising agreement with the most accurate theories and with experiment. It even reproduces an experimentally observed flattening of the interatomic potential due to a delicate correlations balance from a competition between covalent and van der Waals bonding.

preprint2020arXiv

High-order numerical methods for the Riesz space fractional advection-dispersion equations

In this paper, we propose high-order numerical methods for the Riesz space fractional advection-dispersion equations (RSFADE) on a {f}inite domain. The RSFADE is obtained from the standard advection-dispersion equation by replacing the first-order and second-order space derivative with the Riesz fractional derivatives of order $α\in(0,1)$ and $β\in(1,2]$, respectively. Firstly, we utilize the weighted and shifted Grünwald difference operators to approximate the Riesz fractional derivative and present the {f}inite difference method for the RSFADE. Specifically, we discuss the Crank-Nicolson scheme and solve it in matrix form. Secondly, we prove that the scheme is unconditionally stable and convergent with the accuracy of $\mathcal {O}(τ^2+h^2)$. Thirdly, we use the Richardson extrapolation method (REM) to improve the convergence order which can be $\mathcal {O}(τ^4+h^4)$. Finally, some numerical examples are given to show the effectiveness of the numerical method, and the results are excellent with the theoretical analysis.

preprint2020arXiv

Hole-phonon interactions in quantum dots: Effects of phonon confinement and encapsulation materials on spin-orbit qubits

Spin-phonon interactions are one of the mechanisms limiting the lifetime of spin qubits made in semiconductor quantum dots. At variance with other mechanisms such as charge noise, phonons are intrinsic to the device and can hardly be mitigated. They set, therefore fundamental limits to the relaxation time of the qubits. Here we introduce a general framework for the calculation of the spin (and charge) transition rates induced by bulk (3D) and strongly confined 1D or 2D phonons. We discuss the particular case of hole spin-orbit qubits described by the 6 bands kp model. We next apply this theory to a hole qubit in a silicon-on-insulator device. We show that spin relaxation in this device is dominated by a band mixing term that couples the holes to transverse acoustic phonons through the valence band deformation potential d, and optimize the bias point and magnetic field orientation to maximize the number of Rabi oscillations Q that can be achieved within on relaxation time T1. Despite the strong spin-orbit coupling in the valence band, the phonon-limited Q can reach a few tens of thousands. We next explore the effects of phonon confinement in 1D and 2D structures, and the impact of the encapsulation materials on the relaxation rates. We show that the spin lifetimes can depend on the structure of the device over micrometer-long length scales and that they improve when the materials around the qubit get harder. Phonon engineering in semiconductor qubits may therefore become relevant once the extrinsic sources of relaxation have been reduced.

preprint2020arXiv

Hubble Space Telescope Search for Activity in High Perihelion Objects

Solar system objects with perihelia beyond the orbit of Jupiter ($q >$ 5 AU) are too cold for water ice to generate an appreciable coma via sublimation. Despite this, numerous high perihelion objects (HPOs) including many comets and recently escaped Kuiper belt objects (``Centaurs'') are observed to be active out at least to the orbit of Saturn ($q \sim$ 10 AU). Peak equilibrium temperatures at 10 AU ($\sim$125 K), while far too low to sublimate water ice, are sufficient to sublimate super-volatiles such as CO and CO$_2$ ice. Temperatures at 10 AU are also high enough to trigger the rapid crystallization of exposed amorphous ice, thus constituting another possible driver of distant activity. While supervolatile ices can sublimate strongly (as $r_H^{-2}$) to at least Kuiper belt (30 AU) distances, crystallization is an exponential function of temperature that cannot be sustained much beyond $\sim$10 AU. The heliocentric dependence of the activity thus suggests an observational test. If activity in high perihelion objects is triggered by crystallization, then no examples of activity should be found with perihelia $q >>$ 10 AU. If, on the other hand, activity is due to free sublimation of exposed supervolatile ices, or another cause, then distant activity might be detected. We obtained sensitive, high resolution Hubble Space Telescope observations of HPOs to search for activity beyond the crystallization zone. No examples of activity were detected in 53 objects with $q >$ 15 AU, consistent with the crystallization trigger hypothesis. However, sensitivity limits are such that we cannot reject the alternative hypothesis that mass loss is driven by the sublimation of supervolatile ices. We also searched for binary companions in our sample, finding none and setting an empirical 3$σ$ limit to the binary fraction of $<8$\%.

preprint2020arXiv

Large Batch Optimization for Deep Learning: Training BERT in 76 minutes

Training large deep neural networks on massive datasets is computationally very challenging. There has been recent surge in interest in using large batch stochastic optimization methods to tackle this issue. The most prominent algorithm in this line of research is LARS, which by employing layerwise adaptive learning rates trains ResNet on ImageNet in a few minutes. However, LARS performs poorly for attention models like BERT, indicating that its performance gains are not consistent across tasks. In this paper, we first study a principled layerwise adaptation strategy to accelerate training of deep neural networks using large mini-batches. Using this strategy, we develop a new layerwise adaptive large batch optimization technique called LAMB; we then provide convergence analysis of LAMB as well as LARS, showing convergence to a stationary point in general nonconvex settings. Our empirical results demonstrate the superior performance of LAMB across various tasks such as BERT and ResNet-50 training with very little hyperparameter tuning. In particular, for BERT training, our optimizer enables use of very large batch sizes of 32868 without any degradation of performance. By increasing the batch size to the memory limit of a TPUv3 Pod, BERT training time can be reduced from 3 days to just 76 minutes (Table 1). The LAMB implementation is available at https://github.com/tensorflow/addons/blob/master/tensorflow_addons/optimizers/lamb.py

preprint2020arXiv

LSOTB-TIR:A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark

In this paper, we present a Large-Scale and high-diversity general Thermal InfraRed (TIR) Object Tracking Benchmark, called LSOTBTIR, which consists of an evaluation dataset and a training dataset with a total of 1,400 TIR sequences and more than 600K frames. We annotate the bounding box of objects in every frame of all sequences and generate over 730K bounding boxes in total. To the best of our knowledge, LSOTB-TIR is the largest and most diverse TIR object tracking benchmark to date. To evaluate a tracker on different attributes, we define 4 scenario attributes and 12 challenge attributes in the evaluation dataset. By releasing LSOTB-TIR, we encourage the community to develop deep learning based TIR trackers and evaluate them fairly and comprehensively. We evaluate and analyze more than 30 trackers on LSOTB-TIR to provide a series of baselines, and the results show that deep trackers achieve promising performance. Furthermore, we re-train several representative deep trackers on LSOTB-TIR, and their results demonstrate that the proposed training dataset significantly improves the performance of deep TIR trackers. Codes and dataset are available at https://github.com/QiaoLiuHit/LSOTB-TIR.

preprint2020arXiv

Molecular dynamics simulation for cross-linking processes and material properties of epoxy resins with the first principle calculation combined with global reaction route mapping algorithms

Herein, epoxy resin is cured by coupling quantum chemical (QC) calculations with molecular dynamics (MD) simulations that enable parameter-free prediction of material characteristics. A polymer network is formed by the reaction between base resin and curing agent. The reaction uses activation energy and heat of formation data obtained by first-principle calculations coupled with global reaction route mapping (GRRM) algorithms. Density, glass transition temperature, Young's modulus, and curing conversion is used to validate the procedure. Experimental and simulation results indicate that base resin with multi-functional reaction groups increases glass-transition temperature and Young's modulus because of cross-linked formations at the molecular scale.

preprint2020arXiv

Pose-Assisted Multi-Camera Collaboration for Active Object Tracking

Active Object Tracking (AOT) is crucial to many visionbased applications, e.g., mobile robot, intelligent surveillance. However, there are a number of challenges when deploying active tracking in complex scenarios, e.g., target is frequently occluded by obstacles. In this paper, we extend the single-camera AOT to a multi-camera setting, where cameras tracking a target in a collaborative fashion. To achieve effective collaboration among cameras, we propose a novel Pose-Assisted Multi-Camera Collaboration System, which enables a camera to cooperate with the others by sharing camera poses for active object tracking. In the system, each camera is equipped with two controllers and a switcher: The vision-based controller tracks targets based on observed images. The pose-based controller moves the camera in accordance to the poses of the other cameras. At each step, the switcher decides which action to take from the two controllers according to the visibility of the target. The experimental results demonstrate that our system outperforms all the baselines and is capable of generalizing to unseen environments. The code and demo videos are available on our website https://sites.google.com/view/pose-assistedcollaboration.

preprint2020arXiv

Secure Metric Learning via Differential Pairwise Privacy

Distance Metric Learning (DML) has drawn much attention over the last two decades. A number of previous works have shown that it performs well in measuring the similarities of individuals given a set of correctly labeled pairwise data by domain experts. These important and precisely-labeled pairwise data are often highly sensitive in real world (e.g., patients similarity). This paper studies, for the first time, how pairwise information can be leaked to attackers during distance metric learning, and develops differential pairwise privacy (DPP), generalizing the definition of standard differential privacy, for secure metric learning. Unlike traditional differential privacy which only applies to independent samples, thus cannot be used for pairwise data, DPP successfully deals with this problem by reformulating the worst case. Specifically, given the pairwise data, we reveal all the involved correlations among pairs in the constructed undirected graph. DPP is then formalized that defines what kind of DML algorithm is private to preserve pairwise data. After that, a case study employing the contrastive loss is exhibited to clarify the details of implementing a DPP-DML algorithm. Particularly, the sensitivity reduction technique is proposed to enhance the utility of the output distance metric. Experiments both on a toy dataset and benchmarks demonstrate that the proposed scheme achieves pairwise data privacy without compromising the output performance much (Accuracy declines less than 0.01 throughout all benchmark datasets when the privacy budget is set at 4).

preprint2020arXiv

Structured3D: A Large Photo-realistic Dataset for Structured 3D Modeling

Recently, there has been growing interest in developing learning-based methods to detect and utilize salient semi-global or global structures, such as junctions, lines, planes, cuboids, smooth surfaces, and all types of symmetries, for 3D scene modeling and understanding. However, the ground truth annotations are often obtained via human labor, which is particularly challenging and inefficient for such tasks due to the large number of 3D structure instances (e.g., line segments) and other factors such as viewpoints and occlusions. In this paper, we present a new synthetic dataset, Structured3D, with the aim of providing large-scale photo-realistic images with rich 3D structure annotations for a wide spectrum of structured 3D modeling tasks. We take advantage of the availability of professional interior designs and automatically extract 3D structures from them. We generate high-quality images with an industry-leading rendering engine. We use our synthetic dataset in combination with real images to train deep networks for room layout estimation and demonstrate improved performance on benchmark datasets.

preprint2020arXiv

Superconducting proximity effect in a transparent van der Waals superconductor-metal junction

We report on Andreev reflections at clean NbSe2-bilayer graphene junctions. The high transparency of the junction, which manifests as a large conductance enhancement of up to 1.8, enables us to see clear evidence of a proximity-induced superconducting gap in bilayer graphene and two Andreev reflections through a vertical NbSe2-graphene and a lateral graphene-graphene junction respectively. Quantum transport simulations capture the complexity of the experimental data and illuminate the impact of various microscopic parameters on the transmission of the junction. Our work establishes the practice and understanding of an all-van-der-Waals, high-performance superconducting junction. The realization of a highly transparent proximized graphene-graphene junction opens up possibilities to engineer emergent quantum phenomena.

preprint2020arXiv

Travelling wave solutions of the density-suppressed motility model

In this paper, we study the traveling wave solutions to the density-suppressed motility model describing the ``self-trapping'' mechanism that induces spatio-temporal pattern formations observed in the experiment. We establish the existence of traveling wavefronts with a minimal wave speed and discuss the selection of wave profiles supplemented with numerical simulations illustrating the wave patterns which are well consistent with experimental observations.

preprint2020arXiv

UFTR: A Unified Framework for Ticket Routing

Corporations today face increasing demands for the timely and effective delivery of customer service. This creates the need for a robust and accurate automated solution to what is formally known as the ticket routing problem. This task is to match each unresolved service incident, or "ticket", to the right group of service experts. Existing studies divide the task into two independent subproblems - initial group assignment and inter-group transfer. However, our study addresses both subproblems jointly using an end-to-end modeling approach. We first performed a preliminary analysis of half a million archived tickets to uncover relevant features. Then, we devised the UFTR, a Unified Framework for Ticket Routing using four types of features (derived from tickets, groups, and their interactions). In our experiments, we implemented two ranking models with the UFTR. Our models outperform baselines on three routing metrics. Furthermore, a post-hoc analysis reveals that this superior performance can largely be attributed to the features that capture the associations between ticket assignment and group assignment. In short, our results demonstrate that the UFTR is a superior solution to the ticket routing problem because it takes into account previously unexploited interrelationships between the group assignment and group transfer problems.

preprint2020arXiv

Unusual Intralayer Ferromagnetism Between S = 5/2 ions in MnBi$_2$Te$_4$: Role of Empty Bi $p$ States

The layered magnetic topological insulator MnBi$_2$Te$_4$ is a promising platform to realize the quantum anomalous Hall effect because its layers possess intrinsic ferromagnetism. However, it is not well understood why the high-spin $d^5$ magnetic ions Mn$^{2+}$ forming the Mn-Te-Mn spin exchange paths prefer ferromagnetic (FM) coupling, contrary to the prediction of the Goodenough-Kanamori rule that a TM-L-TM spin exchange, where TM and L are a transition-metal magnetic cation and a main group ligand, respectively, is antiferromagnetic (AFM) even when the bond angle of the exchange path is 90$^{\circ}$. Using density functional theory (DFT) calculations, we show that the presence of Bi$^{3+}$ ions is essential for the FM coupling in MnBi$_2$Te$_4$. Then, using a tight-binding model Hamiltonian, we find that high-spin $d^5$ ions (S = 5/2) in TM-L-TM spin exchange paths prefer FM coupling if the empty p-orbitals of a nonmagnetic cation M (e.g., Bi$^{3+}$ ion) hybridize strongly with those of the bridging ligand L, but AFM coupling otherwise.

preprint2020arXiv

What Changed Your Mind: The Roles of Dynamic Topics and Discourse in Argumentation Process

In our world with full of uncertainty, debates and argumentation contribute to the progress of science and society. Despite of the increasing attention to characterize human arguments, most progress made so far focus on the debate outcome, largely ignoring the dynamic patterns in argumentation processes. This paper presents a study that automatically analyzes the key factors in argument persuasiveness, beyond simply predicting who will persuade whom. Specifically, we propose a novel neural model that is able to dynamically track the changes of latent topics and discourse in argumentative conversations, allowing the investigation of their roles in influencing the outcomes of persuasion. Extensive experiments have been conducted on argumentative conversations on both social media and supreme court. The results show that our model outperforms state-of-the-art models in identifying persuasive arguments via explicitly exploring dynamic factors of topic and discourse. We further analyze the effects of topics and discourse on persuasiveness, and find that they are both useful - topics provide concrete evidence while superior discourse styles may bias participants, especially in social media arguments. In addition, we draw some findings from our empirical results, which will help people better engage in future persuasive conversations.

preprint2019arXiv

An improved bound for strong unitary uncertainty relations with refined sequence

We derive the lower bound of uncertainty relations of two unitary operators for a class of states based on the geometric-arithmetic inequality and Cauchy-Schwarz inequality. Furthermore, we propose a set of uncertainty relations for three unitary operators. Compared to the known bound introduced in Phys.Rev.A.100,022116(2019), the unitary uncertainty relations bound with our method is tighter, to a certain extent. Meanwhile, some examples are given in the paper to illustrate our conclusions.

preprint2019arXiv

Coupled density-spin Bose-Einstein condensates dynamics and collapse in systems with quintic nonlinearity

We investigate the effects of spin-orbit coupling and Zeeman splitting on the coupled density-spin dynamics and collapse of the Bose-Einstein condensate driven by the quintic self-attraction in the same- and cross-spin channels. The characteristic feature of the collapse is the decrease in the width as given by the participation ratio of the density rather than by the expectation values of the coordinate. Qualitative arguments and numerical simulations reveal the existence of a critical spin-orbit coupling strength which either prohibits or leads to the collapse, and its dependence on other parameters, such as the condensates norm, spin-dependent nonlinear coupling, and the Zeeman splitting. The entire nonlinear dynamics critically depend on the initial spin sate.

