BZPEERPapers, people, evidence and research paths
Menu

Discover

SearchFind papers, people, topics, institutions and opportunities from one place.GraphSee how papers, authors, topics and evidence connect.

Research tools

HomeContinue from the papers, people and topics that matter now.CollectionsTurn saved papers into reading lists, evidence maps and shareable context.ResearchReconstruct the path that led you from search to paper to question.CollaborationMove from a paper, topic or expert request into a focused thread.PublishCreate full-text research articles with metadata, formulas and versions.

Network

ExpertsFind specialists whose work and reviews explain why they can help.CommunitiesJoin research groups organized around papers, topics and shared evidence.

Opportunities

ListingsBrowse roles, calls and collaborations connected to real research context.

Account

Log inReturn to your saved papers, graph views and active threads.Create accountStart saving papers, building a research trail and joining teams.
Log inCreate account

Source author record

Dong Xu

Dong Xu appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

ResearcherUnclaimed source record
astro-ph.HEComputer Visionastro-ph.COMachine Learningastro-ph.SRhep-phhep-exeess.IVArtificial Intelligenceeess.SYSoftware EngineeringSystems and ControlApplicationsastro-ph.GAastro-ph.IMComputation and LanguageComputer Science and Game Theorycond-mat.mes-halleess.SPgr-qcNeural and Evolutionary ComputingNumerical Analysis

Catalog footprint

What is connected

49works
22topics
4close collaborators

Actions

Connect this record

Log in to claim
Open graphBrowse works

Research graph

See the researcher in context

Open full explorer

Inspect adjacent papers, topics, institutions and collaborators without losing the researcher page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Published work

49 published item(s)

preprint2026arXiv

LiveFMBench: Unveiling the Power and Limits of Agentic Workflows in Specification Generation

Formal specification is essential for rigorous program verification, yet writing correct specifications remains costly and difficult to automate. Although large language models (LLMs) and agents have shown promising progress, their true capabilities and failure modes remain unclear. We present the first systematic and contamination-aware study of LLM- and agent-based formal specification generation for C programs. We introduce LiveFMBench, a continuously evolving benchmark of 630 ACSL (ANSI/ISO C Specification Language)-annotated C programs, including 360 newly collected cases designed to mitigate data leakage. Using this benchmark, we evaluate direct prompting with different sampling sizes, reasoning-enabled (thinking mode) inference, the agentic pipeline, and perform a fine-grained failure analysis. Experimental results reveal that naive evaluation substantially overestimates performance because models under direct prompting may exhibit unfaithful behaviors, such as deceiving automated provers or ignoring code-context constraints; after excluding such cases, the true specification generation accuracy drops by approximately 20\%. We further find that both increased sampling and thinking mode significantly improve success rates, with smaller models benefiting more from thinking mode. Agentic pipelines are particularly effective under low sampling budgets and on harder datasets. Failure analysis further shows that incorrect loop invariants are the dominant error type, while agentic pipelines notably reduce assertion errors. These results expose fundamental limitations in current LLM-based approaches and suggest they remain far from replacing human-authored formal specifications. We release LiveFMBench at https://huggingface.co/datasets/fm-universe/Live-FM-Bench and all evaluation artifacts to support future research.

0 citations0 reviewsNo code linkedOpen access
preprint2024arXiv

Inversion-by-Inversion: Exemplar-based Sketch-to-Photo Synthesis via Stochastic Differential Equations without Training

Exemplar-based sketch-to-photo synthesis allows users to generate photo-realistic images based on sketches. Recently, diffusion-based methods have achieved impressive performance on image generation tasks, enabling highly-flexible control through text-driven generation or energy functions. However, generating photo-realistic images with color and texture from sketch images remains challenging for diffusion models. Sketches typically consist of only a few strokes, with most regions left blank, making it difficult for diffusion-based methods to produce photo-realistic images. In this work, we propose a two-stage method named ``Inversion-by-Inversion" for exemplar-based sketch-to-photo synthesis. This approach includes shape-enhancing inversion and full-control inversion. During the shape-enhancing inversion process, an uncolored photo is generated with the guidance of a shape-energy function. This step is essential to ensure control over the shape of the generated photo. In the full-control inversion process, we propose an appearance-energy function to control the color and texture of the final generated photo.Importantly, our Inversion-by-Inversion pipeline is training-free and can accept different types of exemplars for color and texture control. We conducted extensive experiments to evaluate our proposed method, and the results demonstrate its effectiveness. The code and project can be found at https://ximinng.github.io/inversion-by-inversion-project/.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

Multi-modality Affinity Inference for Weakly Supervised 3D Semantic Segmentation

3D point cloud semantic segmentation has a wide range of applications. Recently, weakly supervised point cloud segmentation methods have been proposed, aiming to alleviate the expensive and laborious manual annotation process by leveraging scene-level labels. However, these methods have not effectively exploited the rich geometric information (such as shape and scale) and appearance information (such as color and texture) present in RGB-D scans. Furthermore, current approaches fail to fully leverage the point affinity that can be inferred from the feature extraction network, which is crucial for learning from weak scene-level labels. Additionally, previous work overlooks the detrimental effects of the long-tailed distribution of point cloud data in weakly supervised 3D semantic segmentation. To this end, this paper proposes a simple yet effective scene-level weakly supervised point cloud segmentation method with a newly introduced multi-modality point affinity inference module. The point affinity proposed in this paper is characterized by features from multiple modalities (e.g., point cloud and RGB), and is further refined by normalizing the classifier weights to alleviate the detrimental effects of long-tailed distribution without the need of the prior of category distribution. Extensive experiments on the ScanNet and S3DIS benchmarks verify the effectiveness of our proposed method, which outperforms the state-of-the-art by ~4% to ~6% mIoU. Codes are released at https://github.com/Sunny599/AAAI24-3DWSSG-MMA.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Coarse-to-fine Deep Video Coding with Hyperprior-guided Mode Prediction

The previous deep video compression approaches only use the single scale motion compensation strategy and rarely adopt the mode prediction technique from the traditional standards like H.264/H.265 for both motion and residual compression. In this work, we first propose a coarse-to-fine (C2F) deep video compression framework for better motion compensation, in which we perform motion estimation, compression and compensation twice in a coarse to fine manner. Our C2F framework can achieve better motion compensation results without significantly increasing bit costs. Observing hyperprior information (i.e., the mean and variance values) from the hyperprior networks contains discriminant statistical information of different patches, we also propose two efficient hyperprior-guided mode prediction methods. Specifically, using hyperprior information as the input, we propose two mode prediction networks to respectively predict the optimal block resolutions for better motion coding and decide whether to skip residual information from each block for better residual coding without introducing additional bit cost while bringing negligible extra computation cost. Comprehensive experimental results demonstrate our proposed C2F video compression framework equipped with the new hyperprior-guided mode prediction methods achieves the state-of-the-art performance on HEVC, UVG and MCL-JCV datasets.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Improving RGB-D Point Cloud Registration by Learning Multi-scale Local Linear Transformation

