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Jie Gao

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preprint2026arXiv

Can Vision Language Models Be Adaptive in Mathematics Education? A Learner Model-based Rubric Study

Adaptive learning refers to educational technologies that track learners' learning progress and adapt the instructional process based on individual learners' learning performance. It is increasingly recognized as critical for developing an effective learning support tool. Vision language models (VLMs) have seen adoption in mathematics education, and students have been using them as learning aids for personalized instruction. However, it is unknown whether VLMs have the ability to adapt to different learner profiles when providing mathematical instructions. Current VLMs lack a systematic evaluation framework for this adaptivity to different learner profiles in mathematics tutoring tasks. To address this gap, we draw on the learner model from the adaptive learning framework (Shute and Towle, 2018) and propose a learner model-based rubric. Our rubric formalizes adaptivity assessment into three aspects: cognitive aspects, motivational aspects, and complexity. We also evaluate two additional dimensions of VLM responses: correctness (of answers and solutions) and quality (of the response itself). Our experimental results show measurable differences in adaptivity across models and also reveal that current VLMs struggle to consistently produce learner model-based instructional responses, especially when receiving limited learner information.

preprint2026arXiv

How to Interpret Agent Behavior

Autonomous agents such as Claude Code and Codex now operate for hours or even days. Understanding their runtime behavior has become critical for downstream tasks such as diagnosing inefficiencies, fixing bugs, and ensuring better oversight. A primary way to gain this understanding is analyzing the reasoning trajectories and execution traces these agents generate. Yet such data remains in unstructured natural-language form, making it difficult for humans to interpret at scale. We introduce ACT*ONOMY (a combination of Action and Taxonomy), a taxonomy for describing and analyzing agent behavior at runtime. ACT*ONOMY has two components: (1) the taxonomy itself, developed through Grounded Theory and structured as a three-level hierarchy of 10 actions, 46 subactions, and 120 leaf categories; and (2) an open repository that hosts the living taxonomy, provides an automated analysis pipeline that applies it to agent trajectories analysis, and defines an extension protocol for customization and growth. Our experiments show that ACTONOMY can compare behavioral profiles across agents and characterize a single agent's behavior across diverse trajectories, surfacing patterns indicative of failure modes. By providing a shared vocabulary, ACT*ONOMY helps researchers, agent designers, and end users interpret agent behavior more consistently, enabling better oversight and control.

preprint2023arXiv

Holistic Network Virtualization and Pervasive Network Intelligence for 6G

In this tutorial paper, we look into the evolution and prospect of network architecture and propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed architecture has two key elements, i.e., holistic network virtualization and pervasive artificial intelligence (AI). The holistic network virtualization consists of network slicing and digital twin, from the aspects of service provision and service demand, respectively, to incorporate service-centric and user-centric networking. The pervasive network intelligence integrates AI into future networks from the perspectives of networking for AI and AI for networking, respectively. Building on holistic network virtualization and pervasive network intelligence, the proposed architecture can facilitate three types of interplay, i.e., the interplay between digital twin and network slicing paradigms, between model-driven and data-driven methods for network management, and between virtualization and AI, to maximize the flexibility, scalability, adaptivity, and intelligence for 6G networks. We also identify challenges and open issues related to the proposed architecture. By providing our vision, we aim to inspire further discussions and developments on the potential architecture of 6G.

preprint2023arXiv

Understanding the Complexity and Its Impact on Testing in ML-Enabled Systems

Machine learning (ML) enabled systems are emerging with recent breakthroughs in ML. A model-centric view is widely taken by the literature to focus only on the analysis of ML models. However, only a small body of work takes a system view that looks at how ML components work with the system and how they affect software engineering for MLenabled systems. In this paper, we adopt this system view, and conduct a case study on Rasa 3.0, an industrial dialogue system that has been widely adopted by various companies around the world. Our goal is to characterize the complexity of such a largescale ML-enabled system and to understand the impact of the complexity on testing. Our study reveals practical implications for software engineering for ML-enabled systems.

preprint2022arXiv

From 996 to 007: Challenges of Working from Home During the Epidemic in China

During the COVID-19 epidemic in China, millions of workers in tech companies had to start working from home (WFH). The change was sudden, unexpected and companies were not ready for it. Additionally, it was also the first time that WFH was experienced on such a large scale. We used the opportunity to describe the effect of WFH at scale for a sustained period of time. As the lockdown was easing, we conducted semi-structured interviews with 12 participants from China working in tech companies. While at first, WFH was reported as a pleasant experience with advantages, e.g. flexible schedule, more time with family, over time, this evolved into a rather negative experience where workers start working all day, every day and feel a higher workload despite the actual workload being reduced. We discuss these results and how they could apply for other extreme circumstances and to help improve WFH in general.

preprint2022arXiv

Injection induced by coaxial laser interference in laser wakefield accelerators

A new injection scheme using the interference of two coaxial laser pulses is proposed for generating high quality beams in laser wakefield accelerators. In this scheme, a relatively loosely focused laser pulse drives the plasma wakefield, and a tightly focused laser pulse with similar intensity triggers interference ring pattern which creates onion-like multi sheaths in the plasma wakefield. Due to the wavefront curvature change after the focal position of the tightly focused laser, the innermost sheath of the wakefield expands, which slows down the effective phase velocity of the wakefield and triggers injection of plasma electrons. Particle-in-cell simulations show that high quality electron beams with low energy spread (a few per mill), high charge (hundred picocoulomb) and small emittance (sub millimeter milliradian) at the same time can be generated using moderate laser parameters for properly chosen phase differences between the two lasers.

preprint2022arXiv

Investigation of spin rotators in CEPC at the Z-pole

Longitudinal polarization is an important design aspect of the future 100 km-scale Circular Electron Position Collider (CEPC). Spin rotators are needed in CEPC collider rings to make the beam polarization along the longitudinal direction at the interaction points (IPs). This paper focuses on the design of spin rotators for CEPC at Z-pole (45.6 GeV). The design of spin rotators in CEPC at Z-pole is based on solenoid magnets and horizontal bending magnets sections. The coupling of transverse motion introduced by solenoids is compensated with quadrupole lenses. Adjustments have been made to the layout to implement the spin rotators into the collider rings.Longitudinal polarized beam can be achieved at the IPs with the spin rotators. High degree of polarization is attainable, while the effect of spin rotators on orbital motion is acceptable. The detailed simulation results will be presented.A solenoid-based spin rotator configuration is designed and integrated into the CEPC collider ring lattice. According to the simulation results, the polarization requirements can be satisfied.

preprint2022arXiv

Logically at Factify 2022: Multimodal Fact Verification

This paper describes our participant system for the multi-modal fact verification (Factify) challenge at AAAI 2022. Despite the recent advance in text based verification techniques and large pre-trained multimodal models cross vision and language, very limited work has been done in applying multimodal techniques to automate fact checking process, particularly considering the increasing prevalence of claims and fake news about images and videos on social media. In our work, the challenge is treated as multimodal entailment task and framed as multi-class classification. Two baseline approaches are proposed and explored including an ensemble model (combining two uni-modal models) and a multi-modal attention network (modeling the interaction between image and text pair from claim and evidence document). We conduct several experiments investigating and benchmarking different SoTA pre-trained transformers and vision models in this work. Our best model is ranked first in leaderboard which obtains a weighted average F-measure of 0.77 on both validation and test set. Exploratory analysis of dataset is also carried out on the Factify data set and uncovers salient patterns and issues (e.g., word overlapping, visual entailment correlation, source bias) that motivates our hypothesis. Finally, we highlight challenges of the task and multimodal dataset for future research.

preprint2022arXiv

On Cyclic Solutions to the Min-Max Latency Multi-Robot Patrolling Problem

We consider the following surveillance problem: Given a set $P$ of $n$ sites in a metric space and a set of $k$ robots with the same maximum speed, compute a patrol schedule of minimum latency for the robots. Here a patrol schedule specifies for each robot an infinite sequence of sites to visit (in the given order) and the latency $L$ of a schedule is the maximum latency of any site, where the latency of a site $s$ is the supremum of the lengths of the time intervals between consecutive visits to $s$. When $k=1$ the problem is equivalent to the travelling salesman problem (TSP) and thus it is NP-hard. We have two main results. We consider cyclic solutions in which the set of sites must be partitioned into $\ell$ groups, for some~$\ell \leq k$, and each group is assigned a subset of the robots that move along the travelling salesman tour of the group at equal distance from each other. Our first main result is that approximating the optimal latency of the class of cyclic solutions can be reduced to approximating the optimal travelling salesman tour on some input, with only a $1+\varepsilon$ factor loss in the approximation factor and an $O\left(\left( k/\varepsilon \right)^k\right)$ factor loss in the runtime, for any $\varepsilon >0$. Our second main result shows that an optimal cyclic solution is a $2(1-1/k)$-approximation of the overall optimal solution. Note that for $k=2$ this implies that an optimal cyclic solution is optimal overall. The results have a number of consequences. For the Euclidean version of the problem, for instance, combining our results with known results on Euclidean TSP, yields a PTAS for approximating an optimal cyclic solution, and it yields a $(2(1-1/k)+\varepsilon)$-approximation of the optimal unrestricted solution. If the conjecture mentioned above is true, then our algorithm is actually a PTAS for the general problem in the Euclidean setting.

