arXiv subjects

Wei Zheng

Publications and source records attributed to Wei Zheng.

At least 73 records · Page 4Linked to original sources

arXiv2023

Batch mode active learning for efficient parameter estimation

For many tasks of data analysis, we may only have the information of the explanatory variable and the evaluation of the response values are quite expensive. While it is impractical or too costly to obtain the responses of all units, a natural remedy is to judiciously select a good sample of units, for which the responses are to be evaluated. In this paper, we adopt the classical criteria in design of experiments to quantify the information of a given sample regarding parameter estimation. Then, we provide a theoretical justification for approximating the optimal sample problem by a continuous problem, for which fast algorithms can be further developed with the guarantee of global convergence. Our results have the following novelties: (i) The statistical efficiency of any candidate sample can be evaluated without knowing the exact optimal sample; (ii) It can be applied to a very wide class of statistical models; (iii) It can be integrated with a broad class of information criteria; (iv) It is much faster than existing algorithms. $(v)$ A geometric interpretation is adopted to theoretically justify the relaxation of the original combinatorial problem to continuous optimization problem.

stat.CO↗

arXiv2023

Disruption Precursor Onset Time Study Based on Semi-supervised Anomaly Detection

The full understanding of plasma disruption in tokamaks is currently lacking, and data-driven methods are extensively used for disruption prediction. However, most existing data-driven disruption predictors employ supervised learning techniques, which require labeled training data. The manual labeling of disruption precursors is a tedious and challenging task, as some precursors are difficult to accurately identify, limiting the potential of machine learning models. To address this issue, commonly used labeling methods assume that the precursor onset occurs at a fixed time before the disruption, which may not be consistent for different types of disruptions or even the same type of disruption, due to the different speeds at which plasma instabilities escalate. This leads to mislabeled samples and suboptimal performance of the supervised learning predictor. In this paper, we present a disruption prediction method based on anomaly detection that overcomes the drawbacks of unbalanced positive and negative data samples and inaccurately labeled disruption precursor samples. We demonstrate the effectiveness and reliability of anomaly detection predictors based on different algorithms on J-TEXT and EAST to evaluate the reliability of the precursor onset time inferred by the anomaly detection predictor. The precursor onset times inferred by these predictors reveal that the labeling methods have room for improvement as the onset times of different shots are not necessarily the same. Finally, we optimize precursor labeling using the onset times inferred by the anomaly detection predictor and test the optimized labels on supervised learning disruption predictors. The results on J-TEXT and EAST show that the models trained on the optimized labels outperform those trained on fixed onset time labels.

physics.plasm-ph↗

arXiv2023

Mode softening in time-crystalline transitions of open quantum systems

In this work, we generalize the concept of roton softening mechanism of spatial crystalline transition to time crystals in open quantum systems. We study a dissipative Dicke model as a prototypical example, which exhibits both continuous time crystal and discrete time crystal phases.We found that on approaching the time crystalline transition, the response function diverges at a finite frequency, which determines the period of the upcoming time crystal. This divergence can be understood as softening of the relaxation rate of the corresponding collective excitation, which can be clearly seen by the poles of the response function on the complex plane. Using this mode softening analysis, we predict a time quasi-crystal phase in our model, in which the self-organized period and the driving period are incommensurate.

cond-mat.quant-gas↗

arXiv2023

Self-Attentive Sequential Recommendation with Cheap Causal Convolutions

Sequential Recommendation is a prominent topic in current research, which uses user behavior sequence as an input to predict future behavior. By assessing the correlation strength of historical behavior through the dot product, the model based on the self-attention mechanism can capture the long-term preference of the sequence. However, it has two limitations. On the one hand, it does not effectively utilize the items' local context information when determining the attention and creating the sequence representation. On the other hand, the convolution and linear layers often contain redundant information, which limits the ability to encode sequences. In this paper, we propose a self-attentive sequential recommendation model based on cheap causal convolution. It utilizes causal convolutions to capture items' local information for calculating attention and generating sequence embedding. It also uses cheap convolutions to improve the representations by lightweight structure. We evaluate the effectiveness of the proposed model in terms of both accurate and calibrated sequential recommendation. Experiments on benchmark datasets show that the proposed model can perform better in single- and multi-objective recommendation scenarios.