Point cloud registration aims at estimating the geometric transformation between two point cloud scans, in which point-wise correspondence estimation is the key to its success. In addition to previous methods that seek correspondences by hand-crafted or learnt geometric features, recent point cloud registration methods have tried to apply RGB-D data to achieve more accurate correspondence. However, it is not trivial to effectively fuse the geometric and visual information from these two distinctive modalities, especially for the registration problem. In this work, we propose a new Geometry-Aware Visual Feature Extractor (GAVE) that employs multi-scale local linear transformation to progressively fuse these two modalities, where the geometric features from the depth data act as the geometry-dependent convolution kernels to transform the visual features from the RGB data. The resultant visual-geometric features are in canonical feature spaces with alleviated visual dissimilarity caused by geometric changes, by which more reliable correspondence can be achieved. The proposed GAVE module can be readily plugged into recent RGB-D point cloud registration framework. Extensive experiments on 3D Match and ScanNet demonstrate that our method outperforms the state-of-the-art point cloud registration methods even without correspondence or pose supervision. The code is available at: https://github.com/514DNA/LLT.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Perturbative benchmark models for a dark shower search program

We provide five benchmark hidden valley models with perturbative parton showers, which span a wide range of dark shower phenomenology. We consider production through an $s$-channel, heavy mediator, which can be identified with the SM Higgs. By assuming a set of well-motivated decay portals, one can moreover fix both the branching ratios of the dark mesons and set a lower bound on their lifetime. We provide a public python tool which can be used to generate self-consistent PYTHIA 8 cards for our benchmark models.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Revisiting Deep Semi-supervised Learning: An Empirical Distribution Alignment Framework and Its Generalization Bound

In this work, we revisit the semi-supervised learning (SSL) problem from a new perspective of explicitly reducing empirical distribution mismatch between labeled and unlabeled samples. Benefited from this new perspective, we first propose a new deep semi-supervised learning framework called Semi-supervised Learning by Empirical Distribution Alignment (SLEDA), in which existing technologies from the domain adaptation community can be readily used to address the semi-supervised learning problem through reducing the empirical distribution distance between labeled and unlabeled data. Based on this framework, we also develop a new theoretical generalization bound for the research community to better understand the semi-supervised learning problem, in which we show the generalization error of semi-supervised learning can be effectively bounded by minimizing the training error on labeled data and the empirical distribution distance between labeled and unlabeled data. Building upon our new framework and the theoretical bound, we develop a simple and effective deep semi-supervised learning method called Augmented Distribution Alignment Network (ADA-Net) by simultaneously adopting the well-established adversarial training strategy from the domain adaptation community and a simple sample interpolation strategy for data augmentation. Additionally, we incorporate both strategies in our ADA-Net into two exiting SSL methods to further improve their generalization capability, which indicates that our new framework provides a complementary solution for solving the SSL problem. Our comprehensive experimental results on two benchmark datasets SVHN and CIFAR-10 for the semi-supervised image recognition task and another two benchmark datasets ModelNet40 and ShapeNet55 for the semi-supervised point cloud recognition task demonstrate the effectiveness of our proposed framework for SSL.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Salient Object Detection via Integrity Learning

Although current salient object detection (SOD) works have achieved significant progress, they are limited when it comes to the integrity of the predicted salient regions. We define the concept of integrity at both a micro and macro level. Specifically, at the micro level, the model should highlight all parts that belong to a certain salient object. Meanwhile, at the macro level, the model needs to discover all salient objects in a given image. To facilitate integrity learning for SOD, we design a novel Integrity Cognition Network (ICON), which explores three important components for learning strong integrity features. 1) Unlike existing models, which focus more on feature discriminability, we introduce a diverse feature aggregation (DFA) component to aggregate features with various receptive fields (i.e., kernel shape and context) and increase feature diversity. Such diversity is the foundation for mining the integral salient objects. 2) Based on the DFA features, we introduce an integrity channel enhancement (ICE) component with the goal of enhancing feature channels that highlight the integral salient objects, while suppressing the other distracting ones. 3) After extracting the enhanced features, the part-whole verification (PWV) method is employed to determine whether the part and whole object features have strong agreement. Such part-whole agreements can further improve the micro-level integrity for each salient object. To demonstrate the effectiveness of our ICON, comprehensive experiments are conducted on seven challenging benchmarks. Our ICON outperforms the baseline methods in terms of a wide range of metrics. Notably, our ICON achieves about 10% relative improvement over the previous best model in terms of average false negative ratio (FNR), on six datasets. Codes and results are available at: https://github.com/mczhuge/ICON.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

A Hybrid Simulation-based Duopoly Game Framework for Analysis of Supply Chain and Marketing Activities

A hybrid simulation-based framework involving system dynamics and agent-based simulation is proposed to address duopoly game considering multiple strategic decision variables and rich payoff, which cannot be addressed by traditional approaches involving closed-form equations. While system dynamics models are used to represent integrated production, logistics, and pricing determination activities of duopoly companies, agent-based simulation is used to mimic enhanced consumer purchasing behavior considering advertisement, promotion effect, and acquaintance recommendation in the consumer social network. The payoff function of the duopoly companies is assumed to be the net profit based on the total revenue and various cost items such as raw material, production, transportation, inventory and backorder. A unique procedure is proposed to solve and analyze the proposed simulation-based game, where the procedural components include strategy refinement, data sampling, gaming solving, and performance evaluation. First, design of experiment and estimated conformational value of information techniques are employed for strategy refinement and data sampling, respectively. Game solving then focuses on pure strategy equilibriums, and performance evaluation addresses game stability, equilibrium strictness, and robustness. A hypothetical case scenario involving soft-drink duopoly on Coke and Pepsi is considered to illustrate and demonstrate the proposed approach. Final results include P-values of statistical tests, confidence intervals, and simulation steady state analysis for different pure equilibriums.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

A Unified End-to-End Framework for Efficient Deep Image Compression

Image compression is a widely used technique to reduce the spatial redundancy in images. Recently, learning based image compression has achieved significant progress by using the powerful representation ability from neural networks. However, the current state-of-the-art learning based image compression methods suffer from the huge computational cost, which limits their capacity for practical applications. In this paper, we propose a unified framework called Efficient Deep Image Compression (EDIC) based on three new technologies, including a channel attention module, a Gaussian mixture model and a decoder-side enhancement module. Specifically, we design an auto-encoder style network for learning based image compression. To improve the coding efficiency, we exploit the channel relationship between latent representations by using the channel attention module. Besides, the Gaussian mixture model is introduced for the entropy model and improves the accuracy for bitrate estimation. Furthermore, we introduce the decoder-side enhancement module to further improve image compression performance. Our EDIC method can also be readily incorporated with the Deep Video Compression (DVC) framework to further improve the video compression performance. Simultaneously, our EDIC method boosts the coding performance significantly while bringing slightly increased computational cost. More importantly, experimental results demonstrate that the proposed approach outperforms the current state-of-the-art image compression methods and is up to more than 150 times faster in terms of decoding speed when compared with Minnen's method. The proposed framework also successfully improves the performance of the recent deep video compression system DVC. Our code will be released at https://github.com/liujiaheng/compression.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Channel Pruning Guided by Classification Loss and Feature Importance

In this work, we propose a new layer-by-layer channel pruning method called Channel Pruning guided by classification Loss and feature Importance (CPLI). In contrast to the existing layer-by-layer channel pruning approaches that only consider how to reconstruct the features from the next layer, our approach additionally take the classification loss into account in the channel pruning process. We also observe that some reconstructed features will be removed at the next pruning stage. So it is unnecessary to reconstruct these features. To this end, we propose a new strategy to suppress the influence of unimportant features (i.e., the features will be removed at the next pruning stage). Our comprehensive experiments on three benchmark datasets, i.e., CIFAR-10, ImageNet, and UCF-101, demonstrate the effectiveness of our CPLI method.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Content Adaptive and Error Propagation Aware Deep Video Compression