preprint2022arXiv

Optimal Local Bayesian Differential Privacy over Markov Chains

In the literature of data privacy, differential privacy is the most popular model. An algorithm is differentially private if its outputs with and without any individual's data are indistinguishable. In this paper, we focus on data generated from a Markov chain and argue that Bayesian differential privacy (BDP) offers more meaningful guarantees in this context. Our main theoretical contribution is providing a mechanism for achieving BDP when data is drawn from a binary Markov chain. We improve on the state-of-the-art BDP mechanism and show that our mechanism provides the optimal noise-privacy tradeoffs for any local mechanism up to negligible factors. We also briefly discuss a non-local mechanism which adds correlated noise. Lastly, we perform experiments on synthetic data that detail when DP is insufficient, and experiments on real data to show that our privacy guarantees are robust to underlying distributions that are not simple Markov chains.

preprint2022arXiv

Social Network Community Detection Based on Textual Content Similarity and Sentimental Tendency

Shared travel has gradually become one of the hot topics discussed on social networking platforms such as Micro Blog. In a timely manner, deeper network community detection on the evaluation content of shared travel in social networks can effectively conduct research and analysis on the public opinion orientation related to shared travel, which has great application prospects. The existing community detection algorithms generally measure the similarity of nodes in the network from the perspective of spatial distance. This paper proposes a Community detection algorithm based on Textual content Similarity and sentimental Tendency (CTST), considering the network structure and node attributes at the same time. The content similarity and sentimental tendency of network community users are taken as node attributes, and on this basis, an undirected weighted network is constructed for community detection. This paper conducts experiments with actual data and analyzes the experimental results. It is found that the modularity of the community detection results is high and the effect is good.

preprint2022arXiv

Study Overview for Super Proton-Proton Collider

SPPC (Super Proton-Proton Collider) is a discovery machine that is designed for energy frontier research in two decades from now, as the second stage of the CEPC-SPPC project. The main objective is to carry out experiments at 125 TeV in center-of-mass energy in a two-ring collider of 100 km in circumference and 20 T in dipole field. This white paper about SPPC describes the machine related issues, including performance, design overview, design challenges, key technologies and their maturity and required R&D, staged options and upgrades, synergies with other facilities, and environmental impacts.

preprint2022arXiv

Subspace Differential Privacy

Many data applications have certain invariant constraints due to practical needs. Data curators who employ differential privacy need to respect such constraints on the sanitized data product as a primary utility requirement. Invariants challenge the formulation, implementation, and interpretation of privacy guarantees. We propose subspace differential privacy, to honestly characterize the dependence of the sanitized output on confidential aspects of the data. We discuss two design frameworks that convert well-known differentially private mechanisms, such as the Gaussian and the Laplace mechanisms, to subspace differentially private ones that respect the invariants specified by the curator. For linear queries, we discuss the design of near-optimal mechanisms that minimize the mean squared error. Subspace differentially private mechanisms rid the need for post-processing due to invariants, preserve transparency and statistical intelligibility of the output, and can be suitable for distributed implementation. We showcase the proposed mechanisms on the 2020 Census Disclosure Avoidance demonstration data, and a spatio-temporal dataset of mobile access point connections on a large university campus.

preprint2022arXiv

TCR: A Transformer Based Deep Network for Predicting Cancer Drugs Response

Predicting clinical outcomes to anti-cancer drugs on a personalized basis is challenging in cancer treatment due to the heterogeneity of tumors. Traditional computational efforts have been made to model the effect of drug response on individual samples depicted by their molecular profile, yet overfitting occurs because of the high dimension for omics data, hindering models from clinical application. Recent research shows that deep learning is a promising approach to build drug response models by learning alignment patterns between drugs and samples. However, existing studies employed the simple feature fusion strategy and only considered the drug features as a whole representation while ignoring the substructure information that may play a vital role when aligning drugs and genes. Hereby in this paper, we propose TCR (Transformer based network for Cancer drug Response) to predict anti-cancer drug response. By utilizing an attention mechanism, TCR is able to learn the interactions between drug atom/sub-structure and molecular signatures efficiently in our study. Furthermore, a dual loss function and cross sampling strategy were designed to improve the prediction power of TCR. We show that TCR outperformed all other methods under various data splitting strategies on all evaluation matrices (some with significant improvement). Extensive experiments demonstrate that TCR shows significantly improved generalization ability on independent in-vitro experiments and in-vivo real patient data. Our study highlights the prediction power of TCR and its potential value for cancer drug repurpose and precision oncology treatment.

preprint2022arXiv

The Optimal Beam-loading in Two-bunch Nonlinear Plasma Wakefield Accelerators

Due to the highly nonlinear nature of the beam-loading, it is at present not possible to analytically determine the beam parameters needed in a two-bunch plasma wakefield accelerator for maintaining a low energy spread. Therefore in this paper, by using the Broyden-Fletcher-Goldfarb-Shanno algorithm for the parameter scanning with the code QuickPIC and the polynomial regression together with k-fold cross-validation method, we obtain two fitting formulas for calculating the parameters of tri-Gaussian electron beams when minimizing the energy spread based on the beam-loading effect in a nonlinear plasma wakefield accelerator. One formula allows the optimization of the normalized charge per unit length of a trailing beam to achieve the minimal energy spread, i.e. the optimal beam-loading. The other one directly gives the transformer ratio when the trailing beam achieves the optimal beam-loading. A simple scaling law for charges of drive beams and trailing beams is obtained from the fitting formula, which indicates that the optimal beam-loading is always achieved for a given charge ratio of the two beams when the length and separation of two beams and the plasma density are fixed. The formulas can also help obtain the optimal plasma densities for the maximum accelerated charge and the maximum acceleration efficiency under the optimal beam-loading respectively. These two fitting formulas will significantly enhance the efficiency for designing and optimizing a two-bunch plasma wakefield acceleration stage.

preprint2022arXiv

Time Window Frechet and Metric-Based Edit Distance for Passively Collected Trajectories

The advances of modern localization techniques and the wide spread of mobile devices have provided us great opportunities to collect and mine human mobility trajectories. In this work, we focus on passively collected trajectories, which are sequences of time-stamped locations that mobile entities visit. To analyse such trajectories, a crucial part is a measure of similarity between two trajectories. We propose the time-window Frechet distance, which enforces the maximum temporal separation between points of two trajectories that can be paired in the calculation of the Frechet distance, and the metric-based edit distance which incorporates the underlying metric in the computation of the insertion and deletion costs. Using these measures, we can cluster trajectories to infer group motion patterns. We look at the $k$-gather problem which requires each cluster to have at least $k$ trajectories. We prove that k-gather remains NP-hard under edit distance, metric-based edit distance and Jaccard distance. Finally, we improve over previous results on discrete Frechet distance and show that there is no strongly sub-quadratic time with approximation factor less than $1.61$ in two dimensional setting unless SETH fails.

preprint2021arXiv

Application-driven Privacy-preserving Data Publishing with Correlated Attributes

Recent advances in computing have allowed for the possibility to collect large amounts of data on personal activities and private living spaces. To address the privacy concerns of users in this environment, we propose a novel framework called PR-GAN that offers privacy-preserving mechanism using generative adversarial networks. Given a target application, PR-GAN automatically modifies the data to hide sensitive attributes -- which may be hidden and can be inferred by machine learning algorithms -- while preserving the data utility in the target application. Unlike prior works, the public's possible knowledge of the correlation between the target application and sensitive attributes is built into our modeling. We formulate our problem as an optimization problem, show that an optimal solution exists and use generative adversarial networks (GAN) to create perturbations. We further show that our method provides privacy guarantees under the Pufferfish framework, an elegant generalization of the differential privacy that allows for the modeling of prior knowledge on data and correlations. Through experiments, we show that our method outperforms conventional methods in effectively hiding the sensitive attributes while guaranteeing high performance in the target application, for both property inference and training purposes. Finally, we demonstrate through further experiments that once our model learns a privacy-preserving task, such as hiding subjects' identity, on a group of individuals, it can perform the same task on a separate group with minimal performance drops.

preprint2021arXiv

Scissor-cross ionization injection in laser wakefield accelerators

We propose to use a frequency doubled pulse colliding with the driving pulse at an acute angle to trigger ionization injection in a laser wakefield accelerator. This scheme effectively reduces the duration that injection occurs, thus high injection quality is obtained. Three-dimensional particle-in-cell simulations show that electron beams with energy of ~500 MeV, charge of ~40 pC, energy spread of ~1% and normalized emittance of a few millimeter milliradian can be produced by ~100 TW laser pulses. By adjusting the angle between the two pulses, the intensity of the trigger pulse and the gas dope ratio, the charge and energy spread of the electron beam can be controlled.

preprint2020arXiv

An Efficient QP Variable Convolutional Neural Network Based In-loop Filter for Intra Coding

