arXiv subjects

Jiyuan Zhang

Publications and source records attributed to Jiyuan Zhang.

At least 73 records · Page 4Linked to original sources

arXiv2023

Synchronous control study of Chua circuit system via capacitive closed-loop coupling

Synchronous control of nonlinear circuits is of great importance in many fields. In this paper, a capacitor is used for closed-loop coupling of three dual-vortex attractor Chua circuits with the same circuit parameters and different initial conditions, and the corresponding synchronization processes and synchronization effects are investigated. It is found that, for the capacitor, the closed-loop coupling can completely synchronize the three Chua circuits. And there exists a critical coupling strength $δ_{critical}^C$ that can be calculated, and when the coupling strength is between the critical coupling strength $δ_{critical}^C$ and the upper coupling strength $δ_{max}^C$, the three circuits can be completely synchronized very quickly. Moreover, the results show that the unidirectional coupling cannot make the circuit system completely synchronized. Finally, we also verify the correctness of the calculation by circuit simulation experiments.

physics.comp-ph↗

arXiv2023

KMT-2021-BLG-2010Lb, KMT-2022-BLG-0371Lb, and KMT-2022-BLG-1013Lb: Three microlensing planets detected via partially covered signals

We inspect 4 microlensing events KMT-2021-BLG-1968, KMT-2021-BLG-2010, KMT-2022-BLG-0371, and KMT-2022-BLG-1013, for which the light curves exhibit partially covered short-term central anomalies. We conduct detailed analyses of the events with the aim of revealing the nature of the anomalies. We test various models that can give rise to the anomalies of the individual events including the binary-lens (2L1S) and binary-source (1L2S) interpretations. Under the 2L1S interpretation, we thoroughly inspect the parameter space to check the existence of degenerate solutions, and if they exist, we test the feasibility of resolving the degeneracy. We find that the anomalies in KMT-2021-BLG-2010 and KMT-2022-BLG-1013 are uniquely defined by planetary-lens interpretations with the planet-to-host mass ratios of $q\sim 2.8\times 10^{-3}$ and $\sim 1.6\times 10^{-3}$, respectively. For KMT-2022-BLG-0371, a planetary solution with a mass ratio $q\sim 4\times 10^{-4}$ is strongly favored over the other three degenerate 2L1S solutions with different mass ratios based on the $χ^2$ and relative proper motion arguments, and a 1L2S solution is clearly ruled out. For KMT-2021-BLG-1968, on the other hand, we find that the anomaly can be explained either by a planetary or a binary-source interpretation, making it difficult to firmly identify the nature of the anomaly. From the Bayesian analyses of the identified planetary events, we estimate that the masses of the planet and host are $(M_{\rm p}/M_{\rm J}, M_{\rm h}/M_\odot) = (1.07^{+1.15}_{-0.68}, 0.37^{+0.40}_{-0.23})$, $(0.26^{+0.13}_{-0.11}, 0.63^{+0.32}_{-0.28})$, and $(0.31^{+0.46}_{-0.16}, 0.18^{+0.28}_{-0.10})$ for KMT-2021-BLG-2010L, KMT-2022-BLG-0371L, and KMT-2022-BLG-1013L, respectively.

astro-ph.EP↗

arXiv2023

OGLE-2016-BLG-1195 AO: Lens, Companion to Lens or Source, or None of the Above?

We systematically investigate the claim by Vandorou et al. (2023) to have detected the host star of the low mass-ratio ($q<10^{-4}$) microlensing planet OGLE-2016-BLG-1195Lb, via Keck adaptive optics (AO) measurements $Δt=4.12\,$yr after the peak of the event ($t_0$). If correct, this measurement would contradict the microlens parallax measurement derived from Spitzer observations in solar orbit taken near $t_0$. We show that this host identification would be in $4\,σ$ conflict with the original ground-based lens-source relative proper-motion measurements. By contrast, Gould (2022) estimated a probability $p=10\%$ that the ``other star'' resolved by single-epoch late-time AO would be a companion to the host or the microlensed source, which is much more probable than a 4$\,σ$ statistical fluctuation. In addition, independent of this proper-motion discrepancy, the kinematics of this host-identification are substantially less probable than those of the Spitzer solution. Hence, this identification should not be accepted, pending additional observations that would either confirm or contradict it, which could be taken in 2023. Motivated by this tension, we present two additional investigations. We explore the possibility that Vandorou et al. (2023) identified the wrong ``star'' (or stellar asterism) on which to conduct their analysis. We find that astrometry of KMT and Keck images favors a star (or asterism) lying about 175 mas northwest of the one that they chose. We also present event parameters from a combined fit to all survey data, which yields, in particular, a more precise mass ratio, $q=(4.6\pm 0.4)\times 10^{-5}$. Finally, we discuss the broader implications of minimizing such false positives for the first measurement of the planet mass function, which will become possible when AO on next-generation telescopes are applied to microlensing planets.

