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Lei Chen

Publications and source records attributed to Lei Chen.

At least 649 records · Page 36Linked to original sources

Probing the Flat Band of Optically-Trapped Spin-Orbital Coupled Bose Gases Using Bragg Spectroscopy

Motivated by the recent efforts in creating the flat band in ultracold atomic systems, we investigate how to probe the flat band in an optically-trapped spin-orbital coupled Bose-Einstein condensate using Bragg spectroscopy. We have found that the excitation spectrum and the dynamic structure factor of the condensate alter dramatically, when the band structure exhibits various level of flatness. In particular, when the band exhibits perfect flatness around the band minima corresponding to a near infinite effective mass, a quadratic dispersion emerges in the low-energy excitation spectrum; in sharp contrast, for the opposite case when an ordinary band is present, the familiar linear dispersion arises. Such linear-to-quadratic crossover in the energy spectrum presents a striking manifestation of the transition of an ordinary band into a flat band, thereby allows the direct probe of the flat band by using Bragg spectroscopy.

cond-mat.quant-gas↗

Non-equilibrium dynamics of an ultracold Bose gas under a multi-pulsed quantum quench in interaction

We investigate the nonequilibrium dynamical properties of a weakly-interacting Bose gas at zero temperature under the multi-pulsed quantum quench in interaction by calculating one-body, two-body correlation functions and Tan's contact of the model system. The multi-pulsed quench is represented as follows: first suddenly quenching the interatomic interaction from $g_{i}$ to $g_{f}$ at time $t=0$, holding time $t$, and then suddenly quenching interaction from $g_{f}$ back to $g_{i}$, holding the time $t$ sequence $n$ times. In particular, two typical kinds of quenching parameters are chosen, corresponding to $(g_{i}/g_{f}>1)$ and $(g_{i}/g_{f}<1)$ respectively. We find that the more the quenching times of $n$ are, the more the excitations are excited, which suggests that the multi-pulsed QQ is more powerful way of studying the non-equilibrium dynamics of many-body quantum system than the `one-off' quantum quench. Finally, we discuss the ultra-short-range properties of the two-body correlation function after the $n$th quenching, which can be used to probe the `Tan'scontact' in experiments. All our calculations can be tested in current cold atom experiments.

cond-mat.quant-gas↗

Unusual behavior of sound velocity of a Bose gas in an optical superlattice at quasi-one-dimension

A Bose gas trapped in a one-dimensional optical superlattice has emerged as a novel superfluid characterized by tunable lattice topologies and tailored band structures. In this work, we focus on the propagation of sound in such a novel system and have found new features on sound velocity, which arises from the interplay between the two lattices with different periodicity and is not present in the case of a condensate in a monochromatic optical lattice. Particularly, this is the first time that the sound velocity is found to first increase and then decrease as the superlattice strength increases even at one dimension. Such unusual behavior can be analytically understood in terms of the competition between the decreasing compressibility and the increasing effective mass due to the increasing superlattice strength. This result suggests a new route to engineer the sound velocity by manipulating the superlattice's parameters. All the calculations based on the mean-field theory are justified by checking the exponent $γ$ of the off-diagonal one-body density matrix that is much smaller than 1. Finally, the conditions for possible experimental realization of our scenario are also discussed.

cond-mat.quant-gas↗

Probing Sound Speed of an Optically-Trapped Bose Gas with Periodically Modulated Interactions by Bragg Spectroscopy

A Bose-Einstein condensate (BEC) with periodically modulated interactions (PMI) has emerged as a novel kind of periodic superfluid, which has been recently experimentally created using optical Feshbach resonance. In this paper, we are motivated to investigate the superfluidity of a BEC with PMI trapped in an optical lattice (OL). In particular, we explore the effects of PMI on the sound speed and the dynamical structure factor of the model system. Our numerical results, combined with the analytical results in both the weak-potential limit and the tight-binding limit, have shown that the PMI can strongly modify the sound speed of a BEC. Moreover, we have shown that the effects of PMI on sound speed can be experimentally probed via the dynamic structure factor, where the excitation strength toward the first Bogoliubov band exhibits marked difference from the non- PMI one. Our predictions of the effects of PMI on the sound speed can be tested using the Bragg spectroscopy.

cond-mat.quant-gas↗

Quench Dynamics of Three-Dimensional Disordered Bose Gases: Condensation, Superfluidity and Fingerprint of Dynamical Bose Glass