In this paper, a novel QP variable convolutional neural network based in-loop filter is proposed for VVC intra coding. To avoid training and deploying multiple networks, we develop an efficient QP attention module (QPAM) which can capture compression noise levels for different QPs and emphasize meaningful features along channel dimension. Then we embed QPAM into the residual block, and based on it, we design a network architecture that is equipped with controllability for different QPs. To make the proposed model focus more on examples that have more compression artifacts or is hard to restore, a focal mean square error (MSE) loss function is employed to fine tune the network. Experimental results show that our approach achieves 4.03\% BD-Rate saving on average for all intra configuration, which is even better than QP-separate CNN models while having less model parameters.

preprint2020arXiv

Approximation Algorithms for Multi-Robot Patrol-Scheduling with Min-Max Latency

We consider the problem of finding patrol schedules for $k$ robots to visit a given set of $n$ sites in a metric space. Each robot has the same maximum speed and the goal is to minimize the weighted maximum latency of any site, where the latency of a site is defined as the maximum time duration between consecutive visits of that site. The problem is NP-hard, as it has the traveling salesman problem as a special case (when $k=1$ and all sites have the same weight). We present a polynomial-time algorithm with an approximation factor of $O(k^2 \log \frac{w_{\max}}{w_{\min}})$ to the optimal solution, where $w_{\max}$ and $w_{\min}$ are the maximum and minimum weight of the sites respectively. Further, we consider the special case where the sites are in 1D. When all sites have the same weight, we present a polynomial-time algorithm to solve the problem exactly. If the sites may have different weights, we present a $12$-approximate solution, which runs in polynomial time when the number of robots, $k$, is a constant.

preprint2020arXiv

Cutting Polygons into Small Pieces with Chords: Laser-Based Localization

Motivated by indoor localization by tripwire lasers, we study the problem of cutting a polygon into small-size pieces, using the chords of the polygon. Several versions are considered, depending on the definition of the "size" of a piece. In particular, we consider the area, the diameter, and the radius of the largest inscribed circle as a measure of the size of a piece. We also consider different objectives, either minimizing the maximum size of a piece for a given number of chords, or minimizing the number of chords that achieve a given size threshold for the pieces. We give hardness results for polygons with holes and approximation algorithms for multiple variants of the problem.

preprint2020arXiv

Data Inference from Encrypted Databases: A Multi-dimensional Order-Preserving Matching Approach

Due to increasing concerns of data privacy, databases are being encrypted before they are stored on an untrusted server. To enable search operations on the encrypted data, searchable encryption techniques have been proposed. Representative schemes use order-preserving encryption (OPE) for supporting efficient Boolean queries on encrypted databases. Yet, recent works showed the possibility of inferring plaintext data from OPE-encrypted databases, merely using the order-preserving constraints, or combined with an auxiliary plaintext dataset with similar frequency distribution. So far, the effectiveness of such attacks is limited to single-dimensional dense data (most values from the domain are encrypted), but it remains challenging to achieve it on high-dimensional datasets (e.g., spatial data) which are often sparse in nature. In this paper, for the first time, we study data inference attacks on multi-dimensional encrypted databases (with 2-D as a special case). We formulate it as a 2-D order-preserving matching problem and explore both unweighted and weighted cases, where the former maximizes the number of points matched using only order information and the latter further considers points with similar frequencies. We prove that the problem is NP-hard, and then propose a greedy algorithm, along with a polynomial-time algorithm with approximation guarantees. Experimental results on synthetic and real-world datasets show that the data recovery rate is significantly enhanced compared with the previous 1-D matching algorithm.

preprint2020arXiv

Energy-Efficient UAV-Assisted Mobile Edge Computing: Resource Allocation and Trajectory Optimization

In this paper, we study unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) with the objective to optimize computation offloading with minimum UAV energy consumption. In the considered scenario, a UAV plays the role of an aerial cloudlet to collect and process the computation tasks offloaded by ground users. Given the service requirements of users, we aim to maximize UAV energy efficiency by jointly optimizing the UAV trajectory, the user transmit power, and computation load allocation. The resulting optimization problem corresponds to nonconvex fractional programming, and the Dinkelbach algorithm and the successive convex approximation (SCA) technique are adopted to solve it. Furthermore, we decompose the problem into multiple subproblems for distributed and parallel problem solving. To cope with the case when the knowledge of user mobility is limited, we adopt a spatial distribution estimation technique to predict the location of ground users so that the proposed approach can still be applied. Simulation results demonstrate the effectiveness of the proposed approach for maximizing the energy efficiency of UAV.

preprint2020arXiv

Low-Latency and Fresh Content Provision in Information-Centric Vehicular Networks

In this paper, the content service provision of information-centric vehicular networks (ICVNs) is investigated from the aspect of mobile edge caching, considering the dynamic driving-related context information. To provide up-to-date information with low latency, two schemes are designed for cache update and content delivery at the roadside units (RSUs). The roadside unit centric (RSUC) scheme decouples cache update and content delivery through bandwidth splitting, where the cached content items are updated regularly in a round-robin manner. The request adaptive (ReA) scheme updates the cached content items upon user requests with certain probabilities. The performance of both proposed schemes are analyzed, whereby the average age of information (AoI) and service latency are derived in closed forms. Surprisingly, the AoI-latency trade-off does not always exist, and frequent cache update can degrade both performances. Thus, the RSUC and ReA schemes are further optimized to balance the AoI and latency. Extensive simulations are conducted on SUMO and OMNeT++ simulators, and the results show that the proposed schemes can reduce service latency by up to 80\% while guaranteeing content freshness in heavily loaded ICVNs.

preprint2020arXiv

RP-DNN: A Tweet level propagation context based deep neural networks for early rumor detection in Social Media

Early rumor detection (ERD) on social media platform is very challenging when limited, incomplete and noisy information is available. Most of the existing methods have largely worked on event-level detection that requires the collection of posts relevant to a specific event and relied only on user-generated content. They are not appropriate to detect rumor sources in the very early stages, before an event unfolds and becomes widespread. In this paper, we address the task of ERD at the message level. We present a novel hybrid neural network architecture, which combines a task-specific character-based bidirectional language model and stacked Long Short-Term Memory (LSTM) networks to represent textual contents and social-temporal contexts of input source tweets, for modelling propagation patterns of rumors in the early stages of their development. We apply multi-layered attention models to jointly learn attentive context embeddings over multiple context inputs. Our experiments employ a stringent leave-one-out cross-validation (LOO-CV) evaluation setup on seven publicly available real-life rumor event data sets. Our models achieve state-of-the-art(SoA) performance for detecting unseen rumors on large augmented data which covers more than 12 events and 2,967 rumors. An ablation study is conducted to understand the relative contribution of each component of our proposed model.

preprint2020arXiv

Streaming Chunk-Aware Multihead Attention for Online End-to-End Speech Recognition

Recently, streaming end-to-end automatic speech recognition (E2E-ASR) has gained more and more attention. Many efforts have been paid to turn the non-streaming attention-based E2E-ASR system into streaming architecture. In this work, we propose a novel online E2E-ASR system by using Streaming Chunk-Aware Multihead Attention(SCAMA) and a latency control memory equipped self-attention network (LC-SAN-M). LC-SAN-M uses chunk-level input to control the latency of encoder. As to SCAMA, a jointly trained predictor is used to control the output of encoder when feeding to decoder, which enables decoder to generate output in streaming manner. Experimental results on the open 170-hour AISHELL-1 and an industrial-level 20000-hour Mandarin speech recognition tasks show that our approach can significantly outperform the MoChA-based baseline system under comparable setup. On the AISHELL-1 task, our proposed method achieves a character error rate (CER) of 7.39%, to the best of our knowledge, which is the best published performance for online ASR.

preprint2020arXiv

The Design of Dynamic Probabilistic Caching with Time-Varying Content Popularity

In this paper, we design dynamic probabilistic caching for the scenario when the instantaneous content popularity may vary with time while it is possible to predict the average content popularity over a time window. Based on the average content popularity, optimal content caching probabilities can be found, e.g., from solving optimization problems, and existing results in the literature can implement the optimal caching probabilities via static content placement. The objective of this work is to design dynamic probabilistic caching that: i) converge (in distribution) to the optimal content caching probabilities under time-invariant content popularity, and ii) adapt to the time-varying instantaneous content popularity under time-varying content popularity. Achieving the above objective requires a novel design of dynamic content replacement because static caching cannot adapt to varying content popularity while classic dynamic replacement policies, such as LRU, cannot converge to target caching probabilities (as they do not exploit any content popularity information). We model the design of dynamic probabilistic replacement policy as the problem of finding the state transition probability matrix of a Markov chain and propose a method to generate and refine the transition probability matrix. Extensive numerical results are provided to validate the effectiveness of the proposed design.