preprint2019arXiv

Deep Image-to-Video Adaptation and Fusion Networks for Action Recognition

Existing deep learning methods for action recognition in videos require a large number of labeled videos for training, which is labor-intensive and time-consuming. For the same action, the knowledge learned from different media types, e.g., videos and images, may be related and complementary. However, due to the domain shifts and heterogeneous feature representations between videos and images, the performance of classifiers trained on images may be dramatically degraded when directly deployed to videos. In this paper, we propose a novel method, named Deep Image-to-Video Adaptation and Fusion Networks (DIVAFN), to enhance action recognition in videos by transferring knowledge from images using video keyframes as a bridge. The DIVAFN is a unified deep learning model, which integrates domain-invariant representations learning and cross-modal feature fusion into a unified optimization framework. Specifically, we design an efficient cross-modal similarities metric to reduce the modality shift among images, keyframes and videos. Then, we adopt an autoencoder architecture, whose hidden layer is constrained to be the semantic representations of the action class names. In this way, when the autoencoder is adopted to project the learned features from different domains to the same space, more compact, informative and discriminative representations can be obtained. Finally, the concatenation of the learned semantic feature representations from these three autoencoders are used to train the classifier for action recognition in videos. Comprehensive experiments on four real-world datasets show that our method outperforms some state-of-the-art domain adaptation and action recognition methods.

preprint2019arXiv

Gaussian Process Regression and Conditional Polynomial Chaos for Parameter Estimation

We present a new approach for constructing a data-driven surrogate model and using it for Bayesian parameter estimation in partial differential equation (PDE) models. We first use parameter observations and Gaussian Process regression to condition the Karhunen-Loéve (KL) expansion of the unknown space-dependent parameters and then build the conditional generalized Polynomial Chaos (gPC) surrogate model of the PDE states. Next, we estimate the unknown parameters by computing coefficients in the KL expansion minimizing the square difference between the gPC predictions and measurements of the states using the Markov Chain Monte Carlo method. Our approach addresses two major challenges in the Bayesian parameter estimation. First, it reduces dimensionality of the parameter space and replaces expensive direct solutions of PDEs with the conditional gPC surrogates. Second, the estimated parameter field exactly matches the parameter measurements. In addition, we show that the conditional gPC surrogate can be used to estimate the states variance, which, in turn, can be used to guide data acquisition. We demonstrate that our approach improves its accuracy with application to one- and two-dimensional Darcy equation with (unknown) space-dependent hydraulic conductivity. We also discuss the effect of hydraulic conductivity and head locations on the accuracy of the hydraulic conductivity estimations.

preprint2019arXiv

Improving solution accuracy and convergence for stochastic physics parameterizations with colored noise

Stochastic parameterizations are used in numerical weather prediction and climate modeling to help capture the uncertainty in the simulations and improve their statistical properties. Convergence issues can arise when time integration methods originally developed for deterministic differential equations are applied naively to stochastic problems. (Hodyss et al 2013, 2014) demonstrated that a correction term to various deterministic numerical schemes, known in stochastic analysis as the Itô correction, can help improve solution accuracy and ensure convergence to the physically relevant solution without substantial computational overhead. The usual formulation of the Itô correction is valid only when the stochasticity is represented by {\it white} noise. In this study, a generalized formulation of the Itô correction is derived for noises of any color. The formulation is applied to a test problem described by an advection-diffusion equation forced with a spectrum of fast processes. We present numerical results for cases with both constant and spatially varying advection velocities to show that, for the same time step sizes, the introduction of the generalized Itô correction helps to substantially reduce time integration error and significantly improve the convergence rate of the numerical solutions when the forcing term in the governing equation is rough (fast varying); alternatively, for the same target accuracy, the generalized Itô correction allows for the use of significantly longer time steps and hence helps to reduce the computational cost of the numerical simulation.

preprint2019arXiv

Model reduction for a power grid model

We apply model reduction techniques to the DeMarco power grid model. The DeMarco model, when augmented by an appropriate line failure mechanism, can be used to study cascade failures. Here we examine the DeMarco model without the line failure mechanism and we investigate how to construct reduced order models for subsets of the state variables. We show that due to the oscillating nature of the solutions and the absence of timescale separation between resolved and unresolved variables, the construction of accurate reduced models becomes highly non-trivial since one has to account for long memory effects. In addition, we show that a reduced model which includes even a short memory is drastically better than a memoryless model.

preprint2019arXiv

Robust Cubature Kalman Filter for Dynamic State Estimation of Synchronous Machines under Unknown Measurement Noise Statistics

Kalman-type filtering techniques including cubature Kalman filter (CKF) does not work well in non-Gaussian environments, especially in the presence of outliers. To solve this problem, Huber's M-estimation based robust CKF (RCKF) is proposed for synchronous machines by combining the Huber's M-estimation theory with the classical CKF, which is capable of coping with the deterioration in performance and discretization of tracking curves when measurement noise statistics deviatefrom the prior noise statistics. The proposed RCKF algorithm has good adaptability to unknown measurement noise statistics characteristics including non-Gaussian measurement noise and outliers. The simulation results on the WSCC 3-machine 9-bus system and New England 16-machine 68-bus system verify the effectiveness of the proposed method and its advantage over the classical CKF.

preprint2019arXiv

Tracing Kinematic and Chemical Properties of Sagittarius Stream by K-Giants, M-Giants, and BHB stars

We characterize the kinematic and chemical properties of $\sim$3,000 Sagittarius (Sgr) stream stars, including K-giants, M-giants, and BHBs, select from SEGUE-2, LAMOST, and SDSS separately in Integrals-of-Motion space. The orbit of Sgr stream is quite clear from the velocity vector in $X$-$Z$ plane. Stars traced by K-giants and M-giants present the apogalacticon of trailing steam is $\sim$ 100 kpc. The metallicity distributions of Sgr K-, M-giants, and BHBs present that the M-giants are on average the most metal-rich population, followed by K-giants and BHBs. All of the K-, M-giants, and BHBs indicate that the trailing arm is on average more metal-rich than leading arm, and the K-giants show that the Sgr debris is the most metal-poor part. The $α$-abundance of Sgr stars exhibits a similar trend with the Galactic halo stars at lower metallicity ([Fe/H] $<\sim$ $-$1.0 dex), and then evolve down to lower [$α$/Fe] than disk stars at higher metallicity, which is close to the evolution pattern of $α$-element of Milky Way dwarf galaxies. We find $V_Y$ and metallicity of K-giants have gradients along the direction of line-of-sight from the Galactic center in $X$-$Z$ plane, and the K-giants show that $V_Y$ increases with metallicity at [Fe/H] $>\sim-$1.5 dex. After dividing the Sgr stream into bright and faint stream according to their locations in equatorial coordinate, the K-giants and BHBs show that the bright and faint stream present different $V_Y$ and metallicities, the bright stream is on average higher in $V_Y$ and metallicity than the faint stream.

preprint2017arXiv

On the Cauchy Problem of 3D Nonhomogeneous Navier-Stokes Equations with Density-Dependent Viscosity and Vacuum

We consider the global existence and large-time asymptotic behavior of strong solutions to the Cauchy problem of the three-dimensional nonhomogeneous incompressible Navier-Stokes equations with density-dependent viscosity and vacuum. We establish some key a priori exponential decay-in-time rates of the strong solutions. Then after using these estimates, we also obtain the global existence of strong solutions in the whole three-dimensional space, provided that the initial velocity is suitably small in the $\dot H^β$-norm for some $β\in(1/2,1].$ Note that this result is proved without any smallness conditions on the initial density. Moreover, the density can contain vacuum states and even have compact support initially.

preprint2016arXiv

Algebraic stability of non-homogeneous regime-switching diffusion processes

Some sufficient conditions on the algebraic stability of non-homogeneous regime-switching diffusion processes are established. In this work we focus on determining the decay rate of a stochastic system which switches randomly between different states, and owns different decay rates at various states. In particular, we show that if a finite-state regime-switching diffusion process is $p$-th moment exponentially stable in some states and is $p$-th moment algebraically stable in other states, which are characterized by a common Lyapunov function, then this process is ultimately exponentially stable regardless of the jumping rate of the random switching between these states. Moreover, these results can be applied to the stabilization of SDE by feedback control to reduce the observation times.

preprint2016arXiv

Developing a Magnetism Conceptual Survey and Assessing Gender Differences in Student Understanding of Magnetism

We discuss the development of a research-based conceptual multiple-choice survey related to magnetism. We also discuss the use of the survey to investigate gender differences in students' difficulties with concepts related to magnetism. We find that while there was no gender difference on the pre-test, female students performed significantly worse than male students when the survey was given as a post-test in traditionally taught calculus-based introductory physics courses (similar results in both the regular and honors versions of the course). In the algebra-based courses, the performance of the female students and the male students has no statistical difference in the pre-test or the post-test.

preprint2016arXiv

Early Stopping for Interleaver Recovering of Turbo Codes

Parameter recovering of channel codes is important in applications such as cognitive radio. The main task for that of a turbo code is to recover the interleaver. The existing optimal algorithm recovers interleaver parameters incrementally one by one. This algorithm continues till the end even if it has failed in the halfway. And there would be lots of wasted computation, as well as incorrectly recovered parameters that will badly deteriorate turbo decoding performance. To address such drawbacks, this paper proposes an early stopping method for the algorithm. Thresholds needed for the method are set through theoretical analysis. Simulations show that the proposed method is able to stop the algorithm in time after it has failed, while no significant degradation in the correct recovering probability is observed.

preprint2016arXiv

Fragmentation Kinematics in Comet 332P/Ikeya-Murakami

We present initial time-resolved observations of the split comet 332P/Ikeya-Murakami taken using the Hubble Space Telescope. Our images reveal a dust-bathed cluster of fragments receding from their parent nucleus at projected speeds in the range 0.06 to 3.5 m s$^{-1}$ from which we estimate ejection times from October to December 2015. The number of fragments with effective radii $\gtrsim$20 m follows a differential power law with index $γ$ = -3.6$\pm$0.6, while smaller fragments are less abundant than expected from an extrapolation of this power-law. We argue that, in addition to losses due to observational selection, torques from anisotropic outgassing are capable of destroying the small fragments by driving them quickly to rotational instability. Specifically, the spin-up times of fragments $\lesssim$20 m in radius are shorter than the time elapsed since ejection from the parent nucleus. The effective radius of the parent nucleus is $r_e \le$ 275 m (geometric albedo 0.04 assumed). This is about seven times smaller than previous estimates and results in a nucleus mass at least 300 times smaller than previously thought. The mass in solid pieces, $2\times10^9$ kg, is about 4% of the mass of the parent nucleus. As a result of its small size, the parent nucleus also has a short spin-up time. Brightness variations in time-resolved nucleus photometry are consistent with rotational instability playing a role in the release of fragments.

preprint2016arXiv

Hubble Space Telescope Observations of Active Asteroid 324P/La Sagra

Hubble Space Telescope observations of active asteroid 324P/La Sagra near perihelion show continued mass loss consistent with the sublimation of near-surface ice. Isophotes of the coma measured from a vantage point below the orbital plane are best matched by steady emission of particles having a nominal size $a \sim$ 100 $μ$m. The inferred rate of mass loss, $dM_d/dt \sim$0.2 kg s$^{-1}$, can be supplied by sublimation of water ice in thermal equilibrium with sunlight from an area as small as 930 m$^2$, corresponding to about 0.2\% of the nucleus surface. Observations taken from a vantage point only 0.6\degr~from the orbital plane of 324P set a limit to the velocity of ejection of dust in the direction perpendicular to the plane, $V_{\perp} <$ 1 m s$^{-1}$. Short-term photometric variations of the near-nucleus region, if related to rotation of the underlying nucleus, rule out periods $\le$ 3.8 hr and suggest that rotation probably does not play a central role in driving the observed mass loss. We estimate that, in the previous orbit, 324P lost about 4$\times$10$^7$ kg in dust particles, corresponding to 6$\times$10$^{-5}$ of the mass of a 550 m spherical nucleus of assumed density $ρ$ = 1000 kg m$^{-3}$. If continued, mass loss at this rate would limit the lifetime of 324P to $\sim$1.6$\times$10$^4$ orbits (about 10$^5$ yr). To survive for the 100 Myr to 400 Myr timescales corresponding, respectively, to dynamical and collisional stability requires a duty cycle $2\times 10^{-4} \le f_d \le 8\times 10^{-4}$. Unless its time in orbit is over-estimated by many orders of magnitude, 324P is revealed as a briefly-active member of a vast population of otherwise dormant ice-containing asteroids.

preprint2016arXiv

New tidal debris nearby the Sagittarius leading tail from the LAMOST DR2 M giant stars

We report two new tidal debris nearby the Sagittarius (Sgr) tidal stream in the north Galactic cap identified from the M giant stars in LAMOST DR2 data. The M giant stars with sky area of $210^\circ<$Λ$<290^\circ$, distance of 10--20kpc, and [Fe/H]$<-0.75$ show clear bimodality in velocity distribution. We denote the two peaks as Vel-3+83 for the one within mean velocity of -3kms$^{-1}$ with respect to that of the well observed Sgr leading tail at the same $Λ$ and Vel+162+26 for the other one with mean velocity of 162kms$^{-1}$ with respect to the Sgr leading tail. Although the projected $Λ$--$V_{gar}$ relation of Vel-3+83 is very similar to the Sgr leading tail, the opposite trend in $Λ$--distance relation against the Sgr leading tail suggests Vel-3+83 has a different 3D direction of motion with any branch of the simulated Sgr tidal stream from Law & Majewski. Therefore, we propose it to be a new tidal debris not related to the Sgr stream. Similarly, the another substructure Vel+162+26, which is the same one as the NGC group discovered by Chou et al., also moves toward a different direction with the Sgr stream, implying that it may have different origin with the Sgr tidal stream.

preprint2016arXiv

Resurrection of (3200) Phaethon in 2016

We present a study of the active asteroid (3200) Phaethon in the 2016 apparition using the STEREO spacecraft and compare the results with data from the previous two perihelia in 2009 and 2012. Once again, Phaethon brightened by $\sim$2 mag soon after its perihelion passage, contradicting expectations from the phase function of a macroscopic monolithic body. Subsequently, a short antisolar tail of $\sim$0°.1 in length was formed within $\sim$1 day and quickly disappeared. No trail was seen. Our syndyne-synchrone analysis indicates that the tail was comprised of submicron to micron particles and can be approximated by a synchrone coinciding with the outburst. We estimate that the outburst has released a mass of $\sim$10$^{4}$--10$^{5}$ kg, comparable to the two mass ejections in 2009 and 2012, and that the average mass-loss rate is $\sim$0.1--1 kg s$^{-1}$. The forward-scattering effect hinted at low level activity of Phaethon prior to the outburst, which increased the effective cross section by merely $\lesssim$1 km$^2$. Without the forward-scattering enhancement, detecting such activity at side-scattering phase angles is very difficult. The forward-scattering effect also reinforces that the ejected dust grains rather than gas emissions were responsible for the activity of Phaethon. Despite Phaethon's reactivation, it is highly unlikely that the Geminid meteoroid stream can be sustained by similar perihelion mass-loss events.

preprint2016arXiv

Selecting M-giants with infra-red photometry: Distances, metallicities and the Sagittarius stream

Using a spectroscopically confirmed sample of M-giants, M-dwarfs and quasars from the LAMOST survey, we assess how well WISE $\&$ 2MASS color-cuts can be used to select M-giant stars. The WISE bands are very efficient at separating M-giants from M-dwarfs and we present a simple classification that can produce a clean and relatively complete sample of M-giants. We derive a new photometric relation to estimate the metallicity for M-giants, calibrated using data from the APOGEE survey. We find a strong correlation between the $(W1-W2)$ color and $\rm [M/H]$, where almost all of the scatter is due to photometric uncertainties. We show that previous photometric distance relations, which are mostly based on stellar models, may be biased and devise a new empirical distance relation, investigating trends with metallicity and star formation history. Given these relations, we investigate the properties of M-giants in the Sagittarius stream. The offset in the orbital plane between the leading and trailing tails is reproduced and, by identifying distant M-giants in the direction of the Galactic anti-center, we confirm that the previously detected debris in the outer halo is the apocenter of the trailing tail. We also find tentative evidence supporting an existing overdensity near the leading tail in the Northern Galactic hemisphere, possibly an extension to the trailing tail (so-called Branch C). We have measured the metallicity distribution along the stream, finding a clear metallicity offset between the leading and trailing tails, in agreement with models for the stream formation. We include an online table of M-giants to facilitate further studies.