cs.IR↗

arXiv2023

Probing quantum many-body correlations by universal ramping dynamics

Ramping a physical parameter is one of the most common experimental protocols in studying a quantum system, and ramping dynamics has been widely used in preparing a quantum state and probing physical properties. Here, we present a novel method of probing quantum many-body correlation by ramping dynamics. We ramp a Hamiltonian parameter to the same target value from different initial values and with different velocities, and we show that the first-order correction on the finite ramping velocity is universal and path-independent, revealing a novel quantum many-body correlation function of the equilibrium phases at the target values. We term this method as the non-adiabatic linear response since this is the leading order correction beyond the adiabatic limit. We demonstrate this method experimentally by studying the Bose-Hubbard model with ultracold atoms in three-dimensional optical lattices. Unlike the conventional linear response that reveals whether the quasi-particle dispersion of a quantum phase is gapped or gapless, this probe is more sensitive to whether the quasi-particle lifetime is long enough such that the quantum phase possesses a well-defined quasi-particle description. In the Bose-Hubbard model, this non-adiabatic linear response is significant in the quantum critical regime where well-defined quasi-particles are absent. And in contrast, this response is vanishingly small in both superfluid and Mott insulators which possess well-defined quasi-particles. Because our proposal uses the most common experimental protocol, we envision that our method can find broad applications in probing various quantum systems.

cond-mat.quant-gas↗

arXiv2022

Fast On-orbit Pulse Phase Estimation of X-ray Crab Pulsar for XNAV Flight Experiments

The recent flight experiments with Neutron Star Interior Composition Explorer (\textit{NICER}) and \textit{Insight}-Hard X-ray Modulation Telescope (\textit{Insight}-HXMT) have demonstrated the feasibility of X-ray pulsar-based navigation (XNAV) in the space. However, the current pulse phase estimation and navigation methods employed in the above flight experiments are computationally too expensive for handling the Crab pulsar data. To solve this problem, this paper proposes a fast algorithm of on-orbit estimating the pulse phase of Crab pulsar called X-ray pulsar navigaTion usIng on-orbiT pulsAr timiNg (XTITAN). The pulse phase propagation model for Crab pulsar data from \textit{Insight}-HXMT and \textit{NICER} are derived. When an exposure on the Crab pulsar is divided into several sub-exposures, we derive an on-orbit timing method to estimate the hyperparameters of the pulse phase propagation model. Moreover, XTITAN is improved by iteratively estimating the pulse phase and the position and velocity of satellite. When applied to the Crab pulsar data from \textit{NICER}, XTITAN is 58 times faster than the grid search method employed by \textit{NICER} experiment. When applied to the Crab pulsar data from \textit{Insight}-HXMT, XTITAN is 180 times faster than the Significance Enhancement of Pulse-profile with Orbit-dynamics (SEPO) which was employed in the flight experiments with \textit{Insight}-HXMT. Thus, XTITAN is computationally much efficient and has the potential to be employed for onboard computation.

astro-ph.IM↗

arXiv2022

DACSR: Decoupled-Aggregated End-to-End Calibrated Sequential Recommendation

Sequential recommendations have made great strides in accurately predicting the future behavior of users. However, seeking accuracy alone may bring side effects such as unfair and overspecialized recommendation results. In this work, we focus on the calibrated recommendations for sequential recommendation, which is connected to both fairness and diversity. On the one hand, it aims to provide fairer recommendations whose preference distributions are consistent with users' historical behaviors. On the other hand, it can improve the diversity of recommendations to a certain degree. But existing methods for calibration have mainly relied on the post-processing on the candidate lists, which require more computation time in generating recommendations. In addition, they fail to establish the relationship between accuracy and calibration, leading to the limitation of accuracy. To handle these problems, we propose an end-to-end framework to provide both accurate and calibrated recommendations for sequential recommendation. We design an objective function to calibrate the interests between recommendation lists and historical behaviors. We also provide distribution modification approaches to improve the diversity and mitigate the effect of imbalanced interests. In addition, we design a decoupled-aggregated model to improve the recommendation. The framework assigns two objectives to two individual sequence encoders, and aggregates the outputs by extracting useful information. Experiments on benchmark datasets validate the effectiveness of our proposed model.

cs.IR↗

arXiv2022

Reconfigurable optical logic operations through scattering media with wavefront shaping