preprint2020arXiv

Visual Perception Model for Rapid and Adaptive Low-light Image Enhancement

Low-light image enhancement is a promising solution to tackle the problem of insufficient sensitivity of human vision system (HVS) to perceive information in low light environments. Previous Retinex-based works always accomplish enhancement task by estimating light intensity. Unfortunately, single light intensity modelling is hard to accurately simulate visual perception information, leading to the problems of imbalanced visual photosensitivity and weak adaptivity. To solve these problems, we explore the precise relationship between light source and visual perception and then propose the visual perception (VP) model to acquire a precise mathematical description of visual perception. The core of VP model is to decompose the light source into light intensity and light spatial distribution to describe the perception process of HVS, offering refinement estimation of illumination and reflectance. To reduce complexity of the estimation process, we introduce the rapid and adaptive $\mathbfβ$ and $\mathbfγ$ functions to build an illumination and reflectance estimation scheme. Finally, we present a optimal determination strategy, consisting of a \emph{cycle operation} and a \emph{comparator}. Specifically, the \emph{comparator} is responsible for determining the optimal enhancement results from multiple enhanced results through implementing the \emph{cycle operation}. By coordinating the proposed VP model, illumination and reflectance estimation scheme, and the optimal determination strategy, we propose a rapid and adaptive framework for low-light image enhancement. Extensive experiment results demenstrate that the proposed method achieves better performance in terms of visual comparison, quantitative assessment, and computational efficiency, compared with the currently state-of-the-arts.

preprint2016arXiv

Analytical estimation of ATF beam halo distribution

In order to study the background status in the ATF2 beam line and the interaction point (IP), this paper developed an analytical method to give the estimation of ATF beam halo distribution based on K. Hirata and K. Yokoya's theory. The equilibrium particle distribution of beam tail in ATF damping ring, when each electron is being affected by, in addition to the synchrotron radiation damping effects, several stochastic processes, such as beam-gas scattring, beam-gas bremsstrahlung and intra-beam scattering, was presented. This method is common and can be applied on other electron rings.

preprint2016arXiv

Beam halo study on ATF damping ring

Halo distribution is a key topic for background study. This paper has developed an analytical method to give an estimation of ATF beam halo distribution. The equilibrium particle distribution of the beam tail in the ATF damping ring is calculated analytically with different emittance and different vacuum degree. The analytical results agree the measurements very well. This is a general method which can be applied to any electron rings.

preprint2016arXiv

Capacitated Kinetic Clustering in Mobile Networks by Optimal Transportation Theory

We consider the problem of capacitated kinetic clustering in which $n$ mobile terminals and $k$ base stations with respective operating capacities are given. The task is to assign the mobile terminals to the base stations such that the total squared distance from each terminal to its assigned base station is minimized and the capacity constraints are satisfied. This paper focuses on the development of \emph{distributed} and computationally efficient algorithms that adapt to the motion of both terminals and base stations. Suggested by the optimal transportation theory, we exploit the structural property of the optimal solution, which can be represented by a power diagram on the base stations such that the total usage of nodes within each power cell equals the capacity of the corresponding base station. We show by using the kinetic data structure framework the first analytical upper bound on the number of changes in the optimal solution, i.e., its stability. On the algorithm side, using the power diagram formulation we show that the solution can be represented in size proportional to the number of base stations and can be solved by an iterative, local algorithm. In particular, this algorithm can naturally exploit the continuity of motion and has orders of magnitude faster than existing solutions using min-cost matching and linear programming, and thus is able to handle large scale data under mobility.

preprint2015arXiv

Cavity and HOM Coupler Design for CEPC

In this paper we will show a cavity and higher order mode (HOM) coupler designing scheme for the Circular Electron-Positron Collider (CEPC) main ring. The cavity radio frequency (RF) design parameters are showed in this paper. The HOM power is calculated based on the beam parameters in the Preliminary Conceptual Design Report (Pre-CDR). The damping results of the higher order modes (HOMs) and same order modes (SOMs) show that they are reached the damping requirements for beam stability.

preprint2015arXiv

Concept for a Future Super Proton-Proton Collider

Following the discovery of the Higgs boson at LHC, new large colliders are being studied by the international high-energy community to explore Higgs physics in detail and new physics beyond the Standard Model. In China, a two-stage circular collider project CEPC-SPPC is proposed, with the first stage CEPC (Circular Electron Positron Collier, a so-called Higgs factory) focused on Higgs physics, and the second stage SPPC (Super Proton-Proton Collider) focused on new physics beyond the Standard Model. This paper discusses this second stage.

preprint2015arXiv

Diffraction-free optical beam propagation with near-zero phase variation in extremely anisotropic metamaterials

Extremely anisotropic metal-dielectric multilayer metamaterials are designed to have the effective permittivity tensor of a transverse component (parallel to the interfaces of the multilayer) with zero real part and a longitudinal component (normal to the interfaces of the multilayer) with ultra-large imaginary part at the same wavelength, including the optical nonlocality analysis based on the transfer-matrix method. The diffraction-free deep-subwavelength optical beam propagation with near-zero phase variation in the designed multilayer stack due to the near-flat iso-frequency contour is demonstrated and analyzed, including the effects of the multilayer period and the material loss.

preprint2015arXiv

HOMs Simulation and Measurement Results of IHEP02 Cavity

In cavities, there exists not only the fundamental mode which is used to accelerate the beam but also higher order modes (HOMs). The higher order modes excited by beam can seriously affect beam quality, especially for the higher R/Q modes. This paper reports on measured results of higher order modes in the IHEP02 1.3GHz low-loss 9-cell superconducting cavity. Using different methods, Qe of the dangerous modes passbands have been got. The results are compared with TESLA cavity results. R/Q of the first three passbands have also been got by simulation and compared with the results of TESLA cavity.

preprint2015arXiv

Method Study of Parameter Choice for a Circular Proton-Proton Collider

In this paper we showed a systematic method of appropriate parameter choice for a circular pp collider by using analytical expression of beam-beam tune shift limit started from given design goal and technical limitations. A parameter space has been explored. Based on parameters scan and considerations from RF systems, a set of appropriate parameter designed for a 50Km and a 100Km circular proton-proton collider was proposed.

preprint2015arXiv

Nonlocal effective medium analysis in symmetric metal-dielectric multilayer metamaterials

The optical nonlocality in symmetric metal-dielectric multilayer metamaterials is theoretically and experimentally investigated with respect to transverse-magnetic-polarized incident light. A nonlocal effective medium theory is derived from the transfer-matrix method to determine the nonlocal effective permittivity depending on both the frequency and wave vector in a symmetric metal-dielectric multilayer stack. In contrast to the local effective medium theory, our proposed nonlocal effective medium theory can accurately predict measured incident angle-dependent reflection spectra from a fabricated multilayer stack and provide nonlocal dispersion relations. Moreover, the bulk plasmon polaritons with large wave vectors supported in the multilayer stack are also investigated with the nonlocal effective medium theory through the analysis of the dispersion relation and eigenmode.

preprint2015arXiv

Nonlocal effective medium approximation for metallic nanorod metamaterials

We present an analytical nonlocal effective medium approximation to describe the optical nonlocal effects in metallic nanorod metamaterials based on Mie scattering theory. It is shown that the developed nonlocal effective medium theory can predict a coexistence state of two modes around the epsilon-near-zero region, where strong optical nonlocal effects lead to the behavior of both positive refraction and negative refraction in the nanorod metamaterials. Outside of the coexistence region, only one mode can be excited and its behavior can be well described using the local effective medium theory.

preprint2015arXiv

Ricci Curvature of the Internet Topology

Analysis of Internet topologies has shown that the Internet topology has negative curvature, measured by Gromov's "thin triangle condition", which is tightly related to core congestion and route reliability. In this work we analyze the discrete Ricci curvature of the Internet, defined by Ollivier, Lin, etc. Ricci curvature measures whether local distances diverge or converge. It is a more local measure which allows us to understand the distribution of curvatures in the network. We show by various Internet data sets that the distribution of Ricci cuvature is spread out, suggesting the network topology to be non-homogenous. We also show that the Ricci curvature has interesting connections to both local measures such as node degree and clustering coefficient, global measures such as betweenness centrality and network connectivity, as well as auxilary attributes such as geographical distances. These observations add to the richness of geometric structures in complex network theory.

preprint2015arXiv

Space Filling Curves for 3D Sensor Networks with Complex Topology

Several aspects of managing a sensor network (e.g., motion planning for data mules, serial data fusion and inference) benefit once the network is linearized to a path. The linearization is often achieved by constructing a space filling curve in the domain. However, existing methods cannot handle networks distributed on surfaces of complex topology. This paper presents a novel method for generating space filling curves for 3D sensor networks that are distributed densely on some two-dimensional geometric surface. Our algorithm is completely distributed and constructs a path which gets uniformly, progressively denser as it becomes longer. We analyze the algorithm mathematically and prove that the curve we obtain is dense. Our method is based on the Hodge decomposition theorem and uses holomorphic differentials on Riemann surfaces. The underlying high genus surface is conformally mapped to a union of flat tori and then a proportionally-dense space filling curve on this union is constructed. The pullback of this curve to the original network gives us the desired curve.