astro-ph.EP↗

arXiv2023

A rate of convergence when generating stable invariant Hermitian random matrix ensembles

Recently, we have classified Hermitian random matrix ensembles that are invariant under the conjugate action of the unitary group and stable with respect to matrix addition. Apart from a scaling and a shift, the whole information of such an ensemble is encoded in the stability exponent determining the ``heaviness'' of the tail and the spectral measure that describes the anisotropy of the probability distribution. In the present work, we address the question how these ensembles can be generated by the knowledge of the latter two quantities. We consider a sum of a specific construction of identically and independently distributed random matrices that are based on Haar distributed unitary matrices and a stable random vectors. For this construction, we derive the rate of convergence in the supremums norm and show that this rate is optimal in the class of all stable invariant random matrices for a fixed stability exponent. As a consequence we also give the rate of convergence in the total variation distance.

math.PR↗

arXiv2023

Simulations of Triple Microlensing Events I: Detectability of a scaled Sun-Jupiter-Saturn System

Up to date, only 13 firmly established triple microlensing events have been discovered, so the occurrence rates of microlensing two-planet systems and planets in binary systems are still uncertain. With the upcoming space-based microlensing surveys, hundreds of triple microlensing events will be detected. To provide clues for future observations and statistical analyses, we initiate a project to investigate the detectability of triple-lens systems with different configurations and observational setups. As the first step, in this work we develop the simulation software and investigate the detectability of a scaled Sun-Jupiter-Saturn system with the recently proposed telescope for microlensing observation on the ``Earth 2.0 (ET)'' satellite. With the same $Δχ^2$ thresholds of detecting a single planet and two planets, we find that the detectability of the scaled Sun-Jupiter-Saturn analog is about 1% and the presence of the Jovian planet suppresses the detectability of the Saturn-like planet by $\sim $13% regardless of the adopted detection $Δχ^2$ threshold. This suppression probability could be at the same level as the Poisson noise of future space-based statistical samples of triple-lenses, so it is inappropriate to treat each planet separately during detection efficiency calculations.

astro-ph.EP↗

arXiv2023

Systematic KMTNet Planetary Anomaly Search, Paper VII: Complete Sample of $q < 10^{-4}$ Planets from the First Four-Year Survey

We present the analysis of seven microlensing planetary events with planet/host mass ratios $q < 10^{-4}$: KMT-2017-BLG-1194, KMT-2017-BLG-0428, KMT-2019-BLG-1806, KMT-2017-BLG-1003, KMT-2019-BLG-1367, OGLE-2017-BLG-1806, and KMT-2016-BLG-1105. They were identified by applying the Korea Microlensing Telescope Network (KMTNet) AnomalyFinder algorithm to 2016--2019 KMTNet events. A Bayesian analysis indicates that all the lens systems consist of a cold super-Earth orbiting an M or K dwarf. Together with 17 previously published and three that will be published elsewhere, AnomalyFinder has found a total of 27 planets that have solutions with $q < 10^{-4}$ from 2016--2019 KMTNet events, which lays the foundation for the first statistical analysis of the planetary mass-ratio function based on KMTNet data. By reviewing the 27 planets, we find that the missing planetary caustics problem in the KMTNet planetary sample has been solved by AnomalyFinder. We also find a desert of high-magnification planetary signals ($A \gtrsim 65$), and a follow-up project for KMTNet high-magnification events could detect at least two more $q < 10^{-4}$ planets per year and form an independent statistical sample.