Recently, learning based video compression methods attract increasing attention. However, the previous works suffer from error propagation due to the accumulation of reconstructed error in inter predictive coding. Meanwhile, the previous learning based video codecs are also not adaptive to different video contents. To address these two problems, we propose a content adaptive and error propagation aware video compression system. Specifically, our method employs a joint training strategy by considering the compression performance of multiple consecutive frames instead of a single frame. Based on the learned long-term temporal information, our approach effectively alleviates error propagation in reconstructed frames. More importantly, instead of using the hand-crafted coding modes in the traditional compression systems, we design an online encoder updating scheme in our system. The proposed approach updates the parameters for encoder according to the rate-distortion criterion but keeps the decoder unchanged in the inference stage. Therefore, the encoder is adaptive to different video contents and achieves better compression performance by reducing the domain gap between the training and testing datasets. Our method is simple yet effective and outperforms the state-of-the-art learning based video codecs on benchmark datasets without increasing the model size or decreasing the decoding speed.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Deep Learning Detection of Inaccurate Smart Electricity Meters: A Case Study

Detecting inaccurate smart meters and targeting them for replacement can save significant resources. For this purpose, a novel deep-learning method was developed based on long short-term memory (LSTM) and a modified convolutional neural network (CNN) to predict electricity usage trajectories based on historical data. From the significant difference between the predicted trajectory and the observed one, the meters that cannot measure electricity accurately are located. In a case study, a proof of principle was demonstrated in detecting inaccurate meters with high accuracy for practical usage to prevent unnecessary replacement and increase the service life span of smart meters.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Dynamic Scheduling and Workforce Assignment in Open Source Software Development

A novel modeling framework is proposed for dynamic scheduling of projects and workforce assignment in open source software development (OSSD). The goal is to help project managers in OSSD distribute workforce to multiple projects to achieve high efficiency in software development (e.g. high workforce utilization and short development time) while ensuring the quality of deliverables (e.g. code modularity and software security). The proposed framework consists of two models: 1) a system dynamic model coupled with a meta-heuristic to obtain an optimal schedule of software development projects considering their attributes (e.g. priority, effort, duration) and 2) an agent based model to represent the development community as a social network, where development managers form an optimal team for each project and balance the workload among multiple scheduled projects based on the optimal schedule obtained from the system dynamic model. To illustrate the proposed framework, a software enhancement request process in Kuali foundation is used as a case study. Survey data collected from the Kuali development managers, project managers and actual historical enhancement requests have been used to construct the proposed models. Extensive experiments are conducted to demonstrate the impact of varying parameters on the considered efficiency and quality.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

GWOPS: A VO-technology Driven Tool to Search for the Electromagnetic Counterpart of Gravitational Wave Event

The search and follow-up observation of electromagnetic (EM) counterparts of gravitational waves (GW) is a current hot topic of GW cosmology. Due to the limitation of the accuracy of the GW observation facility at this stage, we can only get a rough sky-localization region for the GW event, and the typical area of the region is between 200 and 1500 square degrees. Since GW events occur in or near galaxies, limiting the observation target to galaxies can significantly speedup searching for EM counterparts. Therefore, how to efficiently select host galaxy candidates in such a large GW localization region, how to arrange the observation sequence, and how to efficiently identify the GW source from observational data are the problems that need to be solved. International Virtual Observatory Alliance has developed a series of technical standards for data retrieval, interoperability and visualization. Based on the application of VO technologies, we construct the GW follow-up Observation Planning System (GWOPS). It consists of three parts: a pipeline to select host candidates of GW and sort their priorities for follow-up observation, an identification module to find the transient from follow-up observation data, and a visualization module to display GW-related data. GWOPS can rapidly respond to GW events. With GWOPS, the operations such as follow-up observation planning, data storage, data visualization, and transient identification can be efficiently coordinated, which will promote the success searching rate for GWs EM counterparts.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Improving Deep Video Compression by Resolution-adaptive Flow Coding

In the learning based video compression approaches, it is an essential issue to compress pixel-level optical flow maps by developing new motion vector (MV) encoders. In this work, we propose a new framework called Resolution-adaptive Flow Coding (RaFC) to effectively compress the flow maps globally and locally, in which we use multi-resolution representations instead of single-resolution representations for both the input flow maps and the output motion features of the MV encoder. To handle complex or simple motion patterns globally, our frame-level scheme RaFC-frame automatically decides the optimal flow map resolution for each video frame. To cope different types of motion patterns locally, our block-level scheme called RaFC-block can also select the optimal resolution for each local block of motion features. In addition, the rate-distortion criterion is applied to both RaFC-frame and RaFC-block and select the optimal motion coding mode for effective flow coding. Comprehensive experiments on four benchmark datasets HEVC, VTL, UVG and MCL-JCV clearly demonstrate the effectiveness of our overall RaFC framework after combing RaFC-frame and RaFC-block for video compression.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Simulating multi-exit evacuation using deep reinforcement learning

Conventional simulations on multi-exit indoor evacuation focus primarily on how to determine a reasonable exit based on numerous factors in a changing environment. Results commonly include some congested and other under-utilized exits, especially with massive pedestrians. We propose a multi-exit evacuation simulation based on Deep Reinforcement Learning (DRL), referred to as the MultiExit-DRL, which involves in a Deep Neural Network (DNN) framework to facilitate state-to-action mapping. The DNN framework applies Rainbow Deep Q-Network (DQN), a DRL algorithm that integrates several advanced DQN methods, to improve data utilization and algorithm stability, and further divides the action space into eight isometric directions for possible pedestrian choices. We compare MultiExit-DRL with two conventional multi-exit evacuation simulation models in three separate scenarios: 1) varying pedestrian distribution ratios, 2) varying exit width ratios, and 3) varying open schedules for an exit. The results show that MultiExit-DRL presents great learning efficiency while reducing the total number of evacuation frames in all designed experiments. In addition, the integration of DRL allows pedestrians to explore other potential exits and helps determine optimal directions, leading to the high efficiency of exit utilization.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Translating multispectral imagery to nighttime imagery via conditional generative adversarial networks

Nighttime satellite imagery has been applied in a wide range of fields. However, our limited understanding of how observed light intensity is formed and whether it can be simulated greatly hinders its further application. This study explores the potential of conditional Generative Adversarial Networks (cGAN) in translating multispectral imagery to nighttime imagery. A popular cGAN framework, pix2pix, was adopted and modified to facilitate this translation using gridded training image pairs derived from Landsat 8 and Visible Infrared Imaging Radiometer Suite (VIIRS). The results of this study prove the possibility of multispectral-to-nighttime translation and further indicate that, with the additional social media data, the generated nighttime imagery can be very similar to the ground-truth imagery. This study fills the gap in understanding the composition of satellite observed nighttime light and provides new paradigms to solve the emerging problems in nighttime remote sensing fields, including nighttime series construction, light desaturation, and multi-sensor calibration.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