preprint2015arXiv

Stable Delaunay Graphs

Let $P$ be a set of $n$ points in $\mathrm{R}^2$, and let $\mathrm{DT}(P)$ denote its Euclidean Delaunay triangulation. We introduce the notion of an edge of $\mathrm{DT}(P)$ being {\it stable}. Defined in terms of a parameter $α>0$, a Delaunay edge $pq$ is called $α$-stable, if the (equal) angles at which $p$ and $q$ see the corresponding Voronoi edge $e_{pq}$ are at least $α$. A subgraph $G$ of $\mathrm{DT}(P)$ is called {\it $(cα, α)$-stable Delaunay graph} ($\mathrm{SDG}$ in short), for some constant $c \ge 1$, if every edge in $G$ is $α$-stable and every $cα$-stable of $\mathrm{DT}(P)$ is in $G$. We show that if an edge is stable in the Euclidean Delaunay triangulation of $P$, then it is also a stable edge, though for a different value of $α$, in the Delaunay triangulation of $P$ under any convex distance function that is sufficiently close to the Euclidean norm, and vice-versa. In particular, a $6α$-stable edge in $\mathrm{DT}(P)$ is $α$-stable in the Delaunay triangulation under the distance function induced by a regular $k$-gon for $k \ge 2π/α$, and vice-versa. Exploiting this relationship and the analysis in~\cite{polydel}, we present a linear-size kinetic data structure (KDS) for maintaining an $(8α,α)$-$\mathrm{SDG}$ as the points of $P$ move. If the points move along algebraic trajectories of bounded degree, the KDS processes nearly quadratic events during the motion, each of which can processed in $O(\log n)$ time. Finally, we show that a number of useful properties of $\mathrm{DT}(P)$ are retained by $\mathrm{SDG}$ of $P$.

preprint2015arXiv

Study on CEPC performances with different collision energies and geometric layouts

Circular Electron-Positron Collider(CEPC) is one of the largest plans in high energy physics study at China, which would serve as Higgs Factory firstly and then upgrade to a hadron collider. In this paper we give the 50km and 100km design in both single ring and double ring schemes, including $Z$ boson and $W$ boson and Higgs boson by using the optimized method. Also, we give the potential of CEPC running at $Z$ and $W$ poles. And we analysis the relationship of luminosity with circumference and filling factor, which gives a way to evaluate the choice of geometry. What's more, we compare the nominal performance of CEPC-SPPC and LHC and FCC.

preprint2014arXiv

Complex Contagions in Kleinberg's Small World Model

Complex contagions describe diffusion of behaviors in a social network in settings where spreading requires the influence by two or more neighbors. In a $k$-complex contagion, a cluster of nodes are initially infected, and additional nodes become infected in the next round if they have at least $k$ already infected neighbors. It has been argued that complex contagions better model behavioral changes such as adoption of new beliefs, fashion trends or expensive technology innovations. This has motivated rigorous understanding of spreading of complex contagions in social networks. Despite simple contagions ($k=1$) that spread fast in all small world graphs, how complex contagions spread is much less understood. Previous work~\cite{Ghasemiesfeh:2013:CCW} analyzes complex contagions in Kleinberg's small world model~\cite{kleinberg00small} where edges are randomly added according to a spatial distribution (with exponent $γ$) on top of a two dimensional grid structure. It has been shown in~\cite{Ghasemiesfeh:2013:CCW} that the speed of complex contagions differs exponentially when $γ=0$ compared to when $γ=2$. In this paper, we fully characterize the entire parameter space of $γ$ except at one point, and provide upper and lower bounds for the speed of $k$-complex contagions. We study two subtly different variants of Kleinberg's small world model and show that, with respect to complex contagions, they behave differently. For each model and each $k \geq 2$, we show that there is an intermediate range of values, such that when $γ$ takes any of these values, a $k$-complex contagion spreads quickly on the corresponding graph, in a polylogarithmic number of rounds. However, if $γ$ is outside this range, then a $k$-complex contagion requires a polynomial number of rounds to spread to the entire network.

preprint2014arXiv

Efficient Strategies for Single/Multi-Target Jamming on MIMO Gaussian Channels

The problem of jamming on multiple-input multiple-output (MIMO) Gaussian channels is investigated in this paper. In the case of a single target legitimate signal, we show that the existing result based on the simplification of the system model by neglecting the jamming channel leads to losing important insights regarding the effect of jamming power and jamming channel on the jamming strategy. We find a closed-form optimal solution for the problem under a positive semi-definite (PSD) condition without considering simplifications in the model. If the condition is not satisfied and the optimal solution may not exist in closed-form, we find the optimal solution using a numerical method and also propose a suboptimal solution in closed-form as a close approximation of the optimal solution. Then, the possibility of extending the results to solve the problem of multi-target jamming is investigated for four scenarios, i.e., multiple access channel, broadcasting channel, multiple transceiver pairs with orthogonal transmissions, and multiple transceiver pairs with interference, respectively. It is shown that the proposed numerical method can be extended to all scenarios while the proposed closed-form solutions for jamming may be applied in the scenarios of the multiple access channel and multiple transceiver pairs with orthogonal transmissions. Simulation results verify the effectiveness of the proposed solutions.

preprint2014arXiv

How Complex Contagions Spread Quickly in the Preferential Attachment Model and Other Time-Evolving Networks

In this paper, we study the spreading speed of complex contagions in a social network. A $k$-complex contagion starts from a set of initially infected seeds such that any node with at least $k$ infected neighbors gets infected. Simple contagions, i.e., $k=1$, quickly spread to the entire network in small world graphs. However, fast spreading of complex contagions appears to be less likely and more delicate; the successful cases depend crucially on the network structure~\cite{G08,Ghasemiesfeh:2013:CCW}. Our main result shows that complex contagions can spread fast in a general family of time-evolving networks that includes the preferential attachment model~\cite{barabasi99emergence}. We prove that if the initial seeds are chosen as the oldest nodes in a network of this family, a $k$-complex contagion covers the entire network of $n$ nodes in $O(\log n)$ steps. We show that the choice of the initial seeds is crucial. If the initial seeds are uniformly randomly chosen in the PA model, even with a polynomial number of them, a complex contagion would stop prematurely. The oldest nodes in a preferential attachment model are likely to have high degrees. However, we remark that it is actually not the power law degree distribution per se that facilitates fast spreading of complex contagions, but rather the evolutionary graph structure of such models. Some members of the said family do not even have a power-law distribution. We also prove that complex contagions are fast in the copy model~\cite{KumarRaRa00}, a variant of the preferential attachment family. Finally, we prove that when a complex contagion starts from an arbitrary set of initial seeds on a general graph, determining if the number of infected vertices is above a given threshold is $\mathbf{P}$-complete. Thus, one cannot hope to categorize all the settings in which complex contagions percolate in a graph.

preprint2014arXiv

Realizing broadband electromagnetic transparency with a graded-permittivity sphere

Broadband electromagnetic transparency phenomenon is realized with a well-designed graded-permittivity sphere, which has an extremely low scattering cross section over a wide frequency range, based on the generalized Mie scattering theory and numerical simulation in full-wave condition. The dynamic polarization cancellation is revealed by studying the variation of the polarization with respect to the frequency. Furthermore, a properly-designed multi-shell sphere is also proposed and examined in order to reduce the rigorous conditions for realizing the broadband transparency in experiments.

preprint2014arXiv

Study of alternative ILC final focus optical configurations

The role of the ILC final focus system (FFS) is to demagnify the beam to the sizes at the IP required to meet the ILC luminosity goals. The current design of final focus performs perfect chromaticity correction in both horizontal and vertical planes. Based on this design a set of alternative optical configurations were studied in which the horizontal beam size at the IP is increased while at the same time the vertical one is decreased, with the goal of reducing beamsstrahlung emission. Luminosity reduction due to the hour glass effect must be considered because betay*/sigmaz* becomes much smaller in this case. The beam-beam interaction simulation by Guineapig++ was used for evaluation. Reduced bunch lengths are used to make sure that the obtained luminosities are not lower than those of the ILC original (nominal) configuration.

preprint2013arXiv

A Variational Principle for Improving 2D Triangle Meshes based on Hyperbolic Volume

In this paper, we consider the problem of improving 2D triangle meshes tessellating planar regions. We propose a new variational principle for improving 2D triangle meshes where the energy functional is a convex function over the angle structures whose maximizer is unique and consists only of equilateral triangles. This energy functional is related to hyperbolic volume of ideal 3-simplex. Even with extra constraints on the angles for embedding the mesh into the plane and preserving the boundary, the energy functional remains well-behaved. We devise an efficient algorithm for maximizing the energy functional over these extra constraints. We apply our algorithm to various datasets and compare its performance with that of CVT. The experimental results show that our algorithm produces the meshes with both the angles and the aspect ratios of triangles lying in tighter intervals.

preprint2013arXiv

Anomalous optical coupling between two silicon wires of a slot waveguide in epsilon-near-zero metamaterials

Anomalous optical coupling properties between two silicon wires in a silicon slot waveguide embedded in epsilon-near-zero (ENZ) metamaterials are proposed and demonstrated. The dependences of optical field enhancement in the slot region and transverse optical force on the slot size and the permittivity of surrounding material are studied in details. It is demonstrated that the optical field in the slot region is significantly enhanced due to the giant index contrast at the slot interface between silicon wires and ENZ metamaterials, but the optical mode coupling between silicon wires is greatly reduced so that the transverse optical force is suppressed into almost zero. Moreover, metal-dielectric multilayer structures are designed to realize ENZ metamaterials in the slot region for achieving the electric field enhancement.

preprint2013arXiv

Broadband Epsilon-Near-Zero Metamaterials with Step-Like Metal-Dielectric Multilayer Structures