astro-ph.EP↗

arXiv2022

Derivative principles for invariant ensembles

In the present work we show that the joint probability distribution of the eigenvalues can be expressed in terms of a differential operator acting on the distribution of some other matrix quantities. Those quantities might be the diagonal or pseudo-diagonal entries as it is the case for Hermitian matrices. These representations are called derivative principles. We show them for the additive spaces of the Hermitian, Hermitian antisymmetric, Hermitian anti-self-dual, and complex rectangular matrices as well as for the two multiplicative matrix spaces of the positive definite Hermitian matrices and of the unitary matrices. In all six cases we prove the uniqueness of the derivative principles.

math-ph↗

arXiv2022

Study on dynamic model of multi-particle spring system

Generally, multi-particle spring system is an important and widely used physical model. However, with the increase of the number of particles, the difficulty of solving the kinematic trajectory of the particles becomes more and more difficult. The key to solving this problem lies in whether it is possible to construct a dynamic model of the multi-particle spring system which is convenient for numerical solution. In this work, by defining a new physical quantity, the spring action $\mathcal{K}$, we study and reconstruct the dynamic models of two common types of multi-particle spring systems. The calculation results show that the multi-particle spring dynamic model constructed by us has obvious advantages in calculating the spring system with a large number of particles. This will provide important theoretical solutions for the application of multi-particle spring systems to engineering or scientific problems.

physics.comp-ph↗

arXiv2022

Exploration of trace anomaly contribution to proton mass based on light vector meson photoproduction

In the quantum chromodynamics, the mass source of the proton is decomposed into four parts by the energy momentum tensor : quark energy term, gluon energy term, quark mass term and trace anomaly term. And the trace anomaly term is the most crucial contribution for studying the internal structure of the proton. In this work, under the definition of the vector meson dominant model, the trace anomaly contribution of the proton is extracted from the experimental datas of light vector mesons $ρ$, $ω$ and $ϕ$ photoproduction at the near-threshold, which are ($1.15\pm0.08$)$\%$, ($2.70\pm0.04$)$\%$ and ($5.58\pm0.25$)$\%$, respectively. Eventually, the average trace anomaly contribution of the proton is ($4.36\pm0.40$) $\%$, which only account for a small fraction of the total proton mass. The result of this work will provide theoretical information support for further study of proton internal structure.

hep-ph↗

arXiv2022

Uncertainty Guided Depth Fusion for Spike Camera

Depth estimation is essential for various important real-world applications such as autonomous driving. However, it suffers from severe performance degradation in high-velocity scenario since traditional cameras can only capture blurred images. To deal with this problem, the spike camera is designed to capture the pixel-wise luminance intensity at high frame rate. However, depth estimation with spike camera remains very challenging using traditional monocular or stereo depth estimation algorithms, which are based on the photometric consistency. In this paper, we propose a novel Uncertainty-Guided Depth Fusion (UGDF) framework to fuse the predictions of monocular and stereo depth estimation networks for spike camera. Our framework is motivated by the fact that stereo spike depth estimation achieves better results at close range while monocular spike depth estimation obtains better results at long range. Therefore, we introduce a dual-task depth estimation architecture with a joint training strategy and estimate the distributed uncertainty to fuse the monocular and stereo results. In order to demonstrate the advantage of spike depth estimation over traditional camera depth estimation, we contribute a spike-depth dataset named CitySpike20K, which contains 20K paired samples, for spike depth estimation. UGDF achieves state-of-the-art results on CitySpike20K, surpassing all monocular or stereo spike depth estimation baselines. We conduct extensive experiments to evaluate the effectiveness and generalization of our method on CitySpike20K. To the best of our knowledge, our framework is the first dual-task fusion framework for spike camera depth estimation. Code and dataset will be released.

cs.CV↗

arXiv2022

KMT-2021-BLG-0171Lb and KMT-2021-BLG-1689Lb: Two Microlensing Planets in the KMTNet High-cadence Fields with Followup Observations