preprint2016arXiv

Students' Difficulties with Equations involving Circuit Elements

We discuss an investigation exploring students' difficulties with equations involving resistance, capacitance and inductance. We find that introductory physics students have great difficulty understanding, e.g., how the resistance of an ohmic resistor can be written in terms of the potential difference across it and the current through it, but it does not change when the potential difference across the resistor is varied. Similar confusions arose in problems relating to capacitors and inductors. We discuss these difficulties with equations in the context of introductory physics students' performance on questions about circuit elements both in the free-response and multiple-choice formats.

preprint2015arXiv

A unified framework for mesh refinement in random and physical space

In recent work we have shown how an accurate reduced model can be utilized to perform mesh refinement in random space. That work relied on the explicit knowledge of an accurate reduced model which is used to monitor the transfer of activity from the large to the small scales of the solution. Since this is not always available, we present in the current work a framework which shares the merits and basic idea of the previous approach but does not require an explicit knowledge of a reduced model. Moreover, the current framework can be applied for refinement in both random and physical space. In this manuscript we focus on the application to random space mesh refinement. We study examples of increasing difficulty (from ordinary to partial differential equations) which demonstrate the efficiency and versatility of our approach. We also provide some results from the application of the new framework to physical space mesh refinement.

preprint2015arXiv

Analysis of Performance of Linear Analog Codes

In this paper we carefully study the MSE performance of the linear analog codes. We have derived a lower bound of the MSE performance under Likelihood(ML) and Linear Minimal Mean Square Error(LMMSE) decoding criteria respectively. It is proved in this essay that a kind of linear analog codes called \emph {unitary codes} can simultaneously achieve both of these two bounds. At the same time, we compare the obtained linear analog codes' MSE bounds with the performance of some existing nonlinear codes. The results showed that linear analog codes are actually not very satisfying and convinced us that more concerns should be cast onto the nonlinear class in order to find powerful analog codes.

preprint2015arXiv

Bioinspired interfacial materials with enhanced drop mobility: From fundamentals to multifunctional applications

The development of bio-inspired interfacial materials with enhanced drop mobility that mimic the innate functionalities of nature will have significant impact on the energy, environment and global healthcare. In spite of extensive progress, the state of the art of interfacial materials have not reached the level of maturity sufficient for industrial applications in terms of scalability, stability and reliability, which are complicated by their operating environments and lack of facile approaches to exquisitely control the local structural texture and chemical composition at multiple length scales. In this review, we focus on the recent advances in the fundamental understanding as well as practical applications of bio-inspired interfacial materials, with an emphasis on the drop impact induced bouncing and coalescence induced jumping behaviors. We also suggest our own perspectives on how to catalyze new discoveries and to foster technological adoption to move this exciting area forward.

preprint2015arXiv

Competitive co-adsorption of CO2 with H2O, NH3, SO2, NO, NO2, N2, O2, and CH4 in M-MOF-74 (M= Mg, Co, Ni): the role of hydrogen bonding

The importance of co-adsorption for applications of porous materials in gas separation has motivated fundamental studies, which have initially focused on the comparison of the binding energies of different gas molecules in the pores (i.e. energetics) and their overall transport. By examining the competitive co-adsorption of several small molecules in M-MOF-74 (M= Mg, Co, Ni) with in-situ infrared spectroscopy and ab initio simulations, we find that the binding energy at the most favorable (metal) site is not a sufficient indicator for prediction of molecular adsorption and stability in MOFs. Instead, the occupation of the open metal sites is governed by kinetics, whereby the interaction of the guest molecules with the MOF organic linkers controls the reaction barrier for molecular exchange. Specifically, the displacement of CO2 adsorbed at the metal center by other molecules such as H2O, NH3, SO2, NO, NO2, N2, O2, and CH4 is mainly observed for H2O and NH3, even though SO2, NO, and NO2, have higher binding energies (~70-90 kJ/mol) to metal sites than that of CO2 (38 to 48 kJ/mol) and slightly higher than water (~60-80 kJ/mol). DFT simulations evaluate the barriers for H2O->CO2 and SO2->CO2 exchange to be - 13 and 20 kJ/mol, respectively, explaining the slow exchange of CO2 by SO2, compared to water. Furthermore, the calculations reveal that the kinetic barrier for this exchange is determined by the specifics of the interaction of the second guest molecule (e.g., H2O or SO2) with the MOF ligands.

preprint2015arXiv

Disappearance of Comet C/2010 X1 (Elenin): Gone with a Whimper, not a Bang

We examine the rise and sudden demise of comet C/2010 X1 (Elenin) on its approach to perihelion. Discovered inbound at 4.2 AU, this long-period comet was predicted to become very bright when near perihelion, at 0.48 AU on 2011 September 10. Observations starting 2011 February (heliocentric distance $\sim$3.5 AU) indeed show the comet to brighten by about 11 magnitudes, with most of the increase occurring inside 1 AU from the Sun. The peak brightness reached $m_R$ = 6 on UT 2011 August 12.95$\pm$0.50, when at $\sim$0.83 AU from the Sun. We find that most of the surge in brightness in mid-August resulted from dust particle forward-scattering, not from a sudden increase in the activity. A much smaller ($\sim$3 magnitudes) brightening reached a maximum on UT 2011 August 30$\pm$1 (at 0.56 AU), and reflects the true break-up of the nucleus. This second peak was matched by a change in the morphology from centrally condensed to diffuse. The estimated cross-section of the nucleus when at 1 AU inbound was $\sim$1 km$^2$, corresponding to an equal-area circle of radius 0.6 km. No surviving fragments were found to a limiting red magnitude $r'$ = 24.4, corresponding to radii $\lesssim$40 m (red geometric albedo = 0.04 assumed). Our observations are consistent with disintegration of the nucleus into a power law size distribution of fragments with index $q$ = 3.3$\pm$0.2 combined with the action of radiation pressure. We speculate about physical processes that might cause nucleus disruption in a comet when still 0.7 AU from the Sun. Tidal stresses and devolatilization of the nucleus by sublimation are both negligible at this distance. However, the torque caused by mass loss, even at the very low rates measured in comet Elenin, is potentially large enough to be responsible by driving the nucleus to rotational instability.

preprint2015arXiv

Efficient failure probability calculation through mesh refinement

We present a novel way of accelerating hybrid surrogate methods for the calculation of failure probabilities. The main idea is to use mesh refinement in order to obtain improved local surrogates of low computation cost to simulate on. These improved surrogates can reduce significantly the required number of evaluations of the exact model (which is the usual bottleneck of failure probability calculations). Meanwhile the effort on evaluations of surrogates is dramatically reduced by utilizing low order local surrogates. Numerical results of the application of the proposed approach in several examples of increasing complexity show the robustness, versatility and gain in efficiency of the method.

preprint2015arXiv

Electrically tunable resonant scattering in fluorinated bilayer graphene

Adatom-decorated graphene offers a promising new path towards spintronics in the ultrathin limit. We combine experiment and theory to investigate the electronic properties of dilutely fluorinated bilayer graphene, where the fluorine adatoms covalently bond to the top graphene layer. We show that fluorine adatoms give rise to resonant impurity states near the charge neutrality point of the bilayer, leading to strong scattering of charge carriers and hopping conduction inside a field-induced band gap. Remarkably, the application of an electric field across the layers is shown to tune the resonant scattering amplitude from fluorine adatoms by nearly twofold. The experimental observations are well explained by a theoretical analysis combining Boltzmann transport equations and fully quantum-mechanical methods. This paradigm can be generalized to many bilayer graphene-adatom materials, and we envision that the realization of electrically tunable resonance may be a key advantage in graphene-based spintronic devices.

preprint2015arXiv

Extended fast search clustering algorithm: widely density clusters, no density peaks

CFSFDP (clustering by fast search and find of density peaks) is recently developed density-based clustering algorithm. Compared to DBSCAN, it needs less parameters and is computationally cheap for its non-iteration. Alex. at al have demonstrated its power by many applications. However, CFSFDP performs not well when there are more than one density peak for one cluster, what we name as "no density peaks". In this paper, inspired by the idea of a hierarchical clustering algorithm CHAMELEON, we propose an extension of CFSFDP,E_CFSFDP, to adapt more applications. In particular, we take use of original CFSFDP to generating initial clusters first, then merge the sub clusters in the second phase. We have conducted the algorithm to several data sets, of which, there are "no density peaks". Experiment results show that our approach outperforms the original one due to it breaks through the strict claim of data sets.

preprint2015arXiv

Global Existence of Weak Solutions to the Barotropic Compressible Navier-Stokes Flows with Degenerate Viscosities

This paper concerns the existence of global weak solutions to the barotropic compressible Navier-Stokes equations with degenerate viscosity coefficients. We construct suitable approximate system which has smooth solutions satisfying the energy inequality, the BD entropy one, and the Mellet-Vasseur type estimate. Then, after adapting the compactness results due to Mellet-Vasseur [Comm. Partial Differential Equations 32 (2007)], we obtain the global existence of weak solutions to the barotropic compressible Navier-Stokes equations with degenerate viscosity coefficients in two or three dimensional periodic domains or whole space for large initial data. This, in particular, solved an open problem in [P. L. Lions. Mathematical topics in fluid mechanics. Vol. 2. Compressible models. Oxford University Press, 1998].

preprint2015arXiv

Joint Transceiver Design for Wireless Sensor Networks through Block Coordinate Descent Optimization

This paper considers the joint transceiver design in a wireless sensor network where multiple sensors observe the same physical event and transmit their contaminated observations to a fusion center, with all nodes equipped with multiple antennae and linear filters. Under the mean square error (MSE) criterion, the joint beamforming design problem can be formulated as a nonconvex optimization problem. To attack this problem, various block coordinate descent (BCD) algorithms are proposed with convergence being carefully examined. First we propose a two block coordinate descent (2-BCD) algorithm that iteratively designs all the beamformers and the linear receiver, where both subproblems are convex and the convergence of limit points to stationary points is guaranteed. Besides, the thorough solution to optimizing one single beamformer is given, which, although discussed several times, is usually incomplete in existing literature. Based on that, multiple block coordinate descent algorithms are proposed. Solving the joint beamformers' design by cyclically updating each separate beamformer under the 2-BCD framework gives birth to a layered BCD algorithm, which guarantees convergence to stationary points. Besides that, a wide class of multiple BCD algorithms using the general essentially cyclic updating rule has been studied. As will be seen, by appropriately adjusting the update of single beamformer, fast converging, highly efficient and stationary point achieving algorithms can be obtained. Extensive numerical results are presented to verify our findings.

preprint2015arXiv

MIMO Beamforming Design towards Maximizing Mutual Information in Wireless Sensor Network

This paper considers joint beamformer design towards maximizing the mutual information in a coherent wireless sensor network with noisy observation and multiple antennae. Leveraging the weighted minimum mean square error and block coordinate ascent (BCA) framework, we propose two new and efficient methods: batch-mode BCA and cyclic multi-block BCA. The existing batch-mode approaches require stringent conditions such as diagonal channel matrices and positive definite second-order matrices, and are therefore inapplicable to our problem. Our match-mode BCA overcomes the previous limitations via a general second-order cone programming formation, and exhibits a strong convergence property which we have rigorously proven. The existing multi-block approaches rely on numerical solvers to handle the subproblems and some render good performance only at high signal-to-noise ratios. Exploiting the convexity of the trust-region subproblem for the convex case, our multi-block BCA significantly reduces the complexity and enhances the previous results by providing an analytical expression for the energy-preserving optimal solution. Analysis and simulations confirm the advantages of the proposed methods.

preprint2015arXiv

Minimal Logarithmic Signatures for Sporadic Groups

As a special type of factorization of finite groups, logarithmic signature (LS) is used as the main component of cryptographic keys for secret key cryptosystems such as PGM and public key cryptosystems like MST1, MST2 and MST3. An LS with the shortest length is called a minimal logarithmic signature (MLS) and is even desirable for cryptographic constructions. The MLS conjecture states that every finite simple group has an MLS. Until now, the MLS conjecture has been proved true for some families of simple groups. In this paper, we will prove the existence of minimal logarithmic signatures for some sporadic groups.

preprint2015arXiv

Nucleus and Mass Loss from Active Asteroid 313P/Gibbs

We present Hubble Space Telescope observations of active asteroid 313P/Gibbs (formerly P/2014 S4) taken over the five month interval from 2014 October to 2015 March. This object has been recurrently active near perihelion (at 2.4 AU) in two different orbits, a property that is naturally explained by the sublimation of near surface ice but which is difficult to reconcile with other activity mechanisms. We find that the mass loss peaks near 1 kg s$^{-1}$ in October and then declines over the subsequent months by about a factor of five, at nearly constant heliocentric distance. This decrease is too large to be caused by the change in heliocentric distance during the period of observation. However, it is consistent with sublimation from an ice patch shadowed by local topography, for example in a pit like those observed on the nuclei of short-period comet 67P/Churyumov-Gerasimenko. While no unique interpretation is possible, a simple self shadowing model shows that sublimation from a pit with depth to diameter ratio near 1/2 matches the observed rate of decline of the activity, while deeper and shallower pits do not. We estimate the nucleus radius to be 700$\pm$100 m (geometric albedo 0.05 assumed). Measurements of the spatial distribution of the dust were obtained from different viewing geometries. They show that dust was ejected continuously not impulsively, that the effective particle size is large, $\sim$50 $μm$, and that the ejection speed is $\sim$2.5 m s$^{-1}$. The total dust mass ejected is $\sim$10$^7$ kg, corresponding to $\sim$10$^{-5}$ of the nucleus mass. The observations are consistent with partially shadowed sublimation from $\sim$10$^4$ m$^2$ of ice, corresponding to $\sim$0.2\% of the nucleus surface. For ice to survive in 313P for billion-year timescales requires that the duty cycle for sublimation be $\lesssim$10$^{-3}$.

preprint2015arXiv

Partial Decode-Forward Relaying for the Gaussian Two-Hop Relay Network

The multicast capacity of the Gaussian two-hop relay network with one source, $N$ relays, and $L$ destinations is studied. It is shown that a careful modification of the partial decode--forward coding scheme, whereby the relays cooperate through degraded sets of message parts, achieves the cutset upper bound within $(1/2)\log N$ bits regardless of the channel gains and power constraints. This scheme improves upon a previous scheme by Chern and Ozgur, which is also based on partial decode--forward yet has an unbounded gap from the cutset bound for $L \ge 2$ destinations. When specialized to independent codes among relays, the proposed scheme achieves within $\log N$ bits from the cutset bound. The computation of this relaxation involves evaluating mutual information across $L(N+1)$ cuts out of the total $L 2^N$ possible cuts, providing a very simple linear-complexity algorithm to approximate the single-source multicast capacity of the Gaussian two-hop relay network.

preprint2015arXiv

Phonon-limited carrier mobility and resistivity from carbon nanotubes to graphene

Under which conditions do the electrical transport properties of one-dimensional (1D) carbon nanotubes (CNTs) and 2D graphene become equivalent? We have performed atomistic calculations of the phonon-limited electrical mobility in graphene and in a wide range of CNTs of different types to address this issue. The theoretical study is based on a tight-binding method and a force-constant model from which all possible electron-phonon couplings are computed. The electrical resistivity of graphene is found in very good agreement with experiments performed at high carrier density. A common methodology is applied to study the transition from 1D to 2D by considering CNTs with diameter up to 16 nm. It is found that the mobility in CNTs of increasing diameter converges to the same value, the mobility in graphene. This convergence is much faster at high temperature and high carrier density. For small-diameter CNTs, the mobility strongly depends on chirality, diameter, and existence of a bandgap.