The concept of the broadband epsilon-near-zero meta-atom consisting of layered stacks with specified metallic filling ratio and thickness is proposed based on the Bergman spectral representation of the effective permittivity. The step-like metal-dielectric multilayer structures are designed to achieve realistic broadband epsilon-near-zero meta-atoms in optical frequency range. These meta-atoms can be integrated as building blocks for unconventional optical components with exotic electromagnetic properties over a wide frequency range, such as the demonstrated broadband directional emission and phase front shaping.

preprint2013arXiv

Experimental demonstration of near-infrared epsilon-near-zero multilayer metamaterial slabs

Near-infrared epsilon-near-zero (ENZ) metamaterial slabs based on silver-germanium (Ag-Ge) multilayers are experimentally demonstrated. Transmission, reflection and absorption spectra are characterized and used to determine the complex refractive indices and the effective permittivities of the ENZ metamaterial slabs, which match the results obtained from both the numerical simulations and the optical nonlocalities analysis. A rapid post-annealing process is used to reduce the collision frequency of silver and therefore decrease the optical absorption loss of multilayer metamaterial slabs. Furthermore, multilayer grating structures are studied to enhance the optical transmission and also tune the location of ENZ wavelength. The demonstrated near-infrared ENZ multilayer metamaterial slabs are important for realizing many exotic applications, such as phase front shaping and engineering of photonic density of states.

preprint2013arXiv

Experimental realization of epsilon-near-zero metamaterial slabs with metal-dielectric multilayers

Epsilon-near-zero (ENZ) metamaterial slabs at visible frequencies based on metal-dielectric multilayers are experimentally realized. Transmission, reflection and absorption spectra are measured and used to determine the complex refractive indices and the effective permittivities of the ENZ slabs, which agree with the results obtained from both the numerical simulations and the optical nonlocalities analysis. Furthermore, light propagation in ENZ slabs and directional emission from ENZ prisms are also analyzed. The accurate determination of the ENZ wavelength for metal-dielectric multilayer metamaterial slabs is important for realizing many unique applications, such as phase front manipulation and enhancement of photonic density of states.

preprint2013arXiv

Giant optical nonlocality near the Dirac point in metal-dielectric multilayer metamaterials

The giant optical nonlocality near the Dirac point in lossless metal-dielectric multilayer metamaterials is revealed and investigated through the analysis of the band structure of the multilayer stack in the three-dimensional omega-k space, according to the transfer-matrix method with the optical nonlocal effect. The position of the Dirac point is analytically located in the omega-k space. It is revealed that the emergence of the Dirac point is due to the degeneracy of the symmetric and the asymmetric eigenmodes of the coupled surface plasmon polaritons. The optical nonlocality induced epsilon-near-zero frequency shift for the multilayer stack compared to the effective medium is studied. Furthermore, the giant optical nonlocality around the Dirac point is explored with the iso-frequency contour analysis, while the beam splitting phenomenon at the Dirac point due to the optical nonlocal effect is also demonstrated.

preprint2013arXiv

Nanoscale Imaging of Lithium Ion Distribution During In Situ Operation of Battery Electrode and Electrolyte

A major challenge in the development of new battery materials is understanding their fundamental mechanisms of operation and degradation. Their microscopically inhomogeneous nature calls for characterization tools that provide operando and localized information from individual grains and particles. Here we describe an approach that images the nanoscale distribution of ions during electrochemical charging of a battery in a transmission electron microscope liquid flow cell. We use valence energy-loss spectroscopy to track both solvated and intercalated ions, with electronic structure fingerprints of the solvated ions identified using an ab initio non-linear response theory. Equipped with the new electrochemical cell holder, nanoscale spectroscopy and theory, we have been able to determine the lithiation state of a LiFePO4 electrode and surrounding aqueous electrolyte in real time with nanoscale resolution during electrochemical charge and discharge. We follow lithium transfer between electrode and electrolyte and observe charging dynamics in the cathode that differ among individual particles. This technique represents a general approach for the operando nanoscale imaging of electrochemically active ions in a wide range of electrical energy storage systems.

preprint2013arXiv

New Method to Improve the Accelerating Gradient of Superconducting Cavity

Quench is a common phenomenon in a superconducting cavity and often limits the accelerating gradient of the cavity. Accurate location of the quench site can be located by second sound detection. For multi-cell superconducting cavity, one defect may cause the cell with defect quenches and then the whole cavity quenches. Now we proposed a new method to eliminate the bad influence of the quench cell to the whole cavity.

preprint2013arXiv

Optimization Parameter Design of a Circular e+e- Higgs Factory

In this paper we will show a general method of how to make an optimized parameter design of a circular e+e- Higgs Factory by using analytical expression of maximum beam-beam parameter and beamstrahlung beam lifetime started from given design goal and technical limitations. A parameter space has been explored. Based on beam parameters scan and RF parameters scan, a set of optimized parameter designs for 50 km Circular Higgs Factory (CHF) with different RF frequency was proposed.

preprint2013arXiv

Quantum entanglement in plasmonic waveguides with near-zero mode indices

We investigate the quantum entanglement between two quantum dots in a plasmonic waveguide with near-zero mode index, considering the dependence of concurrence on interdot distance, quantum dot-waveguide frequency detuning and coupling strength ratio. High concurrence is achieved for a wide range of interdot distance due to the near-zero mode index, which largely relaxes the strict requirement of interdot distance in conventional dielectric waveguides or metal nanowires. The proposed quantum dot-waveguide system with near-zero phase variation along the waveguide near the mode cutoff frequency shows very promising potential in quantum optics and quantum information processing.

preprint2013arXiv

Report of the ICFA Beam Dynamics Workshop 'Accelerators for a Higgs Factory: Linear vs. Circular' (HF2012)

This paper is a summary report of the ICFA Beam Dynamics Workshop 'Accelerators for a Higgs Factory: Linear vs. Circular' (HF2012). It discusses four types of accelerators as possible candidates for a Higgs factory: linear e+e- colliders, circular e+e- colliders, muon collider and photon colliders. The comparison includes: physics reach, performance (energy and luminosity), upgrade potential, technology maturity and readiness, and technical challenges requiring further R&D.

preprint2013arXiv

Strongly coupled slow-light polaritons in one-dimensional disordered localized states

Cavity quantum electrodynamics advances the coherent control of a single quantum emitter with a quantized radiation field mode, typically piecewise engineered for the highest finesse and confinement in the cavity field. This enables the possibility of strong coupling for chip-scale quantum processing, but till now is limited to few research groups that can achieve the precision and deterministic requirements for these polariton states. Here we observe for the first time coherent polariton states of strong coupled single quantum dot excitons in inherently disordered one-dimensional localized modes in slow-light photonic crystals. Large vacuum Rabi splittings up to 311 μeV are observed, one of the largest avoided crossings in the solid-state. Our tight-binding models with quantum impurities detail these strong localized polaritons, spanning different disorder strengths, complementary to model-extracted pure dephasing and incoherent pumping rates. Such disorder-induced slow-light polaritons provide a platform towards coherent control, collective interactions, and quantum information processing.

preprint2013arXiv

Sum-Rate Maximization with Minimum Power Consumption for MIMO DF Two-Way Relaying: Part I - Relay Optimization

The problem of power allocation is studied for a multiple-input multiple-output (MIMO) decode-and-forward (DF) two-way relaying system consisting of two source nodes and one relay. It is shown that achieving maximum sum-rate in such a system does not necessarily demand the consumption of all available power at the relay. Instead, the maximum sum-rate can be achieved through efficient power allocation with minimum power consumption. Deriving such power allocation, however, is nontrivial due to the fact that it generally leads to a nonconvex problem. In Part I of this two-part paper, a sum-rate maximizing power allocation with minimum power consumption is found for MIMO DF two-way relaying, in which the relay optimizes its own power allocation strategy given the power allocation strategies of the source nodes. An algorithm is proposed for efficiently finding the optimal power allocation of the relay based on the proposed idea of relative water-levels. The considered scenario features low complexity due to the fact that the relay optimizes its power allocation without coordinating the source nodes. As a trade-off for the low complexity, it is shown that there can be waste of power at the source nodes because of no coordination between the relay and the source nodes. Simulation results demonstrate the performance of the proposed algorithm and the effect of asymmetry on the considered system.

preprint2012arXiv

Giant Transverse Optical Forces in Nanoscale Slot Waveguides of Hyperbolic Metamaterials

Here we demonstrate that giant transverse optical forces can be generated in nanoscale slot waveguides of hyperbolic metamaterials, with more than two orders of magnitude stronger compared to the force created in conventional silicon slot waveguides, due to the nanoscale optical field enhancement and the extreme optical energy compression within the air slot region. Both numerical simulation and analytical treatment are carried out to study the dependence of the optical forces on the waveguide geometries and the metamaterial permittivity tensors, including the attractive optical forces for the symmetric modes and the repulsive optical forces for the anti-symmetric modes. The significantly enhanced transverse optical forces result from the strong optical mode coupling strength between two metamaterial waveguides, which can be explained with an explicit relation derived from the coupled mode theory. Moreover, the calculation on realistic metal-dielectric multilayer structures indicates that the predicted giant optical forces are achievable in experiments, which will open the door for various optomechanical applications in nanoscale, such as optical nanoelectromechanical systems, optical sensors and actuators.