In an equilibrium three-dimensional (3D) disordered condensate, it's well established that disorder can generate an amount of normal fluid equaling to $\frac{4}{3}$ of the condensate depletion. The concept that the superfluid is more volatile to the existence of disorder than the condensate is crucial to the understanding of Bose glass phase. In this Letter, we show that, by bringing a weakly disordered 3D condensate to nonequilibrium regime via a quantum quench in the interaction, disorder can destroy superfluid significantly more, leading to a steady state in which the normal fluid density far exceeds $\frac{4}{3}$ of the condensate depletion. This suggests a possibility of engineering Bose Glass in the dynamic regime. As both the condensate density and superfluid density are measurable quantities, our results allow an experimental demonstration of the dramatized interplay between the disorder and interaction in the nonequilibrium scenario.

cond-mat.quant-gas↗

Majorana zero modes on a 1D chain for quantum computation

Numerical calculations for Majorana zero modes on a one-dimensional chain are performed using the technique of block diagonalization for general parameter settings. It is found that Majorana zero modes occur near the ends of the chain and decay exponentially away from the ends. The phase diagrams show that Majorana zero modes of a long-enough chain indeed have a parameter domain of $2t>|μ|$ as predicted from the bulk property of the chain, but a short chain has a much smaller parameter domain than the prediction. Through a numerical simulation Majorana zero modes are found to be robust under the disturbance of noise. Finally the reversion of the parity of the ground states is studied by applying a bias voltage on the quantum dot at an end of the chain. It is found that for a weak coupling between a chain and a quantum dot the parity of the ground states can be reversed through adiabatically tuning the bias voltage.

quant-ph↗

Is getting the right answer just about choosing the right words? The role of syntactically-informed features in short answer scoring

Developments in the educational landscape have spurred greater interest in the problem of automatically scoring short answer questions. A recent shared task on this topic revealed a fundamental divide in the modeling approaches that have been applied to this problem, with the best-performing systems split between those that employ a knowledge engineering approach and those that almost solely leverage lexical information (as opposed to higher-level syntactic information) in assigning a score to a given response. This paper aims to introduce the NLP community to the largest corpus currently available for short-answer scoring, provide an overview of methods used in the shared task using this data, and explore the extent to which more syntactically-informed features can contribute to the short answer scoring task in a way that avoids the question-specific manual effort of the knowledge engineering approach.

cs.CL↗

Probabilistic Nearest Neighbor Queries on Uncertain Moving Object Trajectories

Nearest neighbor (NN) queries in trajectory databases have received significant attention in the past, due to their application in spatio-temporal data analysis. Recent work has considered the realistic case where the trajectories are uncertain; however, only simple uncertainty models have been proposed, which do not allow for accurate probabilistic search. In this paper, we fill this gap by addressing probabilistic nearest neighbor queries in databases with uncertain trajectories modeled by stochastic processes, specifically the Markov chain model. We study three nearest neighbor query semantics that take as input a query state or trajectory $q$ and a time interval. For some queries, we show that no polynomial time solution can be found. For problems that can be solved in PTIME, we present exact query evaluation algorithms, while for the general case, we propose a sophisticated sampling approach, which uses Bayesian inference to guarantee that sampled trajectories conform to the observation data stored in the database. This sampling approach can be used in Monte-Carlo based approximation solutions. We include an extensive experimental study to support our theoretical results.

cs.DB↗

Motionless Phase Stepping in X-Ray Phase Contrast Imaging with a Compact Source

X-ray phase contrast imaging offers a way to visualize the internal structures of an object without the need to deposit any radiation, and thereby alleviate the main concern in x-ray diagnostic imaging procedures today. Grating-based differential phase contrast imaging techniques are compatible with compact x-ray sources, which is a key requirement for the majority of clinical x-ray modalities. However, these methods are substantially limited by the need for mechanical phase stepping. We describe an electromagnetic phase stepping method that eliminates mechanical motion, and thus removing the constraints in speed, accuracy and flexibility. The method is broadly applicable to both projection and tomography imaging modes. The transition from mechanical to electromagnetic scanning should greatly facilitate the translation of x-ray phase contrast techniques into mainstream applications.

physics.med-ph↗

Active Consensus over Sensor Networks via Randomized Communication

Distributed consensus has been widely studied for sensor network applications. Whereas the asymptotic convergence rate has been extensively explored in prior work, other important and practical issues, including energy efficiency and link reliability, have received relatively little attention. In this paper, we present a distributed consensus approach that can achieve a good balance between convergence rate and energy efficiency. The approach selects a subset of links that significantly contribute to the formation of consensus at each iteration, thus adapting the network's topology dynamically to the changes of the sensor states. A global optimization problem is formulated for optimal link selection, which is subsequently factorized into sub-problems that can be solved locally, and practically via approximation. An algorithm is derived to solve the approximation efficiently, using quadratic programming (QP) relaxation and random sampling. Simulations on networks of different types demonstrate that the proposed method reduces the communication energy costs without significantly impacting the convergence rate and that the approach is robust to link failures.