A Siamese Long Short-Term Memory Architecture for Human Re-Identification

Matching pedestrians across multiple camera views known as human re-identification (re-identification) is a challenging problem in visual surveillance. In the existing works concentrating on feature extraction, representations are formed locally and independent of other regions. We present a novel siamese Long Short-Term Memory (LSTM) architecture that can process image regions sequentially and enhance the discriminative capability of local feature representation by leveraging contextual information. The feedback connections and internal gating mechanism of the LSTM cells enable our model to memorize the spatial dependencies and selectively propagate relevant contextual information through the network. We demonstrate improved performance compared to the baseline algorithm with no LSTM units and promising results compared to state-of-the-art methods on Market-1501, CUHK03 and VIPeR datasets. Visualization of the internal mechanism of LSTM cells shows meaningful patterns can be learned by our method.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Dimensionality-Dependent Generalization Bounds for $k$-Dimensional Coding Schemes

The $k$-dimensional coding schemes refer to a collection of methods that attempt to represent data using a set of representative $k$-dimensional vectors, and include non-negative matrix factorization, dictionary learning, sparse coding, $k$-means clustering and vector quantization as special cases. Previous generalization bounds for the reconstruction error of the $k$-dimensional coding schemes are mainly dimensionality independent. A major advantage of these bounds is that they can be used to analyze the generalization error when data is mapped into an infinite- or high-dimensional feature space. However, many applications use finite-dimensional data features. Can we obtain dimensionality-dependent generalization bounds for $k$-dimensional coding schemes that are tighter than dimensionality-independent bounds when data is in a finite-dimensional feature space? The answer is positive. In this paper, we address this problem and derive a dimensionality-dependent generalization bound for $k$-dimensional coding schemes by bounding the covering number of the loss function class induced by the reconstruction error. The bound is of order $\mathcal{O}\left(\left(mk\ln(mkn)/n\right)^{λ_n}\right)$, where $m$ is the dimension of features, $k$ is the number of the columns in the linear implementation of coding schemes, $n$ is the size of sample, $λ_n>0.5$ when $n$ is finite and $λ_n=0.5$ when $n$ is infinite. We show that our bound can be tighter than previous results, because it avoids inducing the worst-case upper bound on $k$ of the loss function and converges faster. The proposed generalization bound is also applied to some specific coding schemes to demonstrate that the dimensionality-dependent bound is an indispensable complement to these dimensionality-independent generalization bounds.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Full-Time Supervision based Bidirectional RNN for Factoid Question Answering

Recently, bidirectional recurrent neural network (BRNN) has been widely used for question answering (QA) tasks with promising performance. However, most existing BRNN models extract the information of questions and answers by directly using a pooling operation to generate the representation for loss or similarity calculation. Hence, these existing models don't put supervision (loss or similarity calculation) at every time step, which will lose some useful information. In this paper, we propose a novel BRNN model called full-time supervision based BRNN (FTS-BRNN), which can put supervision at every time step. Experiments on the factoid QA task show that our FTS-BRNN can outperform other baselines to achieve the state-of-the-art accuracy.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Optical Transients Powered by Magnetars: Dynamics, Light Curves, and Transition to the Nebular Phase

Millisecond magnetars can be formed via several channels: core-collapse of massive stars, accretion-induced collapse of white dwarfs (WDs), double WD mergers, double neutron star (NS) mergers, and WD-NS mergers. Because the mass of ejecta from these channels could be quite different, their light curves are also expected to be diverse. We evaluate the dynamic evolution of optical transients powered by millisecond magnetars. We find that the magnetar with short spin-down timescale converts its rotational energy mostly into the kinetic energy of the transient, while the energy of a magnetar with long spin-down timescale goes into radiation of the transient. This leads us to speculate that hypernovae could be powered by magnetars with short spin-down timescales. At late times the optical transients will gradually evolve into a nebular phase because of the photospheric recession. We treat the photosphere and nebula separately because their radiation mechanisms are different. In some cases the ejecta could be light enough that the magnetar can accelerate it to a relativistic speed. It is well known that the peak luminosity of a supernova (SN) occurs when the luminosity is equal to the instantaneous energy input rate, as shown by Arnett (1979). We show that photospheric recession and relativistic motion can modify this law. The photospheric recession always leads to a delay of the peak time $t_{\mathrm{pk}}$ relative to the time $t_{\times }$ at which the SN luminosity equals the instantaneous energy input rate. Relativistic motion, however, may change this result significantly.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Solving the 56Ni puzzle of magnetar-powered broad-lined type Ic supernovae

Broad-lined type Ic supernovae (SNe Ic-BL) are of great importance because their association with long-duration gamma-ray bursts (LGRBs) holds the key to deciphering the central engine of LGRBs, which refrains from being unveiled despite decades of investigation. Among the two popularly hypothesized types of central engine, i.e., black holes and strongly magnetized neutron stars (magnetars), there is mounting evidence that the central engine of GRB-associated SNe (GRB-SNe) is rapidly rotating magnetars. Theoretical analysis also suggests that magnetars could be the central engine of SNe Ic-BL. What puzzled the researchers is the fact that light curve modeling indicates that as much as 0.2-0.5 solar mass of 56Ni was synthesized during the explosion of the SNe Ic-BL, which is unfortunately in direct conflict with current state-of-the-art understanding of magnetar-powered 56Ni synthesis. Here we propose a dynamic model of magnetar-powered SNe to take into account the acceleration of the ejecta by the magnetar, as well as the thermalization of the injected energy. Assuming that the SN kinetic energy comes exclusively from the magnetar acceleration, we find that although a major fraction of the rotational energy of the magnetar is to accelerate the SNe ejecta, a tiny fraction of this energy deposited as thermal energy of the ejecta is enough to reduce the needed 56Ni to 0.06 solar mass for both SN 1997ef and SN 2007ru. We therefore suggest that magnetars could power SNe Ic-BL both in aspects of energetics and of 56Ni synthesis.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition

3D action recognition - analysis of human actions based on 3D skeleton data - becomes popular recently due to its succinctness, robustness, and view-invariant representation. Recent attempts on this problem suggested to develop RNN-based learning methods to model the contextual dependency in the temporal domain. In this paper, we extend this idea to spatio-temporal domains to analyze the hidden sources of action-related information within the input data over both domains concurrently. Inspired by the graphical structure of the human skeleton, we further propose a more powerful tree-structure based traversal method. To handle the noise and occlusion in 3D skeleton data, we introduce new gating mechanism within LSTM to learn the reliability of the sequential input data and accordingly adjust its effect on updating the long-term context information stored in the memory cell. Our method achieves state-of-the-art performance on 4 challenging benchmark datasets for 3D human action analysis.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

PTF11iqb: Cool supergiant mass loss that bridges the gap between Type IIn and normal supernovae

PTF11iqb was initially classified as a TypeIIn event caught very early after explosion. It showed narrow Wolf-Rayet (WR) spectral features on day 2, but the narrow emission weakened quickly and the spectrum morphed to resemble those of Types II-L and II-P. At late times, Halpha emission exhibited a complex, multipeaked profile reminiscent of SN1998S. In terms of spectroscopic evolution, we find that PTF11iqb was a near twin of SN~1998S, although with weaker interaction with circumstellar material (CSM) at early times, and stronger CSM interaction at late times. We interpret the spectral changes as caused by early interaction with asymmetric CSM that is quickly (by day 20) enveloped by the expanding SN ejecta photosphere, but then revealed again after the end of the plateau when the photosphere recedes. The light curve can be matched with a simple model for weak CSM interaction added to the light curve of a normal SN~II-P. This plateau requires that the progenitor had an extended H envelope like a red supergiant, consistent with the slow progenitor wind speed indicated by narrow emission. The cool supergiant progenitor is significant because PTF11iqb showed WR features in its early spectrum --- meaning that the presence of such WR features in an early SN spectrum does not necessarily indicate a WR-like progenitor. [abridged] Overall, PTF11iqb bridges SNe~IIn with weaker pre-SN mass loss seen in SNe II-L and II-P, implying a continuum between these types.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Scalable Nuclear-norm Minimization by Subspace Pursuit Proximal Riemannian Gradient