preprint2012arXiv

Infrared perfect absorber based on nanowire metamaterial cavities

An infrared perfect absorber based on gold nanowire metamaterial cavities array on a gold ground plane is designed. The metamaterial made of gold nanowires embedded in alumina host exhibits an effective permittivity with strong anisotropy, which supports cavity resonant modes of both electric dipole and magnetic dipole. The impedance of the cavity modes matches the incident plane wave in free space, leading to nearly perfect light absorption. The incident optical energy is efficiently converted into heat so that the local temperature of the absorber will increase. Simulation results show that the designed metamaterial absorber is polarization-insensitive and nearly omnidirectional for the incident angle.

preprint2012arXiv

Nanoscale Metamaterial Optical Waveguides with Ultrahigh Refractive Indices

We propose deep-subwavelength optical waveguides based on metal-dielectric multilayer indefinite metamaterials with ultrahigh effective refractive indices. Waveguide modes with different mode orders are systematically analyzed with numerical simulations based on both metal-dielectric multilayer structures and the effective medium approach. The dependences of waveguide mode indices, propagation lengths and mode areas on different mode orders, free space wavelengths and sizes of waveguide cross sections are studied. Furthermore, waveguide modes are also illustrated with iso-frequency contours in the wave vector space in order to investigate the mechanism of waveguide mode cutoff for high order modes. The deep-subwavelength optical waveguide with a size smaller than λ0/50 and a mode area in the order of 10-4 λ02 is realized, and an ultrahigh effective refractive index up to 62.0 is achieved at the telecommunication wavelength. This new type of metamaterial optical waveguide opens up opportunities for various applications in enhanced light-matter interactions.

preprint2012arXiv

Sum-Rate Maximization with Minimum Power Consumption for MIMO DF Two-Way Relaying: Part II - Network Optimization

In Part II of this two-part paper, a sum-rate-maximizing power allocation with minimum power consumption is found for multiple-input multiple-output (MIMO) decode-and-forward (DF) two-way relaying (TWR) in a network optimization scenario. In this scenario, the relay and the source nodes jointly optimize their power allocation strategies to achieve network optimality. Unlike the relay optimization scenario considered in part I which features low complexity but does not achieve network optimality, the network-level optimal power allocation can be achieved in the network optimization scenario at the cost of higher complexity. The network optimization problem is considered in two cases each with several subcases. It is shown that the considered problem, which is originally nonconvex, can be transferred into different convex problems for all but two subcases. For the remaining two subcases, one for each case, it is proved that the optimal strategies for the source nodes and the relay must satisfy certain properties. Based on these properties, an algorithm is proposed for finding the optimal solution. The effect of asymmetry in the number of antennas, power limits, and channel statistics is also considered. Such asymmetry is shown to have a negative effect on both the achievable sum-rate and the power allocation efficiency in MIMO DF TWR. Simulation results demonstrate the performance of the proposed algorithm and the effect of asymmetry in the system.

preprint2011arXiv

A conventional positron source for International Linear Collider

A possible solution to realize a conventional positron source driven by a several-GeV electron beam for the International Linear Collider is proposed. A 300 Hz electron linac is employed to create positrons with stretching pulse length in order to cure target thermal load. ILC requires about 2600 bunches in a train which pulse length is 1 ms. Each pulse of the 300 Hz linac creates about 130 bunches, then 2600 bunches are created in 63 ms. Optimized parameters such as drive beam energy, beam size, and target thickness, are discussed assuming a L-band capture system to maximize the capture efficiency and to mitigate the target thermal load. A slow rotating tungsten disk is employed as positron generation target.

preprint2011arXiv

Kinetic Stable Delaunay Graphs

We consider the problem of maintaining the Euclidean Delaunay triangulation $\DT$ of a set $P$ of $n$ moving points in the plane, along algebraic trajectories of constant description complexity. Since the best known upper bound on the number of topological changes in the full $\DT$ is nearly cubic, we seek to maintain a suitable portion of it that is less volatile yet retains many useful properties. We introduce the notion of a stable Delaunay graph, which is a dynamic subgraph of the Delaunay triangulation. The stable Delaunay graph (a) is easy to define, (b) experiences only a nearly quadratic number of discrete changes, (c) is robust under small changes of the norm, and (d) possesses certain useful properties. The stable Delaunay graph ($\SDG$ in short) is defined in terms of a parameter $α>0$, and consists of Delaunay edges $pq$ for which the angles at which $p$ and $q$ see their Voronoi edge $e_{pq}$ are at least $α$. We show that (i) $\SDG$ always contains at least roughly one third of the Delaunay edges; (ii) it contains the $β$-skeleton of $P$, for $β=1+Ω(α^2)$; (iii) it is stable, in the sense that its edges survive for long periods of time, as long as the orientations of the segments connecting (nearby) points of $P$ do not change by much; and (iv) stable Delaunay edges remain stable (with an appropriate redefinition of stability) if we replace the Euclidean norm by any sufficiently close norm. In particular, we can approximate the Euclidean norm by a polygonal norm (namely, a regular $k$-gon, with $k=Θ(1/α)$), and keep track of a Euclidean $\SDG$ by maintaining the full Delaunay triangulation of $P$ under the polygonal norm. We describe two kinetic data structures for maintaining $\SDG$. Both structures use $O^*(n)$ storage and process $O^*(n^2)$ events during the motion, each in $O^*(1)$ time.

preprint2011arXiv

Multi-confocal Fluorescence Correlation Spectroscopy : experimental demonstration and potential applications for living cell measurements

We report, for the first time, a multi-confocal Fluorescence Correlation Spectroscopy (mFCS) technique which allows parallel measurements at different locations, by combining a Spatial Light Modulator (SLM), with an Electron Multiplying-CCD camera (EM-CCD). The SLM is used to produce a series of laser spots, while the pixels of the EM-CCD play the roles of virtual pinholes. The phase map addressed to the SLM is calculated by using the spherical wave approximation and makes it possible to produce several diffraction limited laser spots, either aligned or spread over the field of view. To attain fast enough imaging rates, the camera has been used in different acquisition modes, the fastest of which leads to a time resolution of 100 $μ$s. We qualified the experimental set-up by using solutions of sulforhodamine G in glycerol and demonstrated that the observation volumes are similar to that of a standard confocal set-up. To demonstrate that our mFCS method is suitable for intracellular studies, experiments have been conducted on two stable cell lines: mouse embryonic fibroblasts expressing eGFP-actin and H1299 cells expressing the heat shock factor fusion protein HSF1-eGFP. In the first case we could recover, by analyzing the auto-correlation curves, the diffusion constant of G-actin within the cytoplasm, although we were also sensitive to the complex network of interactions with F-actin. Concerning HSF1, we could clearly observe the modifications of the number of molecules and of the HSF1 dynamics during heat shock.

preprint2010arXiv

Design of dispersive optomechanical coupling and cooling in ultrahigh-Q/V slot-type photonic crystal cavities

We describe the strong optomechanical dynamical interactions in ultrahigh-Q/V slot-type photonic crystal cavities. The dispersive coupling is based on a mode-gap photonic crystal cavities with light localization in an air mode with 0.02(lambda/n)3 modal volumes while preserving optical cavity Q up to 5 x 106. The mechanical mode is modeled to have fundamental resonance omega_m/2pi of 460 MHz and a quality factor Qm estimated at 12,000. For this slot-type optomechanical cavity, the dispersive coupling gom is numerically computed at up to 940 GHz/nm (Lom of 202 nm) for the fundamental optomechanical mode. Dynamical parametric oscillations for both cooling and amplification, in the resolved and unresolved sideband limit, are examined numerically, along with the displacement spectral density and cooling rates for the various operating parameters.

preprint2009arXiv

Cooperative Precoding/Resource Allocation Games under Spectral Mask and Total Power Constraints

The use of orthogonal signaling schemes such as time-, frequency-, or code-division multiplexing (T-, F-, CDM) in multi-user systems allows for power-efficient simple receivers. It is shown in this paper that by using orthogonal signaling on frequency selective fading channels, the cooperative Nash bargaining (NB)-based precoding games for multi-user systems, which aim at maximizing the information rates of all users, are simplified to the corresponding cooperative resource allocation games. The latter provides additional practically desired simplifications to transmitter design and significantly reduces the overhead during user cooperation. The complexity of the corresponding precoding/resource allocation games, however, depends on the constraints imposed on the users. If only spectral mask constraints are present, the corresponding cooperative NB problem can be formulated as a convex optimization problem and solved efficiently in a distributed manner using dual decomposition based algorithm. However, the NB problem is non-convex if total power constraints are also imposed on the users. In this case, the complexity associate with finding the NB solution is unacceptably high. Therefore, the multi-user systems are categorized into bandwidth- and power-dominant based on a bottleneck resource, and different manners of cooperation are developed for each type of systems for the case of two-users. Such classification guarantees that the solution obtained in each case is Pareto-optimal and actually can be identical to the optimal solution, while the complexity is significantly reduced. Simulation results demonstrate the efficiency of the proposed cooperative precoding/resource allocation strategies and the reduced complexity of the proposed algorithms.