Follow-up observations of high-magnification gravitational microlensing events can fully exploit their intrinsic sensitivity to detect extrasolar planets, especially those with small mass ratios. To make followup more uniform and efficient, we develop a system, HighMagFinder, based on the real-time data from the Korean Microlensing Telescope Network (KMTNet) to automatically alert possible ongoing high-magnification events. We started a new phase of follow-up observations with the help of HighMagFinder in 2021. Here we report the discovery of two planets in high-magnification microlensing events, KMT-2021-BLG-0171 and KMT-2021-BLG-1689, which were identified by the HighMagFinder. We find that both events suffer the ``central-resonant'' caustic degeneracy. The planet-host mass-ratio is $q\sim4.7\times10^{-5}$ or $q\sim 2.2\times10^{-5}$ for KMT-2021-BLG-0171, and $q\sim2.5\times10^{-4}$ or $q\sim 1.8\times10^{-4}$ for KMT-2021-BLG-1689. Together with two events reported by Ryu et al. (2022), four cases that suffer such degeneracy have been discovered in the 2021 season alone, indicating that the degenerate solutions may have been missed in some previous studies. We also propose a new factor for weighting the probability of each solution from the phase-space. The resonant interpretations for the two events are disfavored under this consideration. This factor can be included in future statistical studies to weight degenerate solutions.

astro-ph.EP↗

arXiv2022

Cyclic Pólya Ensembles on the Unitary Matrices and their Spectral Statistics

The framework of spherical transforms and Pólya ensembles is of utility in deriving structured analytic results for sums and products of random matrices in a unified way. In the present work, we will carry over this framework to study products of unitary matrices. Those are not distributed via the Haar measure, but still are drawn from distributions where the eigenvalue and eigenvector statistics factorise. They include the circular Jacobi ensemble, known in relation to the Fisher-Hartwig singularity in the theory of Toeplitz determinants, as well as the heat kernel for Brownian motion on the unitary group. We define cyclic Pólya frequency functions and show their relation to the cyclic Pólya ensembles, give a uniqueness statement for the corresponding weights, and derive the determinantal point processes of the eigenvalue statistics at fixed matrix dimension. An outline is given of problems one may encounter when investigating the local spectral statistics.

math.PR↗

arXiv2022

Optimal convergence rate of the explicit Euler method for convection-diffusion equations II: high dimensional cases

This is the second part of study on the optimal convergence rate of the explicit Euler discretization in time for the convection-diffusion equations [Appl. Math. Lett. \textbf{131} (2022) 108048] which focuses on high-dimensional linear/nonlinear cases under Dirichlet or Neumann boundary conditions. Several new corrected difference schemes are proposed based on the explicit Euler discretization in temporal derivative and central difference discretization in spatial derivatives. The priori estimate of the corrected scheme with application to constant convection coefficients is provided at length by the maximum principle and the optimal convergence rate four is proved when the step ratios along each direction equal to $1/6$. The corrected difference schemes have essentially improved {\rm \textbf{CFL}} condition and the numerical accuracy comparing with the classical difference schemes. Numerical examples involving two-/three-dimensional linear/nonlinear problems under Dirichlet/Neumann boundary conditions such as the Fisher equation, the Chafee-Infante equation, the Burgers' equation and classification to name a few substantiate the good properties claimed for the corrected difference scheme.

math.NA↗

arXiv2022

Mixture of Experts for Biomedical Question Answering

Biomedical Question Answering (BQA) has attracted increasing attention in recent years due to its promising application prospect. It is a challenging task because the biomedical questions are professional and usually vary widely. Existing question answering methods answer all questions with a homogeneous model, leading to various types of questions competing for the shared parameters, which will confuse the model decision for each single type of questions. In this paper, in order to alleviate the parameter competition problem, we propose a Mixture-of-Expert (MoE) based question answering method called MoEBQA that decouples the computation for different types of questions by sparse routing. To be specific, we split a pretrained Transformer model into bottom and top blocks. The bottom blocks are shared by all the examples, aiming to capture the general features. The top blocks are extended to an MoE version that consists of a series of independent experts, where each example is assigned to a few experts according to its underlying question type. MoEBQA automatically learns the routing strategy in an end-to-end manner so that each expert tends to deal with the question types it is expert in. We evaluate MoEBQA on three BQA datasets constructed based on real examinations. The results show that our MoE extension significantly boosts the performance of question answering models and achieves new state-of-the-art performance. In addition, we elaborately analyze our MoE modules to reveal how MoEBQA works and find that it can automatically group the questions into human-readable clusters.