cs.NI↗

Efficient Data Gathering in Wireless Sensor Networks Based on Matrix Completion and Compressive Sensing

Gathering data in an energy efficient manner in wireless sensor networks is an important design challenge. In wireless sensor networks, the readings of sensors always exhibit intra-temporal and inter-spatial correlations. Therefore, in this letter, we use low rank matrix completion theory to explore the inter-spatial correlation and use compressive sensing theory to take advantage of intra-temporal correlation. Our method, dubbed MCCS, can significantly reduce the amount of data that each sensor must send through network and to the sink, thus prolong the lifetime of the whole networks. Experiments using real datasets demonstrate the feasibility and efficacy of our MCCS method.

cs.NI↗

Observation of Correlation between Route to Formation, Coherence, Noise, and Communication Performance of Kerr Combs

Microresonator optical frequency combs based on cascaded four-wave mixing are potentially attractive as a multi-wavelength source for on-chip optical communications. In this paper we compare time domain coherence, radio-frequency (RF) intensity noise, and individual line optical communications performance for combs generated from two different silicon nitride microresonators. The comb generated by one microresonator forms directly with lines spaced by a single free spectral range (FSR) and exhibits high coherence, low noise, and excellent 10 Gbit/s optical communications results. The comb generated by the second microresonator forms initially with multiple FSR line spacing, with additional lines later filling to reach single FSR spacing. This comb exhibits degraded coherence, increased intensity noise, and severely degraded communications performance. This study is to our knowledge the first to simultaneously investigate and observe a correlation between the route to comb formation, the coherence, noise, and optical communications performance of a Kerr comb.

physics.optics↗

Efficient Multi-way Theta-Join Processing Using MapReduce

Multi-way Theta-join queries are powerful in describing complex relations and therefore widely employed in real practices. However, existing solutions from traditional distributed and parallel databases for multi-way Theta-join queries cannot be easily extended to fit a shared-nothing distributed computing paradigm, which is proven to be able to support OLAP applications over immense data volumes. In this work, we study the problem of efficient processing of multi-way Theta-join queries using MapReduce from a cost-effective perspective. Although there have been some works using the (key,value) pair-based programming model to support join operations, efficient processing of multi-way Theta-join queries has never been fully explored. The substantial challenge lies in, given a number of processing units (that can run Map or Reduce tasks), mapping a multi-way Theta-join query to a number of MapReduce jobs and having them executed in a well scheduled sequence, such that the total processing time span is minimized. Our solution mainly includes two parts: 1) cost metrics for both single MapReduce job and a number of MapReduce jobs executed in a certain order; 2) the efficient execution of a chain-typed Theta-join with only one MapReduce job. Comparing with the query evaluation strategy proposed in [23] and the widely adopted Pig Latin and Hive SQL solutions, our method achieves significant improvement of the join processing efficiency.

cs.DB↗

Whom to Ask? Jury Selection for Decision Making Tasks on Micro-blog Services

It is universal to see people obtain knowledge on micro-blog services by asking others decision making questions. In this paper, we study the Jury Selection Problem(JSP) by utilizing crowdsourcing for decision making tasks on micro-blog services. Specifically, the problem is to enroll a subset of crowd under a limited budget, whose aggregated wisdom via Majority Voting scheme has the lowest probability of drawing a wrong answer(Jury Error Rate-JER). Due to various individual error-rates of the crowd, the calculation of JER is non-trivial. Firstly, we explicitly state that JER is the probability when the number of wrong jurors is larger than half of the size of a jury. To avoid the exponentially increasing calculation of JER, we propose two efficient algorithms and an effective bounding technique. Furthermore, we study the Jury Selection Problem on two crowdsourcing models, one is for altruistic users(AltrM) and the other is for incentive-requiring users(PayM) who require extra payment when enrolled into a task. For the AltrM model, we prove the monotonicity of JER on individual error rate and propose an efficient exact algorithm for JSP. For the PayM model, we prove the NP-hardness of JSP on PayM and propose an efficient greedy-based heuristic algorithm. Finally, we conduct a series of experiments to investigate the traits of JSP, and validate the efficiency and effectiveness of our proposed algorithms on both synthetic and real micro-blog data.