preprint2009arXiv

Cryogenic spectroscopy of ultra-low density colloidal lead chalcogenide quantum dots on chip-scale optical cavities towards single quantum dot near-infrared cavity QED

We present evidence of cavity quantum electrodynamics from a sparse density of strongly quantum-confined Pb-chalcogenide nanocrystals (between 1 and 10) approaching single-dot levels on moderately high-Q mesoscopic silicon optical cavities. Operating at important near-infrared (1500-nm) wavelengths, large enhancements are observed from devices and strong modifications of the QD emission are achieved. Saturation spectroscopy of coupled QDs is observed at 77K, highlighting the modified nanocrystal dynamics for quantum information processing.

preprint2009arXiv

The Emergence of Sparse Spanners and Greedy Well-Separated Pair Decomposition

A spanner graph on a set of points in $R^d$ contains a shortest path between any pair of points with length at most a constant factor of their Euclidean distance. In this paper we investigate new models and aim to interpret why good spanners 'emerge' in reality, when they are clearly built in pieces by agents with their own interests and the construction is not coordinated. Our main result is to show that if edges are built in an arbitrary order but an edge is built if and only if its endpoints are not 'close' to the endpoints of an existing edge, the graph is a $(1 + \eps)$-spanner with a linear number of edges, constant average degree, and the total edge length as a small logarithmic factor of the cost of the minimum spanning tree. As a side product, we show a simple greedy algorithm for constructing optimal size well-separated pair decompositions that may be of interest on its own.

preprint2008arXiv

On the quantization accuracy of the acoustoelectric current

By deriving analytical formulae for the quantization accuracy of the acoustoelectric current, we reveal that: 1) the flatness of the current plateau for the typical present devices has reached the theoretical limit of about 100ppm over a 1/1000 change of the gate voltage; 2) increasing the transport channel length, and counterintuitively, increasing the acoustic wavelength as well, would improve the quantization accuracy, and very promisingly up to 0.01ppm as required for a quantum current standard.

preprint2008arXiv

Temperature-tuning of near-infrared monodisperse quantum dot solids at 1.5 um for controllable Forster energy transfer

We present the first time-resolved cryogenic observations of Forster energy transfer in large, monodisperse lead sulphide quantum dots with ground state transitions near 1.5 um (0.83 eV), in environments from 160 K to room temperature. The observed temperature-dependent dipole-dipole transfer rate occurs in the range of (30-50 ns)^(-1), measured with our confocal single-photon counting setup at 1.5 um wavelengths. By temperature-tuning the dots, 94% efficiency of resonant energy transfer can be achieved for donor dots. The resonant transfer rates match well with proposed theoretical models.

preprint2006arXiv

Weak coupling interactions of colloidal lead sulphide nanocrystals with silicon photonic crystal nanocavities near 1.55 microns at room temperature

We observe the weak coupling of lead sulphide nanocrystals to localized defect modes of 2-dimensional silicon nanocavities. Cavity resonances characterized with ensemble nanocrystals are verified with cold-cavity measurements using integrated waveguides. Polarization dependence of the cavity field modes is observed. The linewidths measured in coupling experiments are broadened in comparison to the cold-cavity characterization, partly due to large homogeneous linewidths of the nanocrystals. The calculated Purcell factor for a single exciton is 75, showing promise toward applications in single photon systems. These novel light sources operate near 1.55 micron wavelengths at room temperature, permitting integration with current fiber communications networks.

Jie Gao

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74 published item(s)

Can Vision Language Models Be Adaptive in Mathematics Education? A Learner Model-based Rubric Study

How to Interpret Agent Behavior

Holistic Network Virtualization and Pervasive Network Intelligence for 6G

Understanding the Complexity and Its Impact on Testing in ML-Enabled Systems

From 996 to 007: Challenges of Working from Home During the Epidemic in China

Injection induced by coaxial laser interference in laser wakefield accelerators

Investigation of spin rotators in CEPC at the Z-pole

Logically at Factify 2022: Multimodal Fact Verification

On Cyclic Solutions to the Min-Max Latency Multi-Robot Patrolling Problem

Optimal Local Bayesian Differential Privacy over Markov Chains

Social Network Community Detection Based on Textual Content Similarity and Sentimental Tendency

Study Overview for Super Proton-Proton Collider

Subspace Differential Privacy

TCR: A Transformer Based Deep Network for Predicting Cancer Drugs Response

The Optimal Beam-loading in Two-bunch Nonlinear Plasma Wakefield Accelerators

Time Window Frechet and Metric-Based Edit Distance for Passively Collected Trajectories

Application-driven Privacy-preserving Data Publishing with Correlated Attributes

Scissor-cross ionization injection in laser wakefield accelerators

An Efficient QP Variable Convolutional Neural Network Based In-loop Filter for Intra Coding

Approximation Algorithms for Multi-Robot Patrol-Scheduling with Min-Max Latency

Cutting Polygons into Small Pieces with Chords: Laser-Based Localization

Data Inference from Encrypted Databases: A Multi-dimensional Order-Preserving Matching Approach

Energy-Efficient UAV-Assisted Mobile Edge Computing: Resource Allocation and Trajectory Optimization

Low-Latency and Fresh Content Provision in Information-Centric Vehicular Networks

RP-DNN: A Tweet level propagation context based deep neural networks for early rumor detection in Social Media

Streaming Chunk-Aware Multihead Attention for Online End-to-End Speech Recognition

The Design of Dynamic Probabilistic Caching with Time-Varying Content Popularity

Visual Perception Model for Rapid and Adaptive Low-light Image Enhancement

Analytical estimation of ATF beam halo distribution

Beam halo study on ATF damping ring

Capacitated Kinetic Clustering in Mobile Networks by Optimal Transportation Theory

Cavity and HOM Coupler Design for CEPC

Concept for a Future Super Proton-Proton Collider

Diffraction-free optical beam propagation with near-zero phase variation in extremely anisotropic metamaterials

HOMs Simulation and Measurement Results of IHEP02 Cavity

Method Study of Parameter Choice for a Circular Proton-Proton Collider

Nonlocal effective medium analysis in symmetric metal-dielectric multilayer metamaterials

Nonlocal effective medium approximation for metallic nanorod metamaterials

Ricci Curvature of the Internet Topology

Space Filling Curves for 3D Sensor Networks with Complex Topology

Stable Delaunay Graphs

Study on CEPC performances with different collision energies and geometric layouts

Complex Contagions in Kleinberg's Small World Model

Efficient Strategies for Single/Multi-Target Jamming on MIMO Gaussian Channels

How Complex Contagions Spread Quickly in the Preferential Attachment Model and Other Time-Evolving Networks

Realizing broadband electromagnetic transparency with a graded-permittivity sphere

Study of alternative ILC final focus optical configurations

A Variational Principle for Improving 2D Triangle Meshes based on Hyperbolic Volume

Anomalous optical coupling between two silicon wires of a slot waveguide in epsilon-near-zero metamaterials

Broadband Epsilon-Near-Zero Metamaterials with Step-Like Metal-Dielectric Multilayer Structures

Experimental demonstration of near-infrared epsilon-near-zero multilayer metamaterial slabs

Experimental realization of epsilon-near-zero metamaterial slabs with metal-dielectric multilayers

Giant optical nonlocality near the Dirac point in metal-dielectric multilayer metamaterials

Nanoscale Imaging of Lithium Ion Distribution During In Situ Operation of Battery Electrode and Electrolyte

New Method to Improve the Accelerating Gradient of Superconducting Cavity

Optimization Parameter Design of a Circular e+e- Higgs Factory

Quantum entanglement in plasmonic waveguides with near-zero mode indices

Report of the ICFA Beam Dynamics Workshop 'Accelerators for a Higgs Factory: Linear vs. Circular' (HF2012)

Strongly coupled slow-light polaritons in one-dimensional disordered localized states

Sum-Rate Maximization with Minimum Power Consumption for MIMO DF Two-Way Relaying: Part I - Relay Optimization

Giant Transverse Optical Forces in Nanoscale Slot Waveguides of Hyperbolic Metamaterials

Infrared perfect absorber based on nanowire metamaterial cavities

Nanoscale Metamaterial Optical Waveguides with Ultrahigh Refractive Indices

Sum-Rate Maximization with Minimum Power Consumption for MIMO DF Two-Way Relaying: Part II - Network Optimization

A conventional positron source for International Linear Collider

Kinetic Stable Delaunay Graphs

Multi-confocal Fluorescence Correlation Spectroscopy : experimental demonstration and potential applications for living cell measurements

Design of dispersive optomechanical coupling and cooling in ultrahigh-Q/V slot-type photonic crystal cavities

Cooperative Precoding/Resource Allocation Games under Spectral Mask and Total Power Constraints

Cryogenic spectroscopy of ultra-low density colloidal lead chalcogenide quantum dots on chip-scale optical cavities towards single quantum dot near-infrared cavity QED

The Emergence of Sparse Spanners and Greedy Well-Separated Pair Decomposition

On the quantization accuracy of the acoustoelectric current

Temperature-tuning of near-infrared monodisperse quantum dot solids at 1.5 um for controllable Forster energy transfer

Weak coupling interactions of colloidal lead sulphide nanocrystals with silicon photonic crystal nanocavities near 1.55 microns at room temperature