preprint2015arXiv

Rings and Radial Waves in the Disk of the Milky Way

We show that in the anticenter region, between Galactic longitudes of $110^\circ<l<229^\circ$, there is an oscillating asymmetry in the main sequence star counts on either side of the Galactic plane using data from the Sloan Digital Sky Survey. This asymmetry oscillates from more stars in the north at distances of about 2 kpc from the Sun to more stars in the south at 4-6 kpc from the Sun to more stars in the north at distances of 8-10 kpc from the Sun. We also see evidence that there are more stars in the south at distances of 12-16 kpc from the Sun. The three more distant asymmetries form roughly concentric rings around the Galactic center, opening in the direction of the Milky Way's spiral arms. The northern ring, 9 kpc from the Sun, is easily identified with the previously discovered Monoceros Ring. Parts of the southern ring at 14 kpc from the Sun (which we call the TriAnd Ring) have previously been identified as related to the Monoceros Ring and others have been called the Triangulum Andromeda Overdensity. The two nearer oscillations are approximated by a toy model in which the disk plane is offset by of the order 100 pc up and then down at different radii. We also show that the disk is not azimuthally symmetric around the Galactic anticenter and that there could be a correspondence between our observed oscillations and the spiral structure of the Galaxy. Our observations suggest that the TriAnd and Monoceros Rings (which extend to at least 25 kpc from the Galactic center) are primarily the result of disk oscillations.

preprint2015arXiv

Spin relaxation via exchange with donor impurity-bound electrons

At low temperatures, electrons in semiconductors are bound to shallow donor impurity ions, neutralizing their charge in equilibrium. Inelastic scattering of other externally-injected conduction electrons accelerated by electric fields can excite transitions within the manifold of these localized states. Promotion of the bound electron into highly spin-orbit-mixed excited states drives a strong spin relaxation of the conduction electrons via exchange interactions, reminiscent of the Bir-Aronov-Pikus process where exchange occurs with valence band hole states. Through low-temperature experiments with silicon spin transport devices and complementary theory, we reveal the consequences of this previously unknown spin depolarization mechanism both below and above the impact ionization threshold.

preprint2015arXiv

Symmetry-breaking in drop bouncing on curved surfaces

The impact of liquid drops on solid surfaces is ubiquitous in nature, and of practical importance in many industrial processes. A drop hitting a flat surface retains a circular symmetry throughout the impact process. Here we show that a drop impinging on Echevaria leaves exhibits asymmetric bouncing dynamics with distinct spreading and retraction along two perpendicular directions. This is a direct consequence of the cylindrical leaves which have a convex/concave architecture of size comparable to the drop. Systematic experimental investigations on mimetic surfaces and lattice Boltzmann simulations reveal that this novel phenomenon results from an asymmetric momentum and mass distribution that allows for preferential fluid pumping around the drop rim. The asymmetry of the bouncing leads to ~40% reduction in contact time.

preprint2015arXiv

The M-giant star candidates identified in the LAMOST data release 1

We perform a discrimination procedure with the spectral index diagram of TiO5 and CaH2+CaH3 to separate M giants from M dwarfs. Using the M giant spectra identified from the LAMOST DR1 with high signal-to-noise ratio (SNR), we have successfully assembled a set of M giant templates, which show more reliable spectral features. Combining with the M dwarf/subdwarf templates in Zhong et al. (2015), we present an extended M-type templates library which includes not only M dwarfs with well-defined temperature and metallicity grid but also M giants with subtype from M0 to M6. Then, the template-fit algorithm were used to automatically identify and classify M giant stars from the LAMOST DR1. The result of M giant stars catalog is cross-matched with 2MASS JHKs and WISE W1/W2 infrared photometry. In addition, we calculated the heliocentric radial velocity of all M giant stars by using the cross-correlation method with the template spectrum in a zero-velocity restframe. Using the relationship between the absolute infrared magnitude MJ and our classified spectroscopic subtype, we derived the spectroscopic distance of M giants with uncertainties of about 40%. A catalog of 8639 M giants is provided. As an additional search result, we also present 101690 M dwarfs/subdwarfs catalog which were classified by our classification pipeline.

preprint2015arXiv

Transceiver Design for Clustered Wireless Sensor Networks --- Towards SNR Maximization

This paper investigates the transceiver design problem in a noisy-sensing noisy-transmission multi-input multi-output (MIMO) wireless sensor network. Consider a cluster-based network, where multiple sensors scattering across several clusters will first send their noisy observations to their respective cluster-heads (CH), who will then forward the data to one common fusion center (FC). The cluster-heads and the fusion center collectively form a coherent-sum multiple access channel (MAC) that is affected by fading and additive noise. Our goal is to jointly design the linear transceivers at the CHs and the FC to maximize the signal-to-noise ratio (SNR) of the recovered signal. We develop three iterative block coordinated ascent (BCA) algorithms: 2-block BCA based on semidefinite relaxation (SDR) and rank reduction via randomization or solving linear equations, 2-block BCA based on iterative second-order cone programming (SOCP), and multi-block BCA that lends itself to efficient closed-form solutions in specific but important scenarios. We show that all of these methods optimize SNR very well but each has different efficiency characteristics that are tailored for different network setups. Convergence analysis is carried out and extensive numerical results are presented to confirm our findings.

preprint2014arXiv

A FETI-DP type domain decomposition algorithm for three-dimensional incompressible Stokes equations

The FETI-DP algorithms, proposed by the authors in [SIAM J. Numer. Anal., 51 (2013), pp.~1235--1253] and [Internat. J. Numer. Methods Engrg., 94 (2013), pp.~128--149] for solving incompressible Stokes equations, are extended to three-dimensional problems. A new analysis of the condition number bound for using the Dirichlet preconditioner is given. An advantage of this new analysis is that the numerous coarse level velocity components, required in the previous analysis to enforce the divergence free subdomain boundary velocity conditions, are no longer needed. This greatly reduces the size of the coarse level problem in the algorithm, especially for three-dimensional problems. The coarse level velocity space can be chosen as simple as for solving scalar elliptic problems corresponding to each velocity component. Both Dirichlet and lumped preconditioners are analyzed using a same framework in this new analysis. Their condition number bounds are proved to be independent of the number of subdomains for fixed subdomain problem size. Numerical experiments in both two and three dimensions demonstrate the convergence rate of the algorithms.

preprint2014arXiv

Aspects of structural landscape of human islet amyloid polypeptide

The human islet amyloid polypeptide (hIAPP) co-operates with insulin to maintain glycemic balance. It also constitutes the amyloid plaques that aggregate in the pancreas of type-II diabetic patients. We have performed extensive in silico investigations to analyse the structural landscape of monomeric hIAPP, which is presumed to be intrinsically disordered. For this we construct from first principles a highly predictive energy function that describes a monomeric hIAPP observed in a NMR experiment, as a local energy minimum. We subject our theoretical model of hIAPP to repeated heating and cooling simulations, back and forth between a high temperature regime where the conformation resembles a random walker and a low temperature limit where no thermal motions prevail. We find that the final low temperature conformations display a high level of degeneracy, in a manner which is fully in line with the presumed intrinsically disordered character of hIAPP. In particular, we identify an isolated family of alpha-helical conformations that might cause the transition to amyloidosis, by nucleation.

preprint2014arXiv

Conditions for supersonic bent Marshak waves

Supersonic radiation diffusion approximation is a useful way to study the radiation transportation. Considering the bent Marshak wave theory in 2-dimensions, and an invariable source temperature, we get the supersonic radiation diffusion conditions which are about the Mach number $M>8(1+\sqrt{\ep})/3$, and the optical depth $τ>1$. A large Mach number requires a high temperature, while a large optical depth requires a low temperature. Only when the source temperature is in a proper region these conditions can be satisfied. Assuming the material opacity and the specific internal energy depend on the temperature and the density as a form of power law, for a given density, these conditions correspond to a region about source temperature and the length of the sample. This supersonic diffusion region involves both lower and upper limit of source temperature, while that in 1-dimension only gives a lower limit. Taking $\rm SiO_2$ and the Au for example, we show the supersonic region numerically.

preprint2014arXiv

Disintegrating Asteroid P/2013 R3

Splitting of the nuclei of comets into multiple components has been frequently observed but, to date, no main-belt asteroid has been observed to break-up. Using the Hubble Space Telescope, we find that main-belt asteroid P/2013 R3 consists of 10 or more distinct components, the largest up to 200 m in radius (assumed geometric albedo of 0.05) each of which produces a coma and comet-like dust tail. A diffuse debris cloud with total mass roughly 2x10^8 kg further envelopes the entire system. The velocity dispersion among the components is about V = 0.2 to 0.5 m/s, is comparable to the gravitational escape speeds of the largest members, while their extrapolated plane-of-sky motions suggest break-up between February and September 2013. The broadband optical colors are those of a C-type asteroid. We find no spectral evidence for gaseous emission, placing model-dependent upper limits to the water production rate near 1 kg/s. Breakup may be due to a rotationally induced structural failure of the precursor body.

preprint2014arXiv

Mesh refinement for uncertainty quantification through model reduction

We present a novel way of deciding when and where to refine a mesh in probability space in order to facilitate the uncertainty quantification in the presence of discontinuities in random space. A discontinuity in random space makes the application of generalized polynomial chaos expansion techniques prohibitively expensive. The reason is that for discontinuous problems, the expansion converges very slowly. An alternative to using higher terms in the expansion is to divide the random space in smaller elements where a lower degree polynomial is adequate to describe the randomness. In general, the partition of the random space is a dynamic process since some areas of the random space, particularly around the discontinuity, need more refinement than others as time evolves. In the current work we propose a way to decide when and where to refine the random space mesh based on the use of a reduced model. The idea is that a good reduced model can monitor accurately, within a random space element, the cascade of activity to higher degree terms in the chaos expansion. In terms, this facilitates the efficient allocation of computational sources to the areas of random space where they are more needed. For the Kraichnan-Orszag system, the prototypical system to study discontinuities in random space, we present theoretical results which show why the proposed method is sound and numerical results which corroborate the theory.

preprint2014arXiv

New Active Asteroid 313P/Gibbs

We present initial observations of the newly-discovered active asteroid 313P/Gibbs (formerly P/2014 S4), taken to characterize its nucleus and comet-like activity. The central object has a radius $\sim$0.5 km (geometric albedo 0.05 assumed). We find no evidence for secondary nuclei and set (with qualifications) an upper limit to the radii of such objects near 25 m, assuming the same albedo. Both aperture photometry and a morphological analysis of the ejected dust show that mass-loss is continuous at rates $\sim$0.2 to 0.4 kg s$^{-1}$, inconsistent with an impact origin. Large dust particles, with radii $\sim$50 to 100 $μ$m, dominate the optical appearance. At 2.4 AU from the Sun, the surface equilibrium temperatures are too low for thermal or desiccation stresses to be responsible for the ejection of dust. No gas is spectroscopically detected (limiting the gas mass loss rate to $<$1.8 kg s$^{-1}$). However, the protracted emission of dust seen in our data and the detection of another episode of dust release near perihelion, in archival observations from 2003, are highly suggestive of an origin by the sublimation of ice. Coincidentally, the orbit of 313P/Gibbs is similar to those of several active asteroids independently suspected to be ice sublimators, including P/2012 T1, 238P/Read and 133P/Elst-Pizarro, suggesting that ice is abundant in the outer asteroid belt.

preprint2014arXiv

New approaches to plactic monoid via Gröbner-Shirshov bases

We present the plactic algebra on an arbitrary alphabet set $A$ by row generators and column generators respectively. We give Gröbner-Shirshov bases for such presentations. In the case of column generators, a finite Gröbner-Shirshov basis is given if $A$ is finite. From the Composition-Diamond lemma for associative algebras, it follows that the set of Young tableaux is a linear basis of plactic algebra. As the result, it gives a new proof that Young tableaux are normal forms of elements of plactic monoid. This result was proved by D.E. Knuth \cite{Knuth} in 1970, see also Chapter 5 in \cite{M.L}.

preprint2014arXiv

Numerical methods for reconstruction of source term of heat equation from the final overdetermination

This paper deals with the numerical methods for the reconstruction of source term in linear parabolic equation from final overdetermination. We assume that the source term has the form f(x)h(t) and h(t) is given, which guarantees the uniqueness of the inverse problem for determining the source term $f(x)$ from final overdetermination. We present the numerical methods for both free boundary and Neumann boundary situations. Moreover, we show that the solution of the boundary conditions problem has the form of the free boundary solution problem by using the extension method. Numerical experiments are done for the inverse problem with the boundary conditions.

preprint2014arXiv

On a conjecture about tricyclic graphs with maximal energy

For a given simple graph $G$, the energy of $G$, denoted by $\mathcal {E}(G)$, is defined as the sum of the absolute values of all eigenvalues of its adjacency matrix, which was defined by I. Gutman. The problem on determining the maximal energy tends to be complicated for a given class of graphs. There are many approaches on the maximal energy of trees, unicyclic graphs and bicyclic graphs, respectively. Let $P^{6,6,6}_n$ denote the graph with $n\geq 20$ vertices obtained from three copies of $C_6$ and a path $P_{n-18}$ by adding a single edge between each of two copies of $C_6$ to one endpoint of the path and a single edge from the third $C_6$ to the other endpoint of the $P_{n-18}$. Very recently, Aouchiche et al. [M. Aouchiche, G. Caporossi, P. Hansen, Open problems on graph eigenvalues studied with AutoGraphiX, {\it Europ. J. Comput. Optim.} {\bf 1}(2013), 181--199] put forward the following conjecture: Let $G$ be a tricyclic graphs on $n$ vertices with $n=20$ or $n\geq22$, then $\mathcal{E}(G)\leq \mathcal{E}(P_{n}^{6,6,6})$ with equality if and only if $G\cong P_{n}^{6,6,6}$. Let $G(n;a,b,k)$ denote the set of all connected bipartite tricyclic graphs on $n$ vertices with three vertex-disjoint cycles $C_{a}$, $C_{b}$ and $C_{k}$, where $n\geq 20$. In this paper, we try to prove that the conjecture is true for graphs in the class $G\in G(n;a,b,k)$, but as a consequence we can only show that this is true for most of the graphs in the class except for 9 families of such graphs.

preprint2014arXiv

Re-examining Sunspot Tilt Angle to Include Anti-Hale Statistics

Sunspot groups and bipolar magnetic regions (BMRs) serve as an observational diagnostic of the solar cycle. We use Debrecen Photohelographic Data (DPD) from 1974-2014 that determined sunspot tilt angles from daily white light observations, and data provided by Li & Ulrich that determined sunspot magnetic tilt angle using Mount Wilson magnetograms from 1974-2012. The magnetograms allowed for BMR tilt angles that were anti-Hale in configuration, so tilt values ranged from 0 to 360° rather than the more common $\pm$ 90°. We explore the visual representation of magnetic tilt angles on a traditional butterfly diagram by plotting the mean area-weighted latitude of umbral activity in each bipolar sunspot group, including tilt information. The large scatter of tilt angles over the course of a single cycle and hemisphere prevents Joy's law from being visually identified in the tilt-butterfly diagram without further binning. The average latitude of anti-Hale regions does not differ from the average latitude of all regions in both hemispheres. The distribution of anti-Hale sunspot tilt angles are broadly distributed between 0 and 360° with a weak preference for east-west alignment 180° from their expected Joy's law angle. The anti-Hale sunspots display a log-normal size distribution similar to that of all sunspots, indicating no preferred size for anti-Hale sunspots. We report that 8.4% $\pm$ 0.8% of all bipolar sunspot regions are misclassified as Hale in traditional catalogs. This percentage is slightly higher for groups within 5° of the equator due to the misalignment of the magnetic and heliographic equators.

preprint2014arXiv

Super-Resolution Compressed Sensing: A Generalized Iterative Reweighted L2 Approach

Conventional compressed sensing theory assumes signals have sparse representations in a known, finite dictionary. Nevertheless, in many practical applications such as direction-of-arrival (DOA) estimation and line spectral estimation, the sparsifying dictionary is usually characterized by a set of unknown parameters in a continuous domain. To apply the conventional compressed sensing technique to such applications, the continuous parameter space has to be discretized to a finite set of grid points, based on which a "presumed dictionary" is constructed for sparse signal recovery. Discretization, however, inevitably incurs errors since the true parameters do not necessarily lie on the discretized grid. This error, also referred to as grid mismatch, may lead to deteriorated recovery performance or even recovery failure. To address this issue, in this paper, we propose a generalized iterative reweighted L2 method which jointly estimates the sparse signals and the unknown parameters associated with the true dictionary. The proposed algorithm is developed by iteratively decreasing a surrogate function majorizing a given objective function, resulting in a gradual and interweaved iterative process to refine the unknown parameters and the sparse signal. A simple yet effective scheme is developed for adaptively updating the regularization parameter that controls the tradeoff between the sparsity of the solution and the data fitting error. Extension of the proposed algorithm to the multiple measurement vector scenario is also considered. Numerical results show that the proposed algorithm achieves a super-resolution accuracy and presents superiority over other existing methods.