cs.DB↗

Mining Frequent Itemsets over Uncertain Databases

In recent years, due to the wide applications of uncertain data, mining frequent itemsets over uncertain databases has attracted much attention. In uncertain databases, the support of an itemset is a random variable instead of a fixed occurrence counting of this itemset. Thus, unlike the corresponding problem in deterministic databases where the frequent itemset has a unique definition, the frequent itemset under uncertain environments has two different definitions so far. The first definition, referred as the expected support-based frequent itemset, employs the expectation of the support of an itemset to measure whether this itemset is frequent. The second definition, referred as the probabilistic frequent itemset, uses the probability of the support of an itemset to measure its frequency. Thus, existing work on mining frequent itemsets over uncertain databases is divided into two different groups and no study is conducted to comprehensively compare the two different definitions. In addition, since no uniform experimental platform exists, current solutions for the same definition even generate inconsistent results. In this paper, we firstly aim to clarify the relationship between the two different definitions. Through extensive experiments, we verify that the two definitions have a tight connection and can be unified together when the size of data is large enough. Secondly, we provide baseline implementations of eight existing representative algorithms and test their performances with uniform measures fairly. Finally, according to the fair tests over many different benchmark data sets, we clarify several existing inconsistent conclusions and discuss some new findings.

cs.DB↗

Probing Within Partially Coherent Microcavity Frequency Combs via Optical Pulse Shaping

Recent investigations of microcavity frequency combs based on cascaded four-wave mixing have revealed a link between the evolution of the optical spectrum and the observed temporal coherence. Here we study a silicon nitride microresonator for which the initial four-wave mixing sidebands are spaced by multiple free spectral ranges (FSRs) from the pump, then fill in to yield a comb with single FSR spacing, resulting in partial coherence. By using a pulse shaper to select and manipulate the phase of various subsets of spectral lines, we are able to probe the structure of the coherence within the partially coherent comb. Our data demonstrate strong variation in the degree of mutual coherence between different groups of lines and provide support for a simple model of partially coherent comb formation.

physics.optics↗

Efficient Subgraph Similarity Search on Large Probabilistic Graph Databases

Many studies have been conducted on seeking the efficient solution for subgraph similarity search over certain (deterministic) graphs due to its wide application in many fields, including bioinformatics, social network analysis, and Resource Description Framework (RDF) data management. All these works assume that the underlying data are certain. However, in reality, graphs are often noisy and uncertain due to various factors, such as errors in data extraction, inconsistencies in data integration, and privacy preserving purposes. Therefore, in this paper, we study subgraph similarity search on large probabilistic graph databases. Different from previous works assuming that edges in an uncertain graph are independent of each other, we study the uncertain graphs where edges' occurrences are correlated. We formally prove that subgraph similarity search over probabilistic graphs is #P-complete, thus, we employ a filter-and-verify framework to speed up the search. In the filtering phase,we develop tight lower and upper bounds of subgraph similarity probability based on a probabilistic matrix index, PMI. PMI is composed of discriminative subgraph features associated with tight lower and upper bounds of subgraph isomorphism probability. Based on PMI, we can sort out a large number of probabilistic graphs and maximize the pruning capability. During the verification phase, we develop an efficient sampling algorithm to validate the remaining candidates. The efficiency of our proposed solutions has been verified through extensive experiments.

cs.DB↗

Near-infrared interferometric observation of the Herbig Ae star HD144432 with VLTI/AMBER

We study the sub-AU-scale circumstellar environment of the Herbig Ae star HD144432 with near-infrared (NIR) VLTI/AMBER observations to investigate the structure of its inner dust disk. The interferometric observations were carried out with the AMBER instrument in the H and K band. We interpret the measured H- and K-band visibilities, the near- and mid-infrared visibilities from the literature, and the SED of HD144432 by using geometric ring models and ring-shaped temperature-gradient disk models with power-law temperature distributions. We derived a K-band ring-fit radius of 0.17 \pm 0.01 AU and an H-band radius of 0.18 \pm 0.01 AU (for a distance of 145 pc). This measured K-band radius of \sim0.17 AU lies in the range between the dust sublimation radius of \sim0.13 AU (predicted for a dust sublimation temperature of 1500 K and gray dust) and the prediction of models including backwarming (\sim0.27 AU). We found that an additional extended halo component is required in both the geometric and temperature-gradient modeling. In the best temperature- gradient model, the disk consists of two components. The inner part of the disk is a thin ring with an inner radius of \sim0.21 AU, a temperature of \sim1600 K, and a ring thickness \sim0.02 AU. The outer part extends from \sim1 AU to \sim10 AU with an inner temperature of \sim400 K. We find that the disk is nearly face-on with an inclination angle of < 28 degree. Our temperature-gradient modeling suggests that the NIR excess is dominated by emission from a narrow, bright rim located at the dust sublimation radius, while an extended halo component contributes \sim6% to the total flux at 2 μm. The MIR model emission has a two-component structure with \sim20% flux from the inner ring and the rest from the outer part. This two-component structure suggests a disk gap, which is possibly caused by the shadow of a puffed-up inner rim.

astro-ph.SR↗