cs.CL↗

arXiv2022

Spatio-Temporal Recurrent Networks for Event-Based Optical Flow Estimation

Event camera has offered promising alternative for visual perception, especially in high speed and high dynamic range scenes. Recently, many deep learning methods have shown great success in providing promising solutions to many event-based problems, such as optical flow estimation. However, existing deep learning methods did not address the importance of temporal information well from the perspective of architecture design and cannot effectively extract spatio-temporal features. Another line of research that utilizes Spiking Neural Network suffers from training issues for deeper architecture.To address these points, a novel input representation is proposed that captures the events' temporal distribution for signal enhancement. Moreover, we introduce a spatio-temporal recurrent encoding-decoding neural network architecture for event-based optical flow estimation, which utilizes Convolutional Gated Recurrent Units to extract feature maps from a series of event images. Besides, our architecture allows some traditional frame-based core modules, such as correlation layer and iterative residual refine scheme, to be incorporated. The network is end-to-end trained with self-supervised learning on the Multi-Vehicle Stereo Event Camera dataset. We have shown that it outperforms all the existing state-of-the-art methods by a large margin. The code link is https://github.com/ruizhao26/STE-FlowNet.

cs.CV↗

arXiv2021

Harmonic analysis for rank-1 Randomised Horn Problems

The randomised Horn problem, in both its additive and multiplicative version, has recently drawn increasing interest. Especially, closed analytical results have been found for the rank-1 perturbation of sums of Hermitian matrices and products of unitary matrices. We will generalise these results to rank-1 perturbations for products of positive definite Hermitian matrices and prove the other results in a new unified way. Our ideas work along harmonic analysis for matrix groups via spherical transforms that have been successfully applied in products of random matrices in the past years. In order to achieve the unified derivation of all three cases, we define the spherical transform on the unitary group and prove its invertibility.

math-ph↗

arXiv2021

A Deep Learning Inference Scheme Based on Pipelined Matrix Multiplication Acceleration Design and Non-uniform Quantization

Matrix multiplication is the bedrock in Deep Learning inference application. When it comes to hardware acceleration on edge computing devices, matrix multiplication often takes up a great majority of the time. To achieve better performance in edge computing, we introduce a low-power Multi-layer Perceptron (MLP) accelerator based on a pipelined matrix multiplication scheme and a nonuniform quantization methodology. The implementation is running on Field-programmable Gate Array (FPGA) devices and tested its performance on handwritten digit classification and Q-learning tasks. Results show that our method can achieve better performance with fewer power consumption.

cs.LG↗

arXiv2020

ViP: Virtual Pooling for Accelerating CNN-based Image Classification and Object Detection

In recent years, Convolutional Neural Networks (CNNs) have shown superior capability in visual learning tasks. While accuracy-wise CNNs provide unprecedented performance, they are also known to be computationally intensive and energy demanding for modern computer systems. In this paper, we propose Virtual Pooling (ViP), a model-level approach to improve speed and energy consumption of CNN-based image classification and object detection tasks, with a provable error bound. We show the efficacy of ViP through experiments on four CNN models, three representative datasets, both desktop and mobile platforms, and two visual learning tasks, i.e., image classification and object detection. For example, ViP delivers 2.1x speedup with less than 1.5% accuracy degradation in ImageNet classification on VGG-16, and 1.8x speedup with 0.025 mAP degradation in PASCAL VOC object detection with Faster-RCNN. ViP also reduces mobile GPU and CPU energy consumption by up to 55% and 70%, respectively. As a complementary method to existing acceleration approaches, ViP achieves 1.9x speedup on ThiNet leading to a combined speedup of 5.23x on VGG-16. Furthermore, ViP provides a knob for machine learning practitioners to generate a set of CNN models with varying trade-offs between system speed/energy consumption and accuracy to better accommodate the requirements of their tasks. Code is available at https://github.com/cmu-enyac/VirtualPooling.

cs.CV↗