preprint2014arXiv

Super-Resolution Compressed Sensing: An Iterative Reweighted Algorithm for Joint Parameter Learning and Sparse Signal Recovery

In many practical applications such as direction-of-arrival (DOA) estimation and line spectral estimation, the sparsifying dictionary is usually characterized by a set of unknown parameters in a continuous domain. To apply the conventional compressed sensing to such applications, the continuous parameter space has to be discretized to a finite set of grid points. Discretization, however, incurs errors and leads to deteriorated recovery performance. To address this issue, we propose an iterative reweighted method which jointly estimates the unknown parameters and the sparse signals. Specifically, the proposed algorithm is developed by iteratively decreasing a surrogate function majorizing a given objective function, which results in a gradual and interweaved iterative process to refine the unknown parameters and the sparse signal. Numerical results show that the algorithm provides superior performance in resolving closely-spaced frequency components.

preprint2014arXiv

The K giant stars from the LAMOST survey data I: identification, metallicity, and distance

We present a support vector machine classifier to identify the K giant stars from the LAMOST survey directly using their spectral line features. The completeness of the identification is about 75% for tests based on LAMOST stellar parameters. The contamination in the identified K giant sample is lower than 2.5%. Applying the classification method to about 2 million LAMOST spectra observed during the pilot survey and the first year survey, we select 298,036 K giant candidates. The metallicities of the sample are also estimated with uncertainty of $0.13\sim0.29$\,dex based on the equivalent widths of Mg$_{\rm b}$ and iron lines. A Bayesian method is then developed to estimate the posterior probability of the distance for the K giant stars, based on the estimated metallicity and 2MASS photometry. The synthetic isochrone-based distance estimates have been calibrated using 7 globular clusters with a wide range of metallicities. The uncertainty of the estimated distance modulus at $K=11$\,mag, which is the median brightness of the K giant sample, is about 0.6\,mag, corresponding to $\sim30$% in distance. As a scientific verification case, the trailing arm of the Sagittarius stream is clearly identified with the selected K giant sample. Moreover, at about 80\,kpc from the Sun, we use our K giant stars to confirm a detection of stream members near the apo-center of the trailing tail. These rediscoveries of the features of the Sagittarius stream illustrate the potential of the LAMOST survey for detecting substructures in the halo of the Milky Way.

preprint2014arXiv

The Nearest High-Velocity Stars Revealed by LAMOST Data Release 1

We report the discovery of 28 candidate high-velocity stars (HVSs) at heliocentric distances of less than 3 kpc, based on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Data Release 1. Our sample of HVS candidates covers a much broader color range than the equivalent ranges discussed in previous studies and comprises the first and largest sample of HVSs in the solar neighborhood. The sufficiently accurate observed and derived parameters for all candidates allow us to ascertain their nature as genuine HVSs, while a subset of 12 objects represents the most promising candidates. Our results also highlight the great potential of discovering statistically large numbers of HVSs of different spectral types in LAMOST survey data. This will ultimately enable us to achieve a better understanding of the nature of Galactic HVSs and their ejection mechanisms, and to constrain the structure of the Galaxy.

preprint2014arXiv

Water Reaction Mechanism in Metal Organic Frameworks with Coordinatively Unsaturated Metal Ions: MOF-74

Water dissociation represents one of the most important reactions in catalysis, essential to the surface and nano sciences [e.g., Hass et al., Science, 1998, 282, 265-268; Brown et al., Science 2001, 294, 67-69; Bikondoa et al., Nature 2005, 5, 189-192]. However, the dissociation mechanism on most oxide surfaces is not well understood due to the experimental challenges of preparing surface structures and characterizing reaction pathways. To remedy this problem, we propose the metal organic framework MOF-74 as an ideal model system to study water reactions. Its crystalline structure is well characterized; the metal oxide node mimics surfaces with exposed cations; and it degrades in water. Combining in situ IR spectroscopy and first-principles calculations, we explored the MOF-74/water interaction as a function of vapor pressure and temperature. Here, we show that, while adsorption is reversible below the water condensation pressure (~19.7 Torr) at room temperature, a reaction takes place at ~150 centigrades even at low water vapor pressures. This important finding is unambiguously demonstrated by a clear spectroscopic signature for the direct reaction using D2O, which is not present using H2O due to strong phonon coupling. Specifically, a sharp absorption band appears at 970 cm-1 when D2O is introduced at above 150 centigrades, which we attribute to an O-D bending vibration on the phenolate linker. Although H2O undergoes a similar dissociation reaction, the corresponding O-H mode is too strongly coupled to MOF vibrations to detect. In contrast, the O-D mode falls in the phonon gap of the MOF and remains localized.

preprint2013arXiv

Analog Turbo Codes: Turning Chaos to Reliability

Analog error correction codes, by relaxing the source space and the codeword space from discrete fields to continuous fields, present a generalization of digital codes. While linear codes are sufficient for digital codes, they are not for analog codes, and hence nonlinear mappings must be employed to fully harness the power of analog codes. This paper demonstrates new ways of building effective (nonlinear) analog codes from a special class of nonlinear, fast-diverging functions known as the chaotic functions. It is shown that the "butterfly effect" of the chaotic functions matches elegantly with the distance expansion condition required for error correction, and that the useful idea in digital turbo codes can be exploited to construct efficient turbo-like chaotic analog codes. Simulations show that the new analog codes can perform on par with, or better than, their digital counter-parts when transmitting analog sources.

preprint2013arXiv

Anisotropy-driven spin relaxation in germanium

A unique spin depolarization mechanism, induced by the presence of g-factor anisotropy and intervalley scattering, is revealed by spin transport measurements on long-distance germanium devices in a longitudinal magnetic field. The confluence of electron-phonon scattering (leading to Elliott-Yafet spin flips) and this previously unobserved physics enables the extraction of spin lifetime solely from spin-valve measurements, without spin precession, and in a regime of substantial electric-field-generated carrier heating. We find spin lifetimes in Ge up to several hundreds of ns at low temperature, far beyond any other available experimental results.

preprint2013arXiv

DA white dwarfs observed in LAMOST pilot survey

A total of $\sim640,000$ objects from LAMOST pilot survey have been publicly released. In this work, we present a catalog of DA white dwarfs from the entire pilot survey. We outline a new algorithm for the selection of white dwarfs by fitting Sérsic profiles to the Balmer H$β$, H$γ$ and H$δ$ lines of the spectra, and calculating the equivalent width of the CaII K line. 2964 candidates are selected by constraining the fitting parameters and the equivalent width of CaII K line. All the spectra of candidates are visually inspected. We identify 230 (59 of them are already in Villanova and SDSS WD catalog) DA white dwarfs, 20 of which are DA white dwarfs with non-degenerate companions. In addition, 128 candidates are classified as DA white dwarf/subdwarfs, which means the classifications are ambiguous. The result is consistent with the expected DA white dwarf number estimated based on the LEGUE target selection algorithm.

preprint2013arXiv

Explicit calculation of strong solution on linear parabolic equation

In this paper, we give the existence and uniqueness of the strong solution of one dimensional linear parabolic equation with mixed boundary conditions. The boundary conditions can be any kind of mixed Dirichlet, Neumann and Robin boundary conditions. We use the extension method to get the unique solution. Furthermore, the method can also be easily implemented as a numerical method. Some simple examples are presented.

preprint2013arXiv

Global Well-Posedness and Large Time Asymptotic Behavior of Classical Solutions to the Compressible Navier-Stokes Equations with Vacuum

This paper concerns the global well-posedness and large time asymptotic behavior of strong and classical solutions to the Cauchy problem of the Navier-Stokes equations for viscous compressible barotropic flows in two or three spatial dimensions with vacuum as far field density. For strong and classical solutions, some a priori decay with rates (in large time) for both the pressure and the spatial gradient of the velocity field are obtained provided that the initial total energy is suitably {small.} Moreover, by using these key decay rates and some analysis on the expansion rates of the essential support of the density, we establish the global existence and uniqueness of classical solutions (which may be of possibly large oscillations) in two spatial dimensions, provided the smooth initial data are of small total energy. In addition, the initial density can even have compact support. This, in particular, yields the global regularity and uniqueness of the re-normalized weak solutions of Lions-Feireisl to the two-dimensional compressible barotropic flows for all adiabatic number $γ>1$ provided that the initial total energy is small.

preprint2013arXiv

Global Well-Posedness of Classical Solutions to the Cauchy problem of Two-Dimensional Baratropic Compressible Navier-Stokes System with Vacuum and Large Initial Data

For smooth initial data, we establish the global existence and uniqueness of strong and classical solutions to the Cauchy problem for the barotropic compressible Navier-Stokes equations in two spatial dimensions with vacuum state as far field and with no restrictions on the size of initial data provided the shear viscosity is a positive constant and the bulk one is $λ= ρ^β$ with $β>4/3$.

preprint2013arXiv

Iterative Decoding and Turbo Equalization: The Z-Crease Phenomenon

Iterative probabilistic inference, popularly dubbed the soft-iterative paradigm, has found great use in a wide range of communication applications, including turbo decoding and turbo equalization. The classic approach of analyzing the iterative approach inevitably use the statistical and information-theoretical tools that bear ensemble-average flavors. This paper consider the per-block error rate performance, and analyzes it using nonlinear dynamical theory. By modeling the iterative processor as a nonlinear dynamical system, we report a universal "Z-crease phenomenon:" the zig-zag or up-and-down fluctuation -- rather than the monotonic decrease -- of the per-block errors, as the number of iteration increases. Using the turbo decoder as an example, we also report several interesting motion phenomenons which were not previously reported, and which appear to correspond well with the notion of "pseudo codewords" and "stopping/trapping sets." We further propose a heuristic stopping criterion to control Z-crease and identify the best iteration. Our stopping criterion is most useful for controlling the worst-case per-block errors, and helps to significantly reduce the average-iteration numbers.

preprint2013arXiv

Liquid and back gate coupling effect: towards biosensing with lowest detection limit

We employ noise spectroscopy and transconductance measurements to establish the optimal regimes of operation for our fabricated silicon nanowire field-effect transistors (Si NW FETs) sensors. A strong coupling between the liquid gate and back gate (the substrate) has been revealed and used for optimisation of signal-to-noise ratio in sub-threshold as well as above-threshold regimes. Increasing the sensitivity of Si NW FET sensors above the detection limit has been predicted and proven by direct experimental measurements.

preprint2013arXiv

Mechanism of preferential adsorption of SO$_2$ into two microporous paddle wheel frameworks M(bdc)(ted)0.5

The selective adsorption of a corrosive gas, SO$_2$, into two microporous pillared paddle-wheel frameworks M(bdc)(ted)0.5 [M = Ni, Zn; bdc = 1,4-benzenedicarboxylate; ted = triethylenediamine] is studied by volumetric adsorption measurements and a combination of in-situ infrared spectroscopy and ab initio density functional theory (DFT) calculations. The uptake of SO$_2$ in M(bdc)(ted)0.5 at room temperature is quite significant, 9.97 mol/kg at 1.13 bar. The major adsorbed SO$_2$ molecules contributing to the isotherm measurements are characterized by stretching bands at 1326 and 1144 cm$^{-1}$. Theoretical calculations including van der Waals interactions (based on vdW-DF) suggest that two adsorption configurations are possible for these SO$_2$ molecules. One geometry involves an SO$_2$ molecule bonded through its sulfur atom to the oxygen atom of the paddle-wheel building unit and its two oxygen atoms to the C-H groups of the organic linkers by formation of hydrogen bonds. Such a configuration results in a distortion of the benzene rings, which is consistent with the experimentally observed shift of the ring deformation mode. In the other geometry, SO$_2$ establishes hydrogen bonding with -CH$_2$ group of the ted linker through its two oxygen atoms simultaneously. The vdW-DF-simulated frequency shifts of the SO$_2$ stretching bands in these two configurations are similar and in good agreement with spectroscopically measured values of physisorbed SO$_2$.In addition, the IR spectra reveal the presence of another minor species, characterized by stretching modes at 1242 and 1105 cm$^{-1}$ and causing significant perturbations of MOFs vibrational modes (CH$_x$ and carboxylate groups). This species is more strongly bound, requiring a higher temperature ($\sim$150 $^\circ$C) to remove it than for the main physisorbed species.

preprint2013arXiv

Mobile Multimedia Recommendation in Smart Communities: A Survey

Due to the rapid growth of internet broadband access and proliferation of modern mobile devices, various types of multimedia (e.g. text, images, audios and videos) have become ubiquitously available anytime. Mobile device users usually store and use multimedia contents based on their personal interests and preferences. Mobile device challenges such as storage limitation have however introduced the problem of mobile multimedia overload to users. In order to tackle this problem, researchers have developed various techniques that recommend multimedia for mobile users. In this survey paper, we examine the importance of mobile multimedia recommendation systems from the perspective of three smart communities, namely, mobile social learning, mobile event guide and context-aware services. A cautious analysis of existing research reveals that the implementation of proactive, sensor-based and hybrid recommender systems can improve mobile multimedia recommendations. Nevertheless, there are still challenges and open issues such as the incorporation of context and social properties, which need to be tackled in order to generate accurate and trustworthy mobile multimedia recommendations.

preprint2013arXiv

On Classical Solutions to the Cauchy Problem of the Two-Dimensional Barotropic Compressible Navier-Stokes Equations with Vacuum

This paper concerns the Cauchy problem of the barotropic compressible Navier-Stokes equations on the whole two-dimensional space with vacuum as far field density. In particular, the initial density can have compact support. When the shear and the bulk viscosities are a positive constant and a power function of the density respectively, it is proved that the two-dimensional Cauchy problem of the compressible Navier-Stokes equations admits a unique local strong solution provided the initial density decays not too slow at infinity. Moreover, if the initial data satisfy some additional regularity and compatibility conditions, the strong solution becomes a classical one.

preprint2013arXiv

Optimal Dynamic Portfolio with Mean-CVaR Criterion

Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) are popular risk measures from academic, industrial and regulatory perspectives. The problem of minimizing CVaR is theoretically known to be of Neyman-Pearson type binary solution. We add a constraint on expected return to investigate the Mean-CVaR portfolio selection problem in a dynamic setting: the investor is faced with a Markowitz type of risk reward problem at final horizon where variance as a measure of risk is replaced by CVaR. Based on the complete market assumption, we give an analytical solution in general. The novelty of our solution is that it is no longer Neyman-Pearson type where the final optimal portfolio takes only two values. Instead, in the case where the portfolio value is required to be bounded from above, the optimal solution takes three values; while in the case where there is no upper bound, the optimal investment portfolio does not exist, though a three-level portfolio still provides a sub-optimal solution.

preprint2013arXiv

Plasmon resonance and heat generation model in nanostructures

In this paper, we investigate the photothermal effects of the plasmon resonance. Metal nanoparticles efficiently generate heat in the presence of electromagnetic radiation. The process is strongly enhanced when a fixed frequency of the incident wave illuminate on nanoprticles such that plasmon resonance happen. We shall introduce the electromagnetic radiation model and show exactly how and when the plasmon resonance happen. We then construct the heat generation and transfer model and derive the heat effect induced by plasmon resonance. Finally, we consider the heat generation under plasmon resonance in a concentric nanoshell structure.

preprint2013arXiv

Recurrent Perihelion Activity in (3200) Phaethon

We present a study of planet-crossing asteroid (3200) Phaethon at three successive perihelia in 2009, 2010 and 2012, using the NASA STEREO spacecraft. Phaethon is clearly detected in 2009 and 2012, but not in 2010. In both former years, Phaethon brightened unexpectedly by ~1 magnitude at large phase angles, inconsistent with the ~1 magnitude of steady fading expected from a discrete, macroscopic body over the same phase angle range. With a perihelion distance of 0.14 AU and surface temperatures up to ~1000 K, a thermal origin of this anomalous brightening is strongly suspected. However, simple thermal emission from Phaethon is too weak, by a factor >1000, to explain the brightening. Neither can ice survive on this body, ruling out comet-like sublimation. Our preferred explanation is that brightening occurs as a result of dust produced and ejected from Phaethon, perhaps by thermal fracture and/or thermal decomposition of surface minerals when near perihelion. A contribution from prompt emission by oxygen released by desiccation of surface minerals cannot be excluded. We infer an ejected mass of order 4x10^8 a_mm kg per outburst, where a_mm is the mean dust radius in millimeters. For plausible dust radii, this mass is small compared to the estimated mass of Phaethon (~2x10^14 kg) and to the mass of the Geminid stream (10^12 kg to 10^13 kg) with which Phaethon is dynamically associated. Perihelion mass-loss events like those observed in 2009 and 2012 contribute to, but do not necessarily account for the Geminids stream mass.