Optical logic gates are fundamental blocks of optical computing to accelerate information processing. While significant progress has been achieved in recent years, existing implementations typically rely on dedicated structures that are predesigned to modulate the phases and intensities of optical beams accurately for specific logic functions. Thus, these optical gates usually lack reconfigurability and are incapable within or through dynamic complex media/environment, such as fog and turbid water. In this work, as a conceptual demonstration, we propose reconfigurable optical logic operations through scattering media with transmission matrix-based wavefront shaping. A light beam is reflected by a spatial light modulator divided into several subregions functioning as logic units, with each displayed with predetermined wavefronts via transmission matrix-based wavefront shaping. Each modulated wavefront transmits through the scattering medium to form a desired light field. The interference of these light fields generates bright optical focus at pre-assigned locations, representing different logic states. As a proof of concept, we experimentally demonstrate five basic logic functions (AND, OR, NOT, NAND, NOR). As the transmission matrix of the scattering medium/system can be measured instantly to adapt to environment perturbation, the method, if further engineered, opens new venues towards reconfigurable optical logic computing in a dynamically complex environment.

physics.optics↗

arXiv2022

Transferable Cross-Tokamak Disruption Prediction with Deep Hybrid Neural Network Feature Extractor

Predicting disruptions across different tokamaks is a great obstacle to overcome. Future tokamaks can hardly tolerate disruptions at high performance discharge. Few disruption discharges at high performance can hardly compose an abundant training set, which makes it difficult for current data-driven methods to obtain an acceptable result. A machine learning method capable of transferring a disruption prediction model trained on one tokamak to another is required to solve the problem. The key is a disruption prediction model containing a feature extractor that is able to extract common disruption precursor traces in tokamak diagnostic data, and a transferable disruption classifier. Based on the concerns above, the paper first presents a deep fusion feature extractor designed specifically for extracting disruption precursor features from common diagnostics on tokamaks according to currently known precursors of disruption, providing a promising foundation for transferable models. The fusion feature extractor is proved by comparing with manual feature extraction on J-TEXT. Based on the feature extractor trained on J-TEXT, the disruption prediction model was transferred to EAST data with mere 20 discharges from EAST experiment. The performance is comparable with a model trained with 1896 discharges from EAST. From the comparison among other model training scenarios, transfer learning showed its potential in predicting disruptions across different tokamaks.

physics.plasm-ph↗

arXiv2022

Nonlinear Hall response in the driving dynamics of ultracold atoms in optical lattices

We propose that a nonlinear Hall response can be observed in Bloch oscillations of ultracold atoms in optical lattices under the condition of preserved time-reversal symmetry. In the short-time limit of Bloch oscillations driven by a direct current (dc) field, the nonlinear Hall current dominates, being a second-order response to the external field strength. The associated Berry curvature dipole, which is a second-order nonlinear coefficient of the driving field, can be obtained from the oscillation of atoms. In an alternating current (ac) driving field, the nonlinear Hall response has a double frequency of the driving force in the case of time-reversal symmetry.

cond-mat.quant-gas↗

arXiv2022

Circular designs for total effects under interference models

This paper studies circular designs for interference models, where a treatment assigned to a plot also affects its neighboring plots within a block. For the purpose of estimating total effects, the circular neighbor balanced design was shown to be universally optimal among designs which do not allow treatments to be neighbors of themselves. Our study shows that self-neighboring block sequences are actually the main ingredient for an optimal design. Here, we adopt the approximate design framework and study optimal designs in the whole design space. Our approach is flexible enough to accommodate all possible design parameters, that is the block size and the number of blocks and treatments. This approach can be broken down into two main steps: the identification of the minimal supporting set of block sequences and the optimality condition built on it. The former is critical for reducing the computational time from almost infinity to seconds. Meanwhile, the task of finding the minimal set is normally achieved through numerical methods, which can only handle small block sizes. Our approach is of a hybrid nature in order to deal with all design sizes. When block size is not large, we provide explicit expressions of the minimal set instead of relying on numerical methods. For larger block sizes when a typical numerical method would fail, we theoretically derived a reasonable size intermediate set of sequences, from which the minimal set can be quickly derived through a customized algorithm. Taking it further, the optimality conditions allow us to obtain both symmetric and asymmetric designs. Lastly, we also investigate the trade-off issue between circular and noncircular designs, and provide guidelines on the choices.

stat.ME↗

arXiv2022

Possible Systematic Rotation in the Mature Stellar Population of a $z=9.1$ Galaxy