Nuclear-norm regularization plays a vital role in many learning tasks, such as low-rank matrix recovery (MR), and low-rank representation (LRR). Solving this problem directly can be computationally expensive due to the unknown rank of variables or large-rank singular value decompositions (SVDs). To address this, we propose a proximal Riemannian gradient (PRG) scheme which can efficiently solve trace-norm regularized problems defined on real-algebraic variety $\mMLr$ of real matrices of rank at most $r$. Based on PRG, we further present a simple and novel subspace pursuit (SP) paradigm for general trace-norm regularized problems without the explicit rank constraint $\mMLr$. The proposed paradigm is very scalable by avoiding large-rank SVDs. Empirical studies on several tasks, such as matrix completion and LRR based subspace clustering, demonstrate the superiority of the proposed paradigms over existing methods.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

SU(3) and Isospin Breaking Effects on B to PPP Amplitudes

Several modes of $B$ decays into three pseudoscalar octet mesons PPP have been measured. These decays have provided useful information for B decays in the standard model (SM). Some of powerful tools in analyzing B decays are flavor $SU(3)$ and isospin symmetries. Such analyses are usually hampered by $SU(3)$ breaking effects due to a relatively large strange quark mass which breaks SU(3) symmetry down to isospin symmetry. The isospin symmetry also breaks down when up and down quark mass difference is non-zero. It is therefore interesting to find relations which are not sensitive to $SU(3)$ and isospin breaking effects. We find that the relations among several fully-symmetric $B \to PPP$ decay amplitudes are not affected by first order $SU(3)$ breaking effects due to a non-zero strange quark mass, and also some of them are not affected by first isospin breaking effects. These relations, therefore, hold to good precisions. Measurements for these relations can provide important information about B decays in the SM.

0 citations0 reviewsNo code linkedOpen access
preprint2014arXiv

A Continuum of H- to He-Rich Tidal Disruption Candidates With a Preference for E+A Galaxies

We present the results of a Palomar Transient Factory (PTF) archival search for blue transients which lie in the magnitude range between "normal" core-collapse and superluminous supernovae (i.e. with $-21\,{\leq}M_{R\,(peak)}\,{\leq}-19$). Of the six events found after excluding all interacting Type~IIn and Ia-CSM supernovae, three (PTF09ge, 09axc and 09djl) are coincident with the centers of their hosts, one (10iam) is offset from the center, and for two (10nuj and 11glr) a precise offset can not be determined. All the central events have similar rise times to the He-rich tidal disruption candidate PS1-10jh, and the event with the best-sampled light curve also has similar colors and power-law decay. Spectroscopically, PTF09ge is He-rich, while PTF09axc and 09djl display broad hydrogen features around peak magnitude. All three central events are in low star-formation hosts, two of which are E+A galaxies. Our spectrum of the host of PS1-10jh displays similar properties. PTF10iam, the one offset event, is different photometrically and spectroscopically from the central events and its host displays a higher star formation rate. Finding no obvious evidence for ongoing galactic nuclei activity or recent star formation, we conclude that the three central transients likely arise from the tidal disruption of a star by a super-massive black hole. We compare the spectra of these events to tidal disruption candidates from the literature and find that all of these objects can be unified on a continuous scale of spectral properties. The accumulated evidence of this expanded sample strongly supports a tidal disruption origin for this class of nuclear transients.

0 citations0 reviewsNo code linkedOpen access
preprint2014arXiv

Exploring the spectral diversity of low-redshift Type Ia supernovae using the Palomar Transient Factory

We present an investigation of the optical spectra of 264 low-redshift (z < 0.2) Type Ia supernovae (SNe Ia) discovered by the Palomar Transient Factory, an untargeted transient survey. We focus on velocity and pseudo-equivalent width measurements of the Si II 4130, 5972, and 6355 A lines, as well those of the Ca II near-infrared (NIR) triplet, up to +5 days relative to the SN B-band maximum light. We find that a high-velocity component of the Ca II NIR triplet is needed to explain the spectrum in ~95 per cent of SNe Ia observed before -5 days, decreasing to ~80 per cent at maximum. The average velocity of the Ca II high-velocity component is ~8500 km/s higher than the photospheric component. We confirm previous results that SNe Ia around maximum light with a larger contribution from the high-velocity component relative to the photospheric component in their Ca II NIR feature have, on average, broader light curves and lower Ca II NIR photospheric velocities. We find that these relations are driven by both a stronger high-velocity component and a weaker contribution from the photospheric Ca II NIR component in broader light curve SNe Ia. We identify the presence of C II in very-early-time SN Ia spectra (before -10 days), finding that >40 per cent of SNe Ia observed at these phases show signs of unburnt material in their spectra, and that C II features are more likely to be found in SNe Ia having narrower light curves.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

A supra-massive magnetar central engine for short GRB 130603B

We show that the peculiar early optical and in particular X-ray afterglow emission of the short duration burst GRB 130603B can be explained by continuous energy injection into the blastwave from a supra-massive magnetar central engine. The observed energetics and temporal/spectral properties of the late infrared bump (i.e., the "kilonova") are also found consistent with emission from the ejecta launched during an NS-NS merger and powered by a magnetar central engine. The isotropic-equivalent kinetic energies of both the GRB blastwave and the kilonova are about $E_{\rm k}\sim 10^{51}$ erg, consistent with being powered by a near-isotropic magnetar wind. However, this relatively small value demands that most of the initial rotational energy of the magnetar $(\sim {\rm a~ few \times 10^{52}~ erg})$ is carried away by gravitational wave radiation. Our results suggest that (i) the progenitor of GRB 130603B would be a NS-NS binary system, whose merger product would be a supra-massive neutron star that lasted for about $\sim 1000$ seconds; (ii) the equation-of-state of nuclear matter would be stiff enough to allow survival of a long-lived supra-massive neutron star, so that it is promising to detect bright electromagnetic counterparts of gravitational wave triggers without short GRB associations in the upcoming Advanced LIGO/Virgo era.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

Direct evidence for a supernova interacting with a large amount of hydrogen-free circumstellar material

We present our observations of SN 2010mb, a Type Ic SN lacking spectroscopic signatures of H and He. SN 2010mb has a slowly-declining light curve ($\sim600\,$days) that cannot be powered by $^{56}$Ni/$^{56}$Co radioactivity, the common energy source for Type Ic SNe. We detect signatures of interaction with hydrogen-free CSM including a blue quasi-continuum and, uniquely, narrow oxygen emission lines that require high densities ($\sim10^9$cm$^{-3}$). From the observed spectra and light curve we estimate that the amount of material involved in the interaction was $\sim3$M$_{\odot}$. Our observations are in agreement with models of pulsational pair-instability SNe described in the literature.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

Is the late near-infrared bump in short-hard GRB 130603B due to the Li-Paczynski kilonova?