preprint2013arXiv

Recursive-Cube-of-Rings (RCR) Revisited: Properties and Enhancement

We study recursive-cube-of-rings (RCR), a class of scalable graphs that can potentially provide rich inter-connection network topology for the emerging distributed and parallel computing infrastructure. Through rigorous proof and validating examples, we have corrected previous misunderstandings on the topological properties of these graphs, including node degree, symmetry, diameter and bisection width. To fully harness the potential of structural regularity through RCR construction, new edge connecting rules are proposed. The modified graphs, referred to as {\it Class-II RCR}, are shown to possess uniform node degrees, better connectivity and better network symmetry, and hence will find better application in parallel computing.

preprint2013arXiv

The Dust Tail of Asteroid (3200) Phaethon

We report the discovery of a comet-like tail on asteroid (3200) Phaethon when imaged at optical wavelengths near perihelion. In both 2009 and 2012, the tail appears >=350" (2.5x10^8 m) in length and extends approximately in the projected anti-solar direction. We interpret the tail as being caused by dust particles accelerated by solar radiation pressure. The sudden appearance and the morphology of the tail indicate that the dust particles are small, with an effective radius ~1 micrometer and a combined mass ~3x10^5 kg. These particles are likely products of thermal fracture and/or desiccation cracking under the very high surface temperatures (~1000 K) experienced by Phaethon at perihelion. The existence of the tail confirms earlier inferences about activity in this body based on the detection of anomalous brightening. Phaethon, the presumed source of the Geminid meteoroids, is still active.

preprint2012arXiv

A 25 Gb/s Silicon Photonics Platform

Silicon has attracted attention as an inexpensive and scalable material system for photonic-electronic, system-on-chip development. For this, a platform with both photodetectors and modulators working at high speeds, with excellent cross-wafer uniformity, is needed. We demonstrate an optical-lithography, wafer-scale photonics platform with 25 Gb/s operation. We also demonstrate modulation with an ultra-low drive voltage of 1 Vpp at 25 Gb/s. We demonstrate attractive cross-wafer uniformity, and provide detailed information about the device geometry. Our platform is available to the community as part of a photonics shuttle service.

preprint2012arXiv

A non-overlapping domain decomposition method for incompressible Stokes equations with continuous pressure

A non-overlapping domain decomposition algorithm is proposed to solve the linear system arising from mixed finite element approximation of incompressible Stokes equations. A continuous finite element space for the pressure is used. In the proposed algorithm, Lagrange multipliers are used to enforce continuity of the velocity component across the subdomain domain boundary. The continuity of the pressure component is enforced in the primal form, i.e., neighboring subdomains share the same pressure degrees of freedom on the subdomain interface and no Lagrange multipliers are needed. After eliminating all velocity variables and the independent subdomain interior parts of the pressures, a symmetric positive semi-definite linear system for the subdomain boundary pressures and the Lagrange multipliers is formed and solved by a preconditioned conjugate gradient method. A lumped preconditioner is studied and the condition number bound of the preconditioned operator is proved to be independent of the number of subdomains for fixed subdomain problem size. Numerical experiments demonstrate the convergence rate of the proposed algorithm.

preprint2012arXiv

A study of strong pulses detected from PSR B0656+14 using Urumqi 25-m radio telescope at 1540MHz

We report on the properties of strong pulses from PSR B0656+14 by analyzing the data obtained using Urumqi 25-m radio telescope at 1540 MHz from August 2007 to September 2010. In 44 hrs of observational data, a total of 67 pulses with signal-to-noise ratios above a 5-σ threshold were detected. The peak flux densities of these pulses are 58 to 194 times that of the average profile, and the pulse energies of them are 3 to 68 times that of the average pulse. These pulses are clustered around phases about 5 degrees ahead of the peak of the average profile. Comparing with the width of the average profile, they are relatively narrow, with the full widths at half-maximum range from 0.28 to 1.78 degrees. The distribution of pulse-energies of the pulses follows a lognormal distribution. These sporadic strong pulses detected from PSR B0656+14 are different in character from the typical giant pulses, and from its regular pulses.

preprint2012arXiv

A unified FETI-DP approach for incompressible Stokes equations

A unified framework of FETI-DP algorithms is proposed for solving the system of linear equations arising from the mixed finite element approximation of incompressible Stokes equations. A distinctive feature of this framework is that it allows using both continuous and discontinuous pressures in the algorithm, while previous FETI-DP methods only apply to discontinuous pressures. A preconditioned conjugate gradient method is used in the algorithm with either a lumped or a Dirichlet preconditioner, and scalable convergence rates are proved. This framework is also used to describe several previously developed FETI-DP algorithms and greatly simplifies their analysis. Numerical experiments of solving a two-dimensional incompressible Stokes problem demonstrate the performances of the discussed FETI-DP algorithms represented under the same framework.

preprint2012arXiv

An Algorithm for Preferential Selection of Spectroscopic Targets in LEGUE

We describe a general target selection algorithm that is applicable to any survey in which the number of available candidates is much larger than the number of objects to be observed. This routine aims to achieve a balance between a smoothly-varying, well-understood selection function and the desire to preferentially select certain types of targets. Some target-selection examples are shown that illustrate different possibilities of emphasis functions. Although it is generally applicable, the algorithm was developed specifically for the LAMOST Experiment for Galactic Understanding and Exploration (LEGUE) survey that will be carried out using the Chinese Guo Shou Jing Telescope. In particular, this algorithm was designed for the portion of LEGUE targeting the Galactic halo, in which we attempt to balance a variety of science goals that require stars at fainter magnitudes than can be completely sampled by LAMOST. This algorithm has been implemented for the halo portion of the LAMOST pilot survey, which began in October 2011.

preprint2012arXiv

Analyzing the frequency shift of physiadsorbed CO2 in metal organic framework materials

Combining first-principles density functional theory simulations with IR and Raman experiments, we determine the frequency shift of vibrational modes of CO2 when physiadsorbed in the iso-structural metal organic framework materials Mg-MOF74 and Zn-MOF74. Surprisingly, we find that the resulting change in shift is rather different for these two systems and we elucidate possible reasons. We explicitly consider three factors responsible for the frequency shift through physiabsorption, namely (i) the change in the molecule length, (ii) the asymmetric distortion of the CO$_2$ molecule, and (iii) the direct influence of the metal center. The influence of each factor is evaluated separately through different geometry considerations, providing a fundamental understanding of the frequency shifts observed experimentally.

preprint2012arXiv

Bayesian logistic betting strategy against probability forecasting

We propose a betting strategy based on Bayesian logistic regression modeling for the probability forecasting game in the framework of game-theoretic probability by Shafer and Vovk (2001). We prove some results concerning the strong law of large numbers in the probability forecasting game with side information based on our strategy. We also apply our strategy for assessing the quality of probability forecasting by the Japan Meteorological Agency. We find that our strategy beats the agency by exploiting its tendency of avoiding clear-cut forecasts.

preprint2012arXiv

Challenging the Long Tail Recommendation

The success of "infinite-inventory" retailers such as Amazon.com and Netflix has been largely attributed to a "long tail" phenomenon. Although the majority of their inventory is not in high demand, these niche products, unavailable at limited-inventory competitors, generate a significant fraction of total revenue in aggregate. In addition, tail product availability can boost head sales by offering consumers the convenience of "one-stop shopping" for both their mainstream and niche tastes. However, most of existing recommender systems, especially collaborative filter based methods, can not recommend tail products due to the data sparsity issue. It has been widely acknowledged that to recommend popular products is easier yet more trivial while to recommend long tail products adds more novelty yet it is also a more challenging task. In this paper, we propose a novel suite of graph-based algorithms for the long tail recommendation. We first represent user-item information with undirected edge-weighted graph and investigate the theoretical foundation of applying Hitting Time algorithm for long tail item recommendation. To improve recommendation diversity and accuracy, we extend Hitting Time and propose efficient Absorbing Time algorithm to help users find their favorite long tail items. Finally, we refine the Absorbing Time algorithm and propose two entropy-biased Absorbing Cost algorithms to distinguish the variation on different user-item rating pairs, which further enhances the effectiveness of long tail recommendation. Empirical experiments on two real life datasets show that our proposed algorithms are effective to recommend long tail items and outperform state-of-the-art recommendation techniques.

preprint2012arXiv

Exchanging Third-Party Information with Minimum Transmission Cost

In this paper, we consider the problem of minimizing the total transmission cost for exchanging channel state information. We proposed a network coded cooperative data exchange scheme, such that the total transmission cost is minimized while each client can decode all the channel information held by all other clients. In this paper, we first derive a necessary and sufficient condition for a feasible transmission. Based on the derived condition, there exists a feasible code design to guarantee that each client can decode the complete information. We further formulate the problem of minimizing the total transmission cost as an integer linear programming. Finally, we discuss the probability that each client can decode the complete information with distributed random linear network coding.

preprint2012arXiv

Existence and Blowup Behavior of Global Strong Solutions to the Two-Dimensional Baratropic Compressible Navier-Stokes System with Vacuum and Large Initial Data

For periodic initial data with initial density allowed to vanish, we establish the global existence of strong and weak solutions for the two-dimensional compressible Navier-Stokes equations with no restrictions on the size of initial data provided the bulk viscosity coefficient is $λ= ρ^β$ with $β>4/3$. These results generalize and improve the previous ones due to Vaigant-Kazhikhov([Sib. Math. J. (1995), 36(6), 1283-1316]) which requires $β>3$. Moreover, both the uniform upper bound of the density and the large-time behavior of the strong and weak solutions are also obtained.

preprint2012arXiv

Global Well-Posedness with Large Oscillations and Vacuum to the Three-Dimensional Equations of Compressible Nematic Liquid Crystal Flows

This paper is concerned with the three-dimensional equations of a simplified hydrodynamic flow modeling the motion of compressible, nematic liquid crystal materials. The authors establish the global existence of classical solution to the Cauchy problem with smooth initial data which are of small energy but possibly large oscillations with constant state as far-field condition which could be either vacuum or non-vacuum. The initial density is allowed to vanish and the spatial measure of the set of vacuum can be arbitrarily large, in particular, the initial density can even have compact support. As a byproduct, the large-time behavior of the solution is also studied.

preprint2012arXiv

Influence of electron scatterings on thermoelectric effect

In this work, we employed non-equilibrium Green's function to investigate the electron transport properties in the nanowire with the presence of scatterings. The scattering mechanism is modelled by using the concept of Büttiker probe. The effect of electron scattering is analyzed under three conditions: absence of external field; with a bias voltage; and with a finite temperature difference. It is found weak and strong scatterings strength affect the electron transport in different ways. In the case of weak scattering strength, electron trapping increase the electron density, hereafter boost the conductance significantly. Although the increment in conductance would reduce the Seebeck coefficient slightly, the power factor still increases. In the case of strong scattering strength, electron diffraction causes the redistribution of electrons, accumulation of electron at the ends of the wire blocks current flow; hence the conductance is reduced significantly. Although the Seebeck coefficient increases slightly, the power factor still decreases. The power factor is enhanced by 6%-18%, at the optimum scattering strength.

preprint2012arXiv

LAMOST Experiment for Galactic Understanding and Exploration (LEGUE) The survey science plan

We describe the current plans for a spectroscopic survey of millions of stars in the Milky Way galaxy using the Guo Shou Jing Telescope (GSJT, formerly the Large Area Multi-Object Spectroscopic Telescope - LAMOST). The survey will obtain spectra for 2.5 million stars brighter than $r<19$ during dark/grey time, and 5 million stars brighter than $r<17$ or $J<16$ on nights that are moonlit or have low transparency. The survey will begin in fall of 2012, and will run for at least four years. The telescope design constrains the optimal declination range for observations to $10^\circ<δ<50^\circ$, and site conditions lead to an emphasis on stars in the direction of the Galactic anticenter. The survey is divided into three parts with different target selection strategies: disk, anticenter, and spheroid. The resulting dataset will be used to study the merger history of the Milky Way, the substructure and evolution of the disks, the nature of the first generation of stars through identification of the lowest metallicity stars, and star formation through study of open clusters and the OB associations. Detailed design of the LEGUE survey will be completed after a review of the results of the pilot survey in summer 2012.

preprint2012arXiv

Long-Term Measurements of Sunspot Magnetic Tilt Angles

Tilt angles of close to 30,600 sunspots are determined using Mount Wilson daily averaged magnetograms taken from 1974 to 2012, and MDI/SoHO magnetograms taken from 1996 to 2010. Within a cycle, more than 90% of sunspots have a normal polarity alignment along the east-west direction following Hale's law. The median tilts increase with increasing latitude (Joy's law) at a rate of ~0.5 degree per degree of latitude. Tilt angles of spots appear largely invariant with respect to time at a given latitude, but they decrease by ~0.9degree per year on average, a trend which largely reflects Joy's law following the butterfly diagram. We find an asymmetry between the hemispheres in the mean tilt angles. On average, the tilts are greater in the southern than in the northern hemisphere for all latitude zones, and the differences increase with increasing latitude.

preprint2012arXiv

Non-homogeneous distributed storage systems

This paper describes a non-homogeneous distributed storage systems (DSS), where there is one super node which has a larger storage size and higher reliability and availability than the other storage nodes. We propose three distributed storage schemes based on (k+2; k) maximum distance separable (MDS) codes and non-MDS codes to show the efficiency of such non-homogeneous DSS in terms of repair efficiency and data availability. Our schemes achieve optimal bandwidth (k+1/2)(M/k) when repairing 1-node failure, but require only one fourth of the minimum required file size and can operate with a smaller field size leading to significant complexity reduction than traditional homogeneous DSS. Moreover, with non-MDS codes, our scheme can achieve an even smaller repair bandwidth of M/2k . Finally, we show that our schemes can increase the data availability by 10% than the traditional homogeneous DSS scheme.

preprint2012arXiv

On Rings and Streams in the Galactic Anti-Center

We confirm that there are at least three separate low-latitude over-densities of blue F turnoff stars near the Milky Way anti-center: the Monoceros Ring, the Anti-Center Stream (ACS), and the Eastern Banded Structure (EBS). There might also be a small number of normal thick disk stars at the same location. The ACS is a tilted component that extends to higher Galactic latitude at lower Galactic longitude, 10 kpc from the Sun towards the anti-center. It has a sharp cutoff on the high latitude side. Distance, velocity, and proper motion measurements are consistent with previous orbit fits. The mean metallicity is [Fe/H]$=-0.96 \pm 0.03$, which is lower than the thick disk and Monoceros Ring. The Monoceros Ring is a higher density substructure that is present at $15\arcdeg<b<22\arcdeg$ at all longitudes probed in this survey. The structure likely continues towards lower latitudes. The distances are consistent with a constant distance from the Galactic Center of 17.6 kpc. The mean line-of-sight velocity of the structure is consistent with a thick disk rotation. However, the velocity dispersion of these stars is $\sim 15$ km s$^{-1}$, and the metallicity is [Fe/H]$=-0.80 \pm 0.01$. Both of these quantities are lower than the canonical thick disk. We suggest that this ring structure is likely different from the thick disk, though its association with the disk cannot be definitively ruled out. The Eastern Banded Structure (EBS) is detected primarily photometrically, near $(l,b)=(225\arcdeg,30\arcdeg)$, at a distance of 10.9 kpc from the Sun.

preprint2012arXiv

Perturbation analysis of the matrix equation X - \sum_{i=1}^m A_i^* X^{p_i} A_i = Q