We present new observations with the Atacama Large Millimeter/submillimeter Array for a gravitationally-lensed galaxy at $z=9.1$, MACS1149-JD1. [O III] 88-$μ$m emission is detected at 10$σ$ with a spatial resolution of $\sim0.3$ kpc in the source plane, enabling the most distant morpho-kinematic study of a galaxy. The [O III] emission is distributed smoothly without any resolved clumps and shows a clear velocity gradient with $ΔV_{\rm obs}/2σ_{\rm tot}=0.84\pm0.23$, where $ΔV_{\rm obs}$ is the observed maximum velocity difference and $σ_{\rm tot}$ is the velocity dispersion measured in the spatially-integrated line profile, suggesting a rotating system. Assuming a geometrically thin self-gravitating rotation disk model, we obtain $V_{\rm rot}/σ_V=0.67_{-0.26}^{+0.73}$, where $V_{\rm rot}$ and $σ_V$ are the rotation velocity and velocity dispersion, respectively, still consistent with rotation. The resulting disk mass of $0.65_{-0.40}^{+1.37}\times10^{9}$ M$_\odot$ is consistent with being associated with the stellar mass identified with a 300 Myr-old stellar population independently indicated by a Balmer break in the spectral energy distribution. We conclude that the most of the dynamical mass is associated with the previously-identified mature stellar population that formed at $z\sim15$.

astro-ph.GA↗

arXiv2022

Long-Tail Session-based Recommendation from Calibration

Accurate predictions in session-based recommendations have progressed, but a few studies have focused on skewed recommendation lists caused by popularity bias. Existing models for mitigating popularity bias have attempted to reduce the overconcentration of popular items by amplifying scores of less popular items. However, they normally ignore the users' different preferences toward long-tail items. Thus, we incorporate calibration, where calibrated recommendations reflect the users' interests in recommendation lists with appropriate proportions, to mitigate the popularity bias from the user's perspective. Specifically, we propose a calibration module to predict the ratio of tail items in the recommendation list from the session representation, and align it to the ongoing session. Additionally, we utilize a two-stage curriculum training strategy to improve prediction in the calibration module. Experiments on benchmark datasets show that our model can both achieve the competitive accuracy of recommendation and provide more tail items.

cs.IR↗

arXiv2022

Tunable Confinement-Deconfinement Transition in an Ultracold Atom Quantum Simulator

The one-dimensional lattice Schwinger model has recently been realized by using bosons in optical lattices. This model contains both confinement and deconfinement phases, whose phase diagram is controlled by the mass of the matter field and the topological angle. Since varying the mass of matter field is straightforward experimentally, we propose how to tune the topological angle, allowing accessing the entire phase diagram. We propose that direct experimental evidence of confinement and deconfinement can be obtained by measuring whether a physical charge is localized around a fixed gauge charge to screen it. We also discuss the PXP model realized in the Rydberg atoms array, which is equivalent to the lattice Schwinger model when all local gauge charges are fixed as zero. Although the gauge charges are fixed, we can alternatively probe the confinement and the deconfinement in the PXP model by studying the relative motion of a pair of a physical charge and an anti-charge. Our scheme can be directly implemented in these two relevant experimental platforms of ultracold atom quantum simulators.

cond-mat.quant-gas↗

arXiv2022

Topological Micromotion of Floquet Quantum Systems

The Floquet Hamiltonian has often been used to describe a time-periodic system. Nevertheless, because the Floquet Hamiltonian depends on a micro-motion parameter, the Floquet Hamiltonian with a fixed micro-motion parameter cannot faithfully represent a driven system, which manifests as the anomalous edge states. Here we show that an accurate description of a Floquet system requires a set of Hamiltonian exhausting all values of the micro-motion parameter, and this micro-motion parameter can be viewed as an extra synthetic dimension of the system. Therefore, we show that a $d$-dimensional Floquet system can be described by a $d+1$-dimensional static Hamiltonian, and the advantage of this representation is that the periodic boundary condition is automatically imposed along the extra-dimension, which enables a straightforward definition of topological invariants. The topological invariant in the $d+1$-dimensional system can ensure a $d-1$-dimensional edge state of the $d$-dimensional Floquet system. Here we show two examples where the topological invariant is a three-dimensional Hopf invariant. We highlight that our scheme of classifying Floquet topology on the micro-motion space is different from the previous classification of Floquet topology on the time space.