Short-hard gamma-ray bursts (GRBs) are widely believed to be produced by the merger of two binary compact objects, specifically by two neutron stars or by a neutron star orbiting a black hole. According to the Li-Paczynski kilonova model, the merger would launch sub-relativistic ejecta and a near-infrared/optical transient would then occur, lasting up to days, which is powered by the radioactive decay of heavy elements synthesized in the ejecta. The detection of a late bump using the {\em Hubble Space Telescope} ({\em HST}) in the near-infrared afterglow light curve of the short-hard GRB 130603B is indeed consistent with such a model. However, as shown in this Letter, the limited {\em HST} near-infrared lightcurve behavior can also be interpreted as the synchrotron radiation of the external shock driven by a wide mildly relativistic outflow. In such a scenario, the radio emission is expected to peak with a flux of $\sim 100 μ$Jy, which is detectable for current radio arrays. Hence, the radio afterglow data can provide complementary evidence on the nature of the bump in GRB 130603B. It is worth noting that good spectroscopy during the bump phase in short-hard bursts can test validity of either model above, analogous to spectroscopy of broad-lined Type Ic supernova in long-soft GRBs.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

Large SU(3) breaking effects and CP violation in $B^+ $ decays into three charged SU(3) octet pseudoscalar mesons

TThe LHCb collaboration has recently reported evidence for non-zero CP asymmetries in $B^+$ decays into $π^+ K^+ K^-,\; π^+π^+π^-,\; K^+ K^+ K^- $ and $K^+π^+π^-$. The branching ratios for these decays have also been measured with different values ranging from $5\times 10^{-6}$ to $51\times 10^{-6}$. If flavor $SU(3)$ symmetry is a good symmetry for $B$ decays, in the case that the dominant amplitude is momentum independent it is expected that branching ratios $Br$ and CP violating rate differences $Δ_{CP} = Γ- \overlineΓ$ satisfy, $Br(π^+π^+π^-) = 2Br(π^+ K^+ K^-)$, $Br(K^+K^+K^-) = 2 Br(K^+π^+π^-)$, and $Δ_{CP}(π^+π^+π^-) = 2Δ_{CP}(π^+ K^+K^-) = - Δ_{CP}(K^+K^+K^-) = -2Δ_{CP}(K^+π^+π^-)$. The experimental data do not exhibit the expected pattern for the branching ratios. The rate differences for $B^+\to π^+π^+π^-$ and $B^+\to K^+ K^+ K^-$ satisfy the relation between $ΔS =0$ and $ΔS=1$ well, but the other two do not, with the CP asymmetries having different signs than expected. In this work we study how to including momentum dependent and also $SU(3)$ breaking effects on these decays to explain experimental data. We find that only including lowest order derivative terms, in the $SU(3)$ limit, the decay patterns cannot be explained. Large $SU(3)$ breaking effects are needed to explain the data.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

The $β$ angle as the CP violating phase in the CKM matrix

The CKM matrix describing quark mixing with three generations can be parameterized by three Euler mixing angles and one CP violating phase. In most of the parameterizations, the CP violating phase chosen is not a directly measurable quantity and is parametrization dependent. In this work, we propose to use the most accurately measured CP violating angle $β$ in the unitarity triangleas the phase in the CKM matrix, and construct an explicit $β$ parameterization. We also derive an approximate Wolfenstein-like expression for this parameterization.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

Type Ia Supernovae Strongly Interacting with Their Circumstellar Medium

Owing to their utility for measurements of cosmic acceleration, Type Ia supernovae (SNe) are perhaps the best-studied class of SNe, yet the progenitor systems of these explosions largely remain a mystery. A rare subclass of SNe Ia show evidence of strong interaction with their circumstellar medium (CSM), and in particular, a hydrogen-rich CSM; we refer to them as SNe Ia-CSM. In the first systematic search for such systems, we have identified 16 SNe Ia-CSM, and here we present new spectra of 13 of them. Six SNe Ia-CSM have been well-studied previously, three were previously known but are analyzed in-depth for the first time here, and seven are new discoveries from the Palomar Transient Factory. The spectra of all SNe Ia-CSM are dominated by Hα emission (with widths of ~2000 km/s) and exhibit large Hα/Hβ intensity ratios (perhaps due to collisional excitation of hydrogen via the SN ejecta overtaking slower-moving CSM shells); moreover, they have an almost complete lack of He I emission. They also show possible evidence of dust formation through a decrease in the red wing of Hα 75-100 d past maximum brightness, and nearly all SNe Ia-CSM exhibit strong Na I D absorption from the host galaxy. The absolute magnitudes (uncorrected for host-galaxy extinction) of SNe Ia-CSM are found to be -21.3 <= M_R <= -19 mag, and they also seem to show ultraviolet emission at early times and strong infrared emission at late times (but no detected radio or X-ray emission). Finally, the host galaxies of SNe Ia-CSM are all late-type spirals similar to the Milky Way, or dwarf irregulars like the Large Magellanic Cloud, which implies that these objects come from a relatively young stellar population. This work represents the most detailed analysis of the SN Ia-CSM class to date.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

U-spin analysis of CP violation in $B^- $ decays into three charged light pseudoscalar mesons

We carry out a $U$-spin symmetry analysis for CP violation in $B^- $ decays into three light $π^-π^-π^+$, $π^- K^-K^+$, $K^-K^-K^+$ and $K^- π^-π^+$ mesons. We clarify some subtle points in constructing decay amplitudes with $U=0$ formed by the two negatively charged light mesons in the final states. $U$-spin conserving momentum independent and momentum dependent decay amplitudes, and $U$-spin violating decay amplitudes due to quark mass difference are constructed.

0 citations0 reviewsNo code linkedOpen access
preprint2012arXiv

Gamma-Ray Bursts: the Isotropic-Equivalent-Energy Function and the Cosmic Formation Rate

Gamma-ray bursts (GRBs) are brief but intense emission of soft $γ-$rays, mostly lasting from a few seconds to a few thousand seconds. For such kind of high energy transients, their isotropic-equivalent-energy ($E_{\rm iso}$) function may be more scientifically meaningful when compared with GRB isotropic-equivalent-luminosity function ($L_{\rm iso}$), as the traditional luminosity function refers to steady emission much longer than a few thousand seconds. In this work we for the first time construct the isotropic-equivalent-energy function for a sample of 95 bursts with measured redshifts ($z$) and find an excess of high-$z$ GRBs. Assuming that the excess is caused by a GRB luminosity function evolution in a power-law form, we find a cosmic evolution of $E_{\rm iso}\propto(1+z)^{1.80^{+0.36}_{-0.63}}$, which is comparable to that between $L_{\rm iso}$ and $z$, i.e., $L_{\rm iso}\propto(1+z)^{2.30^{+0.56}_{-0.51}}$ (both $1σ$). The evolution-removed isotropic-equivalent-energy function can be reasonably fitted by a broken power-law, in which the dim and bright segments are $ψ(E_{\rm iso})\propto E_{\rm iso}^{-0.27\pm0.01}$ and $ψ(E_{\rm iso})\propto E_{\rm iso}^{-0.87\pm0.07}$, respectively ($1σ$). For the cosmic GRB formation rate, it increases quickly in the region of $0 \leq z \lesssim 1$, and roughly keeps constant for $1\lesssim z \lesssim 4$, and finally falls with a power index of $-3.80\pm2.16$ for $z\gtrsim 4$, in good agreement with the observed cosmic star formation rate so far.