Consider the nonlinear matrix equation X-sum_{i=1}^{m}A_{i}^{*}X^{p_{i}}A_{i}=Q with p_{i}>0. Sufficient and necessary conditions for the existence of positive definite solutions to the equation with p_{i}>0 are derived. Two perturbation bounds for the unique solution to the equation with 0<p_{i}<1 are evaluated. The backward error of an approximate solution for the unique solution to the equation with 0<p_{i}<1 is given. Explicit expressions of the condition number for the equation with 0<p_{i}<1 are obtained. The theoretical results are illustrated by numerical examples.

preprint2012arXiv

Serrin-Type Blowup Criterion for Viscous, Compressible, and Heat Conducting Navier-Stokes and Magnetohydrodynamic Flows

This paper establishes a blowup criterion for the three-dimensional viscous, compressible, and heat conducting magnetohydrodynamic (MHD) flows. It is essentially shown that for the Cauchy problem and the initial-boundary-value one of the three-dimensional compressible MHD flows with initial density allowed to vanish, the strong or smooth solution exists globally if the density is bounded from above and the velocity satisfies the Serrin's condition. Therefore, if the Serrin norm of the velocity remains bounded, it is not possible for other kinds of singularities (such as vacuum states vanish or vacuum appears in the non-vacuum region or even milder singularities) to form before the density becomes unbounded. This criterion is analogous to the well-known Serrin's blowup criterion for the three-dimensional incompressible Navier-Stokes equations, in particular, it is independent of the temperature and magnetic field and is just the same as that of the barotropic compressible Navier-Stokes equations. As a direct application, it is shown that the same result also holds for the strong or smooth solutions to the three-dimensional full compressible Navier-Stokes system describing the motion of a viscous, compressible, and heat conducting fluid.

preprint2012arXiv

Solutions and improved perturbation analysis for the matrix equation X-A^{*}X^{-p}A=Q (p>0)

In this paper the nonlinear matrix equation X-A^{*}X^{-p}A=Q with p>0 is investigated. We consider two cases of this equation: the case p>1 and the case 0<p<1. In the case p>1, a new sufficient condition for the existence of a unique positive definite solution for the matrix equation is obtained. A perturbation estimate for the positive definite solution is derived. Explicit expressions of the condition number for the positive definite solution are given. In the case 0<p<1, a new sharper perturbation bound for the unique positive definite solution is evaluated. A new backward error of an approximate solution to the unique positive definite solution is obtained. The theoretical results are illustrated by numerical examples.

preprint2012arXiv

Solutions and perturbation analysis of the matrix equation X - \sum_{i=1}^m A_i^* X^{-1} A_i = Q

Consider the nonlinear matrix equation X-sum_{i=1}^{m}A_{i}^{*}X^{-1}A_{i}=Q. This paper shows that there exists a unique positive definite solution to the equation without any restriction on A_{i}. Three perturbation bounds for the unique solution to the equation are evaluated. A backward error of an approximate solution for the unique solution to the equation is derived. Explicit expressions of the condition number for the unique solution to the equation are obtained. The theoretical results are illustrated by numerical examples.

preprint2012arXiv

Stability and Hydrolyzation of Metal Organic Frameworks with Paddle-Wheel SBUs upon Hydration

Instability of most prototypical metal organic frameworks (MOFs) in the presence of moisture is always a limita- tion for industrial scale development. In this work, we examine the dissociation mechanism of microporous paddle wheel frameworks M(bdc)(ted)0.5 [M=Cu, Zn, Ni, Co; bdc= 1,4-benzenedicarboxylate; ted= triethylenediamine] in controlled humidity environments. Combined in-situ IR spectroscopy, Raman, and Powder x-ray diffraction measurements show that the stability and modification of isostructual M(bdc)(ted)0.5 compounds upon exposure to water vapor critically depend on the central metal ion. A hydrolysis reaction of water molecules with Cu-O-C is observed in the case of Cu(bdc)(ted)0.5. Displacement reactions of ted linkers by water molecules are identified with Zn(bdc)(ted)0.5 and Co(bdc)(ted)0.5. In contrast,. Ni(bdc)(ted)0.5 is less suscept- ible to reaction with water vapors than the other three compounds. In addition, the condensation of water vapors into the framework is necessary to initiate the dissociation reaction. These findings, supported by supported by first principles theoretical van der Waals density functional (vdW-DF) calculations of overall reaction enthalpies, provide the necessary information for de- termining operation conditions of this class of MOFs with paddle wheel secondary building units and guidance for developing more robust units.

preprint2012arXiv

The site conditions of the Guo Shou Jing Telescope

The weather at Xinglong Observing Station, where the Guo Shou Jing Telescope (GSJT) is located, is strongly affected by the monsoon climate in north-east China. The LAMOST survey strategy is constrained by these weather patterns. In this paper, we present a statistics on observing hours from 2004 to 2007, and the sky brightness, seeing, and sky transparency from 1995 to 2011 at the site. We investigate effects of the site conditions on the survey plan. Operable hours each month shows strong correlation with season: on average there are 8 operable hours per night available in December, but only 1-2 hours in July and August. The seeing and the sky transparency also vary with seasons. Although the seeing is worse in windy winters, and the atmospheric extinction is worse in the spring and summer, the site is adequate for the proposed scientific program of LAMOST survey. With a Monte Carlo simulation using historical data on the site condition, we find that the available observation hours constrain the survey footprint from 22h to 16h in right ascension; the sky brightness allows LAMOST to obtain the limit magnitude of V = 19.5mag with S/N = 10.

preprint2012arXiv

Tuning the Gate Opening Pressure of Metal Organic Frameworks (MOFs) for the Selective Separation of Hydro-carbons

Separation of hydrocarbons is one of the most energy demanding processes. The need to develop materials for the selective adsorption of hydrocarbons, under reasonable conditions, is therefore of paramount importance. This work unveils unexpected hydrocarbon selectivity in a flexible Metal Organic Framework (MOF), based on differences in their gate opening pressure. We show selectivity dependence on both chain length and specific framework-gas interaction. Combining Raman spectroscopy and theoretical van der Waals Density Functional (vdW-DF) calculations, the separation mechanisms governing this unexpected gate opening behavior are revealed.

preprint2011arXiv

Active Longitudes Revealed by Large-scale and Long-lived Coronal Streamers

We use time-series ultraviolet full sun images to construct limb-synoptic maps of the Sun. On these maps, large-scale, long-lived coronal streamers appear as repetitive sinusoid-like arcs projected over the polar regions. They are caused by high altitude plasma produced from sunspot-rich regions at latitudes generally far from the poles. The non-uniform longitudinal distribution of these reveals four longitudinal zones at the surface of the sun from which sunspots erupt preferentially over the 5-year observing interval (2006 January to 2011 April). Spots in these zones (or "clusters") have individual lifetimes short compared to the lifetimes of the coronal features which they sustain, and erupt at different times. The four sunspot clusters contain >75% of all numbered sunspots in this period. They occupy two distinct longitudinal zones separated by ~180 degree and each spanning ~100 degree in longitude. The rotation rates of the spot clusters are ~5% faster than the rates at both the surface and the bottom of the convection zone. While no convincing theoretical framework exists to interpret the sunspot clusters in the longitude-time space, their persistent and nonuniform distribution indicates long-lived, azimuthal structures beneath the surface, and are compatible with the existence of previously-reported active longitudes on the sun.

preprint2011arXiv

Field-induced negative differential spin lifetime in silicon

We show that the electric field-induced thermal asymmetry between the electron and lattice systems in pure silicon substantially impacts the identity of the dominant spin relaxation mechanism. Comparison of empirical results from long-distance spin transport devices with detailed Monte-Carlo simulations confirms a strong spin depolarization beyond what is expected from the standard Elliott-Yafet theory already at low temperatures. The enhanced spin-flip mechanism is attributed to phonon emission processes during which electrons are scattered between conduction band valleys that reside on different crystal axes. This leads to anomalous behavior, where (beyond a critical field) reduction of the transit time between spin-injector and spin-detector is accompanied by a counterintuitive reduction in spin polarization and an apparent negative spin lifetime.

preprint2011arXiv

Global Classical and Weak Solutions to the Three-Dimensional Full Compressible Navier-Stokes System with Vacuum and Large Oscillations

We establish the global existence and uniqueness of classical solutions to the three-dimensional full compressible Navier-Stokes system with smooth initial data which are of small energy but possibly large oscillations where the initial density is allowed to vanish. Moreover, for the initial data which may be discontinuous and contain vacuum states, we also obtain the global existence of weak solutions. These results generalize previous ones on classical and weak solutions for initial density being strictly away from vacuum, and are the first for global classical and weak solutions which may have large oscillations and can contain vacuum states.

preprint2011arXiv

Mobile Wireless Localization through Cooperation

This paper considers N mobile nodes that move together in the vicinity of each other, whose initial poses as well as subsequent movements must be accurately tracked in real time with the assist of M(>=3) reference nodes. By engaging the neighboring mobile nodes in a simple but effective cooperation, and by exploiting both the time-of-arrival (TOA) information (between mobile nodes and reference nodes) and the received-signal-strength (RSS) information (between mobile nodes), an effective new localization strategy, termed cooperative TOA and RSS (COTAR), is developed. An optimal maximum likelihood detector is first formulated, followed by the derivation of a low-complexity iterative approach that can practically achieve the Cramer-Rao lower bound. Instead of using simplified channel models as in many previous studies, a sophisticated and realistic channel model is used, which can effectively account for the critical fact that the direct path is not necessarily the strongest path. Extensive simulations are conducted in static and mobile settings, and various practical issues and system parameters are evaluated. It is shown that COTAR significantly outperforms the existing strategies, achieving a localization accuracy of only a few tenths of a meter in clear environments and a couple of meters in heavily obstructed environments.

preprint2011arXiv

Modeling spin transport in electrostatically-gated lateral-channel silicon devices: role of interfacial spin relaxation

Using a two-dimensional finite-differences scheme to model spin transport in silicon devices with lateral geometry, we simulate the effects of spin relaxation at interfacial boundaries, i.e. the exposed top surface and at an electrostatically-controlled backgate with SiO_2 dielectric. These gate-voltage-dependent simulations are compared to previous experimental results and show that strong spin relaxation due to extrinsic effects yield an Si/SiO_2 interfacial spin lifetime of ~ 1ns, orders of magnitude lower than lifetimes in the bulk Si, whereas relaxation at the top surface plays no substantial role. Hall effect measurements on ballistically injected electrons gated in the transport channel yield the carrier mobility directly and suggest that this reduction in spin lifetime is only partially due to enhanced interfacial momentum scattering which induces random spin flips as in the Elliott effect. Therefore, other extrinsic mechanisms such as those caused by paramagnetic defects should also be considered in order to explain the dramatic enhancement in spin relaxation at the gate interface over bulk values.

preprint2011arXiv

Network Localization on Unit Disk Graphs

We study the problem of cooperative localization of a large network of nodes in integer-coordinated unit disk graphs, a simplified but useful version of general random graph. Exploiting the property that the radius $r$ sets clear cut on the connectivity of two nodes, we propose an essential philosophy that "no connectivity is also useful information just like the information being connected" in unit disk graphs. Exercising this philosophy, we show that the conventional network localization problem can be re-formulated to significantly reduce the search space, and that global rigidity, a necessary and sufficient condition for the existence of unique solution in general graphs, is no longer necessary. While the problem is still NP-hard, we show that a (depth-first) tree-search algorithm with memory O(N) ($N$ is the network size) can be developed, and for practical setups, the search complexity and speed is very manageable, and is magnitudes less than the conventional problem, especially when the graph is sparse or when only very limited anchor nodes are available.

preprint2011arXiv

On the maximal energy tree with two maximum degree vertices

For a simple graph $G$, the energy $E(G)$ is defined as the sum of the absolute values of all eigenvalues of its adjacent matrix. For $Δ\geq 3$ and $t\geq 3$, denote by $T_a(Δ,t)$ (or simply $T_a$) the tree formed from a path $P_t$ on $t$ vertices by attaching $Δ-1$ $P_2$'s on each end of the path $P_t$, and $T_b(Δ, t)$ (or simply $T_b$) the tree formed from $P_{t+2}$ by attaching $Δ-1$ $P_2$'s on an end of the $P_{t+2}$ and $Δ-2$ $P_2$'s on the vertex next to the end. In [X. Li, X. Yao, J. Zhang and I. Gutman, Maximum energy trees with two maximum degree vertices, J. Math. Chem. 45(2009), 962--973], Li et al. proved that among trees of order $n$ with two vertices of maximum degree $Δ$, the maximal energy tree is either the graph $T_a$ or the graph $T_b$, where $t=n+4-4Δ\geq 3$. However, they could not determine which one of $T_a$ and $T_b$ is the maximal energy tree. This is because the quasi-order method is invalid for comparing their energies. In this paper, we use a new method to determine the maximal energy tree. It turns out that things are more complicated. We prove that the maximal energy tree is $T_b$ for $Δ\geq 7$ and any $t\geq 3$, while the maximal energy tree is $T_a$ for $Δ=3$ and any $t\geq 3$. Moreover, for $Δ=4$, the maximal energy tree is $T_a$ for all $t\geq 3$ but $t=4$, for which $T_b$ is the maximal energy tree. For $Δ=5$, the maximal energy tree is $T_b$ for all $t\geq 3$ but $t$ is odd and $3\leq t\leq 89$, for which $T_a$ is the maximal energy tree. For $Δ=6$, the maximal energy tree is $T_b$ for all $t\geq 3$ but $t=3,5,7$, for which $T_a$ is the maximal energy tree. One can see that for most $Δ$, $T_b$ is the maximal energy tree, $Δ=5$ is a turning point, and $Δ=3$ and 4 are exceptional cases.

preprint2011arXiv

On the motion of three-dimensional compressible isentropic flows with large external potential forces and vacuum

We study the global existence and uniqueness of classical solutions to the three-dimensional compressible isentropic Navier-Stokes equations with vacuum and external potential forces which could be arbitrarily large provided the initial data is of small energy and the unique steady state is strictly away from vacuum. In particular, the solution may have large oscillations and contain vacuum states. For the case of discontinuous initial data, we also prove the global existence of weak solutions. The large-time behavior of the solution is obtained simultaneously. It is worthwhile mentioning that the compatibility condition on the initial data and the regularity condition of the external potential forces in the present paper are much weaker than those assumed in the existing literature.

preprint2011arXiv

Pre-Discovery Observations of Disrupting Asteroid P/2010 A2

Solar system object P/2010 A2 is the first-noticed example of the aftermath of a recently disrupted asteroid, probably resulting from a collision. Nearly a year elapsed between its inferred initiation in early 2009 and its eventual detection in early 2010. Here, we use new observations to assess the factors underlying the visibility, especially to understand the delayed discovery. We present prediscovery observations from the LINEAR telescope and set limits to the early-time brightness from SOHO and STEREO satellite coronagraphic images. Consideration of the circumstances of discovery of P/2010 A2 suggests that similar objects must be common, and that future all-sky surveys will reveal them in large numbers.

preprint2011arXiv

Spin-Polarized Transient Electron Trapping in Phosphorus-doped Silicon

Experimental evidence of electron spin precession during travel through the phosphorus-doped Si channel of an all-electrical device simultaneously indicates two distinct processes: (i) short timescales (~50ps) due to purely conduction-band transport from injector to detector, and (ii) long timescales (~1ns) originating from delays associated with capture/re-emission in shallow impurity traps. The origin of this phenomenon, examined via temperature, voltage, and electron density dependence measurements, is established by means of comparison to a numerical model and is shown to reveal the participation of metastable excited states in the phosphorus impurity spectrum. This work therefore demonstrates the potential to make the study of macroscopic spin transport relevant to the quantum regime of individual spin interactions with impurities as envisioned for quantum information applications.