quant-ph↗

arXiv2022

Identifying Emergent Leadership in OSS Projects Based on Communication Styles

In open source software (OSS) communities, existing leadership indicators are dominantly measured by code contribution or community influence. Recent studies on emergent leadership shed light on additional dimensions such as intellectual stimulation in collaborative communications. To that end, this paper proposes an automated approach, named iLead, to mine communication styles and identify emergent leadership behaviors in OSS communities, using issue comments data. We start with the construction of 6 categories of leadership behaviors based on existing leadership studies. Then, we manually label leadership behaviors in 10,000 issue comments from 10 OSS projects, and extract 304 heuristic linguistic patterns which represent different types of emergent leadership behaviors in flexible and concise manners. Next, an automated algorithm is developed to merge and consolidate different pattern sets extracted from multiple projects into a final pattern ranking list, which can be applied for the automatic leadership identification. The evaluation results show that iLead can achieve a median precision of 0.82 and recall of 0.78, outperforming ten machine/deep learning baselines. To demonstrate practical usefulness, we also conduct empirical analysis and human evaluation of the identified leadership behaviors from iLead. We argue that emergent leadership behaviors in issue discussion should be taken into consideration to broaden existing OSS leadership viewpoints. Practical insights on community building and leadership skill development are offered for OSS community and individual developers, respectively.

cs.SE↗

arXiv2021

A census of optically dark massive galaxies in the early Universe from magnification by lensing galaxy clusters

We present ALMA 870um and JCMT SCUBA2 850um dust continuum observations of a sample of optically dark and strongly lensed galaxies in the cluster fields. The ALMA and SCUBA2 observations reach a median rms of about 0.11 mJy and 0.44 mJy, respectively, with the latter close to the confusion limit of the data at 850um. This represents one of the most sensitive searches for dust emission in optically dark galaxies. We detect the dust emission in 12 out of 15 galaxies at >3.8 sigma, corresponding to a detection rate of 80 per cent. Thanks to the gravitational lensing, our observations reach a deeper limiting flux than previous surveys in blank fields by a factor of 3. We estimate delensed infrared luminosities in the range log(LIR)=11.5-12.7 Lsun, which correspond to dust-obscured star formation rates (SFRs) of 30 to 520 Msun per year. Stellar population fits to the optical-to-NIR photometric data yield a median redshift z=4.26 and de-lensed stellar mass log(Mstar)=10.78 Msun. They contribute a lensing-corrected star-formation rate density at least an order of magnitude higher than that of equivalently massive UV-selected galaxies at z>3. The results suggest that there is a missing population of massive star-forming galaxies in the early Universe, which may dominate the SFR density at the massive end. Five optically dark galaxies are located within r<50 arcsec in one cluster field, representing a potential overdensity structure that has a physical origin at a confidence level >99.974% from Poisson statistics. Follow-up spectroscopic observations with ALMA and JWST are crucial to confirm whether it is associated with a protocluster at similar redshifts.

astro-ph.GA↗

arXiv2021

The Stackelberg Equilibrium for One-sided Zero-sum Partially Observable Stochastic Games

Formulating cyber-security problems with attackers and defenders as a partially observable stochastic game has become a trend recently. Among them, the one-sided two-player zero-sum partially observable stochastic game (OTZ-POSG) has emerged as a popular model because it allows players to compete for multiple stages based on partial knowledge of the system. All existing work on OTZ-POSG has focused on the simultaneous move scenario and assumed that one player's actions are private in the execution process. However, this assumption may become questionable since one player's action may be detected by the opponent through deploying action detection strategies. Hence, in this paper, we propose a turn-based OTZ-POSG with the assumption of public actions and investigate the existence and properties of a Stackelberg equilibrium for this game. We first prove the existence of the Stackelberg equilibrium for the one-stage case and show that the one-stage game can be converted into a linear-fractional programming problem and therefore solved by linear programming. For multiple stages, the main challenge is the information leakage issue as the public run-time action reveals certain private information to the opponent and allows the opponent to achieve more rewards in the future. To deal with this issue, we adopt the concept of $ε$-Stackelberg equilibrium and prove that this equilibrium can be achieved for finite-horizon OTZ-POSGs. We propose a space partition approach to solve the game iteratively and show that the value function of the leader is piece-wise linear and the value function of the follower is piece-wise constant for multiple stages. Finally, examples are given to illustrate the space partition approach and show that value functions are piece-wise linear and piece-wise constant.

eess.SY↗