0 citations0 reviewsNo code linkedOpen access
preprint2012arXiv

GRB 120422A: A Low-luminosity Gamma-ray Burst Driven by Central Engine

GRB 120422A is a low-luminosity Gamma-ray burst (GRB) associated with a bright supernova, which distinguishes itself by its relatively short T90 ~ 5 s and an energetic X-ray tail. We analyze the Swift BAT and XRT data and discuss the physical implications. We show that the early steep decline in the X-ray light curve can be interpreted as the curvature tail of a late emission episode around 58-86 s, with a curved instantaneous spectrum at the end of the emission episode. Together with the main activity in the first ~ 20 s and the weak emission from 40 s to 60 s, the prompt emission is variable, which points towards a central engine origin, in contrast to the shock breakout origin as invoked to interpret some other nearby low-luminosity supernova GRBs. The curvature effect interpretation and interpreting the early shallow decay as the coasting external forward shock emission in a wind medium both give a constraint on the bulk Lorentz factor Γto be around several. Comparing the properties of GRB 120422A and other supernova GRBs, we found that the main criterion to distinguish engine-driven GRBs from the shock breakout GRBs is the time-averaged luminosity, with a separation line of about ~ 10^48 erg s^-1.

0 citations0 reviewsNo code linkedOpen access
preprint2012arXiv

Learning with Augmented Features for Heterogeneous Domain Adaptation

We propose a new learning method for heterogeneous domain adaptation (HDA), in which the data from the source domain and the target domain are represented by heterogeneous features with different dimensions. Using two different projection matrices, we first transform the data from two domains into a common subspace in order to measure the similarity between the data from two domains. We then propose two new feature mapping functions to augment the transformed data with their original features and zeros. The existing learning methods (e.g., SVM and SVR) can be readily incorporated with our newly proposed augmented feature representations to effectively utilize the data from both domains for HDA. Using the hinge loss function in SVM as an example, we introduce the detailed objective function in our method called Heterogeneous Feature Augmentation (HFA) for a linear case and also describe its kernelization in order to efficiently cope with the data with very high dimensions. Moreover, we also develop an alternating optimization algorithm to effectively solve the nontrivial optimization problem in our HFA method. Comprehensive experiments on two benchmark datasets clearly demonstrate that HFA outperforms the existing HDA methods.

0 citations0 reviewsNo code linkedOpen access
preprint2012arXiv

Swift J2058.4+0516: Discovery of a Possible Second Relativistic Tidal Disruption Flare?

We report the discovery by the Swift hard X-ray monitor of the transient source Swift J2058.4+0516 (Sw J2058+05). Our multi-wavelength follow-up campaign uncovered a long-lived (duration >~ months), luminous X-ray (L_X,iso ~ 3 x 10^47 erg s^-1) and radio (nu L_nu,iso ~ 10^42 erg s^-1) counterpart. The associated optical emission, however, from which we measure a redshift of 1.1853, is relatively faint, and this is not due to a large amount of dust extinction in the host galaxy. Based on numerous similarities with the recently discovered GRB 110328A / Swift J164449.3+573451 (Sw J1644+57), we suggest that Sw J2058+05 may be the second member of a new class of relativistic outbursts resulting from the tidal disruption of a star by a supermassive black hole. If so, the relative rarity of these sources (compared with the expected rate of tidal disruptions) implies that either these outflows are extremely narrowly collimated (theta < 1 degree), or only a small fraction of tidal disruptions generate relativistic ejecta. Analogous to the case of long-duration gamma-ray bursts and core-collapse supernovae, we speculate that rapid spin of the black hole may be a necessary condition to generate the relativistic component. Alternatively, if powered by gas accretion (i.e., an active galactic nucleus [AGN]), Sw J2058+05 would seem to represent a new mode of variability in these sources, as the observed properties appear largely inconsistent with known classes of AGNs capable of generating relativistic jets (blazars, narrow-line Seyfert 1 galaxies).

0 citations0 reviewsNo code linkedOpen access
preprint2012arXiv

The $α$, $β$ and $γ$ parameterizations of CP violating CKM phase

The CKM matrix describing quark mixing with three generations can be parameterized by three mixing angles and one CP violating phase. In most of the parameterizations, the CP violating phase chosen is not a directly measurable quantity and is parametrization dependent. In this work, we propose to use experimentally measurable CP violating quantities, $α$, $β$ or $γ$ in the unitarity triangle as the phase in the CKM matrix, and construct explicit $α$, $β$ and $γ$ parameterizations. Approximate Wolfenstein-like expressions are also suggested.

0 citations0 reviewsNo code linkedOpen access
preprint2011arXiv

Calcium-rich gap transients in the remote outskirts of galaxies

From the first two seasons of the Palomar Transient Factory, we identify three peculiar transients (PTF09dav, PTF10iuv, PTF11bij) with five distinguishing characteristics: peak luminosity in the gap between novae and supernovae (M_R = 15.5 to -16.5), rapid photometric evolution (rise-time ~12--15 days), large photospheric velocities (~6000 to 11000 km/s), early spectroscopic evolution into nebular phase (~1 to 3 months) and peculiar nebular spectra dominated by Calcium. We also culled the extensive decade-long Lick Observatory Supernova Search database and identified an additional member of this group, SN 2007ke. Our choice of photometric and spectroscopic properties was motivated by SN 2005E (Perets et al. 2010). To our surprise, as in the case of SN 2005E, all four members of this group are also clearly offset from the bulk of their host galaxy. Given the well-sampled early and late-time light curves, we derive ejecta masses in the range of 0.4--0.7 Msun. Spectroscopically, we find that there may be a diversity in the photospheric phase, but the commonality is in the unusual nebular spectra. Our extensive follow-up observations rule out standard thermonuclear and standard core-collapse explosions for this class of "Calcium-rich gap" transients. If the progenitor is a white dwarf, we are likely seeing a detonation of the white dwarf core and perhaps, even shockfront interaction with a previously ejected nova shell. In the less likely scenario of a massive star progenitor, a very non-standard channel specific to a low-metallicity environment needs to be invoked (e.g., ejecta fallback leading to black hole formation). Detection (or lack thereof) of a faint underlying host (dwarf galaxy, cluster) will provide a crucial and decisive diagnostic to choose between these alternatives.

0 citations0 reviewsNo code linkedOpen access
preprint2011arXiv

PTF10ops - a subluminous, normal-width lightcurve Type Ia supernova in the middle of nowhere

PTF10ops is a Type Ia supernova (SN Ia), whose lightcurve and spectral properties place it outside the current SN Ia subtype classifications. Its spectra display the characteristic lines of subluminous SNe Ia, but it has a normal-width lightcurve with a long rise-time, typical of normal luminosity SNe Ia. The early-time optical spectra of PTF10ops were modelled using a spectral fitting code and found to have all the lines typically seen in subluminous SNe Ia, without the need to invoke more uncommon elements. The host galaxy environment of PTF10ops is also unusual with no galaxy detected at the position of the SN down to an absolute limiting magnitude of r \geq -12.0 mag, but a very massive galaxy is present at a separation of ~148 kpc and at the same redshift as suggested by the SN spectral features. The progenitor of PTF10ops is most likely a very old star, possibly in a low metallicity environment, which affects its explosion mechanism and observational characteristics. PTF10ops does not easily fit into any of the current models of either subluminous or normal SN Ia progenitor channels.