preprint2010arXiv

Activity in Geminid Parent (3200) Phaethon

The asteroid (3200) Phaethon is widely recognized as the parent of the Geminid meteoroid stream. However, it has never shown evidence for on-going mass loss or for any form of comet-like activity that would indicate the continued replenishment of the stream. Following an alert by Battams and Watson (2009), we used NASA's STEREO-A spacecraft to image Phaethon near perihelion, in the period UT 2009 June 17 - 22, when the heliocentric distance was near 0.14 AU. The resulting photometry shows an unexpected brightening, by a factor of two, starting UT 2009 June 20.2+/-0.2, which we interpret as an impulsive release of dust particles from Phaethon. If the density is near 2500 kg/m^3, then the emitted dust particles must have a combined mass of ~2.5x10^8 a1 kg, where a1 is the particle radius in millimeters. Assuming a1 = 1, this is approximately 10^-4 of the Geminid stream mass and to replenish the stream in steady-state within its estimated ~1000 yr lifetime would require ~10 events like the one observed, per orbit. Alternatively, on-going mass loss may be unrelated to the event which produced the Phaethon-Geminid complex. An impact origin of the dust is highly unlikely. Phaethon is too hot for water ice to survive, rendering unlikely the possibility that dust is ejected through gas-drag from sublimated ice. Instead, we suggest that Phaethon is essentially a rock comet, in which the small perihelion distance leads both to the production of dust (through thermal fracture and decomposition-cracking of hydrated minerals) and to its ejection into interplanetary space (through radiation pressure sweeping and other effects).

preprint2010arXiv

Blowup Criterion for the Compressible Flows with Vacuum States

We prove that the maximum norm of the deformation tensor of velocity gradients controls the possible breakdown of smooth(strong) solutions for the 3-dimensional compressible Navier-Stokes equations, which will happen, for example, if the initial density is compactly supported \cite{X1}. More precisely, if a solution of the compressible Navier-Stokes equations is initially regular and loses its regularity at some later time, then the loss of regularity implies the growth without bound of the deformation tensor as the critical time approaches. Our result is the same as Ponce's criterion for 3-dimensional incompressible Euler equations (\cite{po}). Moreover, our method can be generalized to the full Compressible Navier-Stokes system which improve the previous results. In addition, initial vacuum states are allowed in our cases.

preprint2010arXiv

Composition-Diamond Lemma for Non-associative Algebras over a Commutative Algebra

We establish the Composition-Diamond lemma for non-associative algebras over a free commutative algebra. As an application, we prove that every countably generated non-associative algebra over an arbitrary commutative algebra $K$ can be embedded into a two-generated non-associative algebra over $K$.

preprint2010arXiv

Efficient ML Decoding for Quantum Convolutional Codes

A novel decoding algorithm is developed for general quantum convolutional codes. Exploiting useful ideas from classical coding theory, the new decoder introduces two innovations that drastically reduce the decoding complexity compared to the existing quantum Viterbi decoder. First, the new decoder uses an efficient linear-circuits-based mechanism to map a syndrome to a candidate vector, whereas the existing algorithm relies on a non-trivial lookup table. Second, the new algorithm is cleverly engineered such that only one run of the Viterbi algorithm suffices to locate the most-likely error pattern, whereas the existing algorithm must run the Viterbi algorithm many times. The efficiency of the proposed algorithm allows us to simulate and present the first performance curve of a general quantum convolutional code.

preprint2010arXiv

Generalized Adaptive Network Coded Cooperation (GANCC): A Unified Framework for Network Coding and Channel Coding

This paper considers distributed coding for multi-source single-sink data collection wireless networks. A unified framework for network coding and channel coding, termed "generalized adaptive network coded cooperation" (GANCC), is proposed. Key ingredients of GANCC include: matching code graphs with the dynamic network graphs on-the-fly, and integrating channel coding with network coding through circulant low-density parity-check codes. Several code constructing methods and several families of sparse-graph codes are proposed, and information theoretical analysis is performed. It is shown that GANCC is simple to operate, adaptive in real time, distributed in nature, and capable of providing remarkable coding gains even with a very limited number of cooperating users.

preprint2010arXiv

Global Well-Posedness of Classical Solutions with Large Oscillations and Vacuum to the Three-Dimensional Isentropic Compressible Navier-Stokes Equations

We establish the global existence and uniqueness of classical solutions to the Cauchy problem for the isentropic compressible Navier-Stokes equations in three spatial dimensions with smooth initial data which are of small energy but possibly large oscillations with constant state as far field which could be either vacuum or non-vacuum. The initial density is allowed to vanish and the spatial measure of the set of vacuum can be arbitrarily large, in particular, the initial density can even have compact support. These results generalize previous results on classical solutions for initial densities being strictly away from vacuum, and are the first for global classical solutions which may have large oscillations and can contain vacuum states.

preprint2010arXiv

Outburst of Comet 17P/Holmes Observed With The Solar Mass Ejection Imager

We present time-resolved photometric observations of Jupiter family comet 17P/Holmes during its dramatic outburst of 2007. The observations, from the orbiting Solar Mass Ejection Imager (SMEI), provide the most complete measure of the whole-coma brightness, free from the effects of instrumental saturation and with a time-resolution well-matched to the rapid brightening of the comet. The lightcurve is divided into two distinct parts. A rapid rise between the first SMEI observation on UT 2007 October 24 06h 37m (mid-integration) and UT 2007 October 25, is followed by a slow decline until the last SMEI observation on UT 2008 April 6 22h 16m (mid-integration). We find that the rate of change of the brightness is reasonably well-described by a Gaussian function having a central time of UT 2007 October 24.54+/-0.01 and a full-width-at-half-maximum 0.44+/-0.02 days. The maximum rate of brightening occurs some 1.2 days after the onset of activity. At the peak the scattering cross-section grows at 1070+/-40 km^2/s while the (model-dependent) mass loss rates inferred from the lightcurve reach a maximum at 3+/-10^5 kg/s. The integrated mass in the coma lies in the range (2 to 90)x10^10 kg, corresponding to 0.2% to 10% of the nucleus mass, while the kinetic energy of the ejecta is (0.6 to 30) MTonnes TNT. The particulate coma mass could be contained within a shell on the nucleus of thickness ~1.5 to 60 m. This is comparable to the distance traveled by conducted heat in the century since the previous outburst of 17P/Holmes. This coincidence is consistent with, but does not prove, the idea that the outburst was triggered by the action of conducted heat, possibly through the crystallization of buried amorphous ice.

preprint2010arXiv

Serrin Type Criterion for the Three-Dimensional Viscous Compressible Flows

We extend the well-known Serrin's blowup criterion for the three-dimensional (3D) incompressible Navier-Stokes equations to the 3D viscous compressible cases. It is shown that for the Cauchy problem of the 3D compressible Navier-Stokes system in the whole space, the strong or smooth solution exists globally if the velocity satisfies the Serrin's condition and either the supernorm of the density or the $L^1(0,T;L^\infty)$-norm of the divergence of the velocity is bounded. Furthermore, in the case that either the shear viscosity coefficient is suitably large or there is no vacuum, the Serrin's condition on the velocity can be removed in this criteria.

preprint2009arXiv

Modeling spin transport with current-sensing spin detectors

By incorporating the proper boundary conditions, we analytically derive the impulse response (or "Green's function") of a current-sensing spin detector. We also compare this result to a Monte-Carlo simulation (which automatically takes the proper boundary condition into account) and an empirical spin transit time distribution obtained from experimental spin precession measurements. In the strong drift-dominated transport regime, this spin current impulse response can be approximated by multiplying the spin density impulse response by the average drift velocity. However, in weak drift fields, large modeling errors up to a factor of 3 in most-probable spin transit time can be incurred unless the full spin current Green's function is used.

preprint2008arXiv

The role of particle interactions in a many-body model of Feshbach molecular formation in bosonic systems

In this paper, we investigate the atom-molecule conversion dynamics of a generalized many-body model that includes the atom-atom, atom-molecule, and molecule-molecule interactions, emphasizing the efficiency of the Feshbach molecular formation. We show that the picture of two-body molecular production depicted by the Landau-Zener model is significantly altered: The energy levels are dramatically distorted and the conversion efficiency is suppressed by the particle interactions. According to the rule of constant action and with the help of phase-space analysis, we derive an analytical expression for the conversion efficiency in the adiabatic limit. It shows a ceiling for the conversion efficiency when the interaction strength is larger than a critical value. We further derive a closed equation for the conversion efficiency with the stationary phase approximation. In the sudden limit, the conversion efficiency is twice that predicted by the two-body Landau-Zener formula. Our analytical formula has been confirmed by numerical calculations.

preprint2008arXiv

Vector Magnetic Fields and Electric Currents from the Imaging Vector Magnetograph

First, we describe a general procedure to produce high quality vector magnetograms using the Imaging Vector Magnetograph (IVM) at Mees Solar Observatory. At the spatial resolution 2"x2", the Stokes Q,U,V uncertainty reaches 0.001-0.0005 in time-averaged data over 1-hour in the quiet Sun. When vector magnetic fields are inferred from the time-averaged Stokes spectral images of FeI 6302.5A, the resulting uncertainties are on the order of 10 G for the longitudinal fields, 40 G for the transverse field strength and 9 degree for the magnetic azimuth. The magnetic field inversion used in this work is the "Triplet" code, which was developed and implemented in the IVM software package by the late Barry J. LaBonte. The inversion code is described in detail in the Appendix. Second, we solve for the absolute value of the vertical electric current density, |Jz|, accounting for the above IVM problems, for two different active regions. One is a single sunspot region (NOAA 10001 observed on 20 June 2002) while the other is a more complex, quadrupolar region (NOAA10030 observed on 15 July 2002). We use a calculation that does not require disambiguation of 180 degree in the transverse field directions. The |Jz| uncertainty is on the order of 7.0 mA m^-2. The vertical current density increases with increasing vertical magnetic field. The rate of increase is about 1 -2 times as large in the quadrupolar NOAA 10030 region as in the simple NOAA 10001, and it is more spatially variable over NOAA 10030 than over NOAA 10001.

preprint1996arXiv

The Milky Way, The Local Galaxies \& the IR Tully-Fisher Relation

Using the near infrared fluxes of local galaxies derived from COBE/DIRBE J(1.25 $μ$m) K (2.2 $μ$m) \& L (3.5 $μ$m) band maps and published Cepheid distances, we construct Tully-Fisher (TF) diagrams for the nearby galaxies. The measured dispersions in these luminosity-linewidth diagrams are remarkably small: $σ_J = 0.09$ magnitudes, $σ_K = 0.13$ magnitudes, and $σ_L = 0.20$ magnitudes. For the J and K bands, Monte Carlo simulations give a 95\% confidence interval upper limit on the true scatter in the T-F diagram of $σ_J \le 0.35$ and $σ_K \le 0.45$. We determine Milky Way's luminosity and place it in the T-F diagram by fitting a bar plus ``standard'' values of its size and circular speed (Sun-Galactic center distance $R_0 = 8.5 \kpc$ and $Θ_0 =220 \kms$), the Milky Way lies within $1.5 σ$ of the TF relations. We can use the TF relation and the Cepheid distances to nearby bright galaxies to constrain $R_0$ and $Θ_0$. Alternatively, we can fix the parameters of the Galaxy to their standard values, ignore the Cepheid zero-point, and use the Tully-Fisher relation to determine the Hubble Constant directly: $H_0 = 66 \pm 12$ km/s/Mpc.

Jing Li

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198 published item(s)

Personalizing LLMs with Binary Feedback: A Preference-Corrected Optimization Framework

PPU-Bench:Real World Benchmark for Personalized Partial Unlearning in Vision Language Models

Team-Based Self-Play With Dual Adaptive Weighting for Fine-Tuning LLMs

Physical properties and first-principles calculations of an altermagnet candidate Cs$_{1-δ}$V$_2$Te$_2$O

Distinguishing the Topological Charge of Vortex Beam via Fourier Back Plane Imaging with Chiral Gammadion Structure

Audio2Gestures: Generating Diverse Gestures from Audio

Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm

A Blind All-sky Search for Star Clusters in Gaia EDR3: 886 Clusters within 1.2 kpc of the Sun

A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict

A Knowledge Distillation-Based Backdoor Attack in Federated Learning

A Multi-Behavior Planning Framework for Robot Guide

A physical perturbation based study on the prediction of free-fall disks with chaotic modes in the water

Absorbance Enhancement of Monolayer MoS$_2$ in a Perfect Absorbing System

Adversarial Attacks and Defense Methods for Power Quality Recognition

An Efficient Coarse-to-Fine Facet-Aware Unsupervised Summarization Framework based on Semantic Blocks

An inverse random source problem for the Helium production-diffusion equation driven by a fractional Brownian motion

Analyzing the Intensity of Complaints on Social Media

Attention-based Multimodal Feature Representation Model for Micro-video Recommendation

Continuous Sign Language Recognition via Temporal Super-Resolution Network

Critiquing-based Modeling of Subjective Preferences

Cross-domain Trajectory Prediction with CTP-Net

Decoupled IoU Regression for Object Detection

Designer magnetic topological graphene nanoribbons

Discovery of extended structure around open cluster COIN-Gaia 13 based on Gaia EDR3

Doctor Recommendation in Online Health Forums via Expertise Learning

Domain Invariant Model with Graph Convolutional Network for Mammogram Classification

Estimating accurate reddening values of LAMOST M dwarfs

Fermi Observations of GRB 220426A: a burst similar to GRB 090902B

Global Classical Solutions to the Full Compressible Navier-Stokes System in 3D Exterior Domains

Global Existence of Classical Solutions to Full Compressible Navier-Stokes System with Large Oscillations and Vacuum in 3D Bounded Domains

Hubble Space Telescope Observations of Active Asteroid P/2020 O1 (Lemmon-PANSTARRS)

Many-body exciton and inter-valley correlations in heavily electron-doped WSe$_2$ monolayers

Mobility Support for Millimeter Wave Communications: Opportunities and Challenges

Multi-scale temporal network for continuous sign language recognition

On genuine entanglement for tripartite systems

p-orbital disclination states in non-Euclidean geometries

Pasta phases in neutron stars under strong magnetic fields

Performance evaluation of baseline-dependent averaging based onfull-scale SKA1-LOW simulation

Quantum control and quantum speed limits in supersymmetric potentials

Recognition of Handwritten Chinese Text by Segmentation: A Segment-annotation-free Approach

Rethinking Attention-Model Explainability through Faithfulness Violation Test

Saliency in Augmented Reality

Searching Extra-tidal Features around the Globular Cluster Whiting 1

Single-stage Rotate Object Detector via Two Points with Solar Corona Heatmap

SPTS: Single-Point Text Spotting

Successful New-entry Prediction for Multi-Party Online Conversations via Latent Topics and Discourse Modeling

Testing the seesaw mechanisms via displaced right-handed neutrinos from a light scalar at the HL-LHC

Topological equivalence canonical forms for linear multivariable systems without control

TVShowGuess: Character Comprehension in Stories as Speaker Guessing

Accurate predictions of chaotic motion of a free fall disk

Global Existence of Strong and Weak Solutions to 2D Compressible Navier-Stokes System in Bounded Domains with Large Data and Vacuum

Hydrogen molecule spectrum by many-body GW and Bethe-Salpeter equation

Mimicing the Kane-Mele type spin orbit interaction by spin-flexual phonon coupling in graphene devices

Minority Oversampling for Imbalanced Time Series Classification

Quantum Gaussian process regression

Reducibility of relativistic Schrödinger equation with unbounded perturbations

Spatial Curvature and Large Scale Lorentz Violation

A Feshbach engine in the Thomas-Fermi regime

A Resource Allocation and Coordinated Transmission Scheme for Large Cellular Networks

An Attention Based Neural Network for Jet Tagging

Charge detection in an array of CMOS quantum dots

Constructive and Destructive Interference of Kerker-type Scattering in an Ultra-thin Silicon Huygens Metasurface

Continuous-Time Analysis of the Bitcoin and Prism Backbone Protocols

Double spin asymmetry in dihadron production in SIDIS off the longitudinally polarized nucleon target

Effects of coherence on quantum speed limits and shortcuts to adiabaticity in many-particle systems

Efficient implementation of immersed boundary-lattice Boltzmann method for massive particle-laden flows Part I: Serial computing

Fairness Constraints in Semi-supervised Learning

GPM: A Generic Probabilistic Model to Recover Annotator's Behavior and Ground Truth Labeling

GRB 140423A: A Case of Stellar Wind to Interstellar Medium Transition in the Afterglow

Ground-state correlation energy of beryllium dimer by the Bethe-Salpeter equation

High-order numerical methods for the Riesz space fractional advection-dispersion equations

Hole-phonon interactions in quantum dots: Effects of phonon confinement and encapsulation materials on spin-orbit qubits

Hubble Space Telescope Search for Activity in High Perihelion Objects

Large Batch Optimization for Deep Learning: Training BERT in 76 minutes