0 citations0 reviewsNo code linkedOpen access
preprint2011arXiv

PTF11eon/SN2011dh: Discovery of a Type IIb Supernova From a Compact Progenitor in the Nearby Galaxy M51

On May 31, 2011 UT a supernova (SN) exploded in the nearby galaxy M51 (the Whirlpool Galaxy). We discovered this event using small telescopes equipped with CCD cameras, as well as by the Palomar Transient Factory (PTF) survey, and rapidly confirmed it to be a Type II supernova. Our early light curve and spectroscopy indicates that PTF11eon resulted from the explosion of a relatively compact progenitor star as evidenced by the rapid shock-breakout cooling seen in the light curve, the relatively low temperature in early-time spectra and the prompt appearance of low-ionization spectral features. The spectra of PTF11eon are dominated by H lines out to day 10 after explosion, but initial signs of He appear to be present. Assuming that He lines continue to develop in the near future, this SN is likely a member of the cIIb (compact IIb; Chevalier and Soderberg 2010) class, with progenitor radius larger than that of SN 2008ax and smaller than the eIIb (extended IIb) SN 1993J progenitor. Our data imply that the object identified in pre-explosion Hubble Space Telescope images at the SN location is possibly a companion to the progenitor or a blended source, and not the progenitor star itself, as its radius (~10^13 cm) would be highly inconsistent with constraints from our post-explosion photometric and spectroscopic data.

0 citations0 reviewsNo code linkedOpen access
preprint2011arXiv

Real-Time Detection and Rapid Multiwavelength Follow-up Observations of a Highly Subluminous Type II-P Supernova from the Palomar Transient Factory Survey

The Palomar Transient Factory (PTF) is an optical wide-field variability survey carried out using a camera with a 7.8 square degree field of view mounted on the 48-in Oschin Schmidt telescope at Palomar Observatory. One of the key goals of this survey is to conduct high-cadence monitoring of the sky in order to detect optical transient sources shortly after they occur. Here, we describe the real-time capabilities of the PTF and our related rapid multiwavelength follow-up programs, extending from the radio to the gamma-ray bands. We present as a case study observations of the optical transient PTF10vdl (SN 2010id), revealed to be a very young core-collapse (Type II-P) supernova having a remarkably low luminosity. Our results demonstrate that the PTF now provides for optical transients the real-time discovery and rapid-response follow-up capabilities previously reserved only for high-energy transients like gamma-ray bursts.

0 citations0 reviewsNo code linkedOpen access
preprint2011arXiv

SN2010jp (PTF10aaxi): A Jet-Driven Type II Supernova

We present photometry and spectroscopy of the peculiar TypeII supernova (SN) 2010jp, also named PTF10aaxi. The light curve exhibits a linear decline with a relatively low peak absolute magnitude of only -15.9, and a low radioactive decay luminosity at late times that suggests a nickel mass below 0.003 $M_{\odot}$. Spectra of SN2010jp display an unprecedented triple-peaked H$α$ line profile, showing: (1) a narrow (800 km/s) central component that suggests shock interaction with dense CSM; (2) high-velocity blue and red emission features centered at -12600 and +15400 km/s; and (3) broad wings extending from -22000 to +25000 km/s. These features persist during 100 days after explosion. We propose that this line profile indicates a bipolar jet-driven explosion, with the central component produced by normal SN ejecta and CSM interaction at mid latitudes, while the high-velocity bumps and broad line wings arise in a nonrelativistic bipolar jet. Two variations of the jet interpretation seem plausible: (1) A fast jet mixes 56Ni to high velocities in polar zones of the H-rich envelope, or (2) the reverse shock in the jet produces blue and red bumps in Balmer lines when a jet interacts with dense CSM. Jet-driven SNeII are predicted for collapsars resulting from a wide range of initial masses above 25 $M_{\odot}$ at sub-solar metallicity. This seems consistent with the SN host environment, which is either an extremely low-luminosity dwarf galaxy or very remote parts of an interacting pair of star-forming galaxies. It also seems consistent with the low 56Ni mass that may accompany black hole formation. We speculate that the jet survives to produce observable signatures because the star's H envelope was mostly stripped away by previous eruptive mass loss.

0 citations0 reviewsNo code linkedOpen access
preprint2010arXiv

XRF 100316D/SN 2010bh: clue to the diverse origin of nearby supernova-associated GRBs

X-ray Flash (XRF) 100316D, a nearby super-long under-luminous burst with a peak energy E_p \sim 20 keV, was detected by Swift and was found to be associated with an energetic supernova SN 2010bh. Both the spectral and the temporal behavior of this burst are rather similar to that of XRF 060218, except that the latter was associated with a "less energetic" SN 2006aj and had a prominent soft thermal emission component in the spectrum. We analyze the spectral and temporal properties of this burst, and interpret the prompt gamma-ray emission and the early X-ray plateau emission as synchrotron emission from a dissipating Poynting-flux-dominated outflow, probably powered by a magnetar with a spin period of $P \sim 10$ ms and the polar cap magnetic field $B_{\rm p} \sim 3\times 10^{15}$ G. The energetic supernova SN 2010bh associated with this burst is, however, difficult to interpret within the slow magnetar model, which implies that the nascent magnetar may spin much faster with an initial rotation period $\sim 1$ ms, and thus suggests a delay between the core collapse and the emergence of the relativistic magnetar wind from the star. The diverse behaviors of low-luminosity GRBs and their associated SNe may be understood within a unified picture that invokes different initial powers of the central engine and different delay times between the core collapse and the emergence of the relativistic jet from the star.

0 citations0 reviewsNo code linkedOpen access
preprint2009arXiv

GRB 080916C and GRB 090510: the high energy emission and the afterglow

We constrain the physical composition of the outflows of GRBs 080916C and 090510 with the prompt emission data and find that the former is likely magnetic while the latter may be baryonic. The X-ray and optical afterglow emission of both GRBs can be reasonably fitted using the standard external shock model but the density profiles of the circum-burst medium are different. We also propose a simple method to estimate the number of the seed photons suppose the GeV afterglow photons are due to the inverse Compton radiation of external forward shock electrons. The seed photons needed in the modeling are too many to be realistic for both events. The synchrotron radiation of the forward shock seems able to account for the GeV afterglow data.

0 citations0 reviewsNo code linkedOpen access
preprint2007arXiv

Fine-structure splitting of exciton states in quantum dot molecules: symmetry and tunnel-coupling effects

Exciton levels and fine-structure splitting in laterally-coupled quantum dot molecules are studied. The electron and hole tunneling energies as well as the direct Coulomb interaction are essential for the exciton levels. It is found that fine-structure splitting of the two-lowest exciton levels is contributed from the intra- and inter-dot exchange interactions, both of which are largely influenced by the symmetry and tunnel-coupling between the two dots. As the inter-dot separation is reduced, fine-structure splitting of the exciton ground state is largely increased while those of the excited states are decreased. Moreover, the dependence of the fine-structure splitting in quantum dot molecules on the Coulomb correlation is clearly clarified.

0 citations0 reviewsNo code linkedOpen access