357 citations · 875 across the 60 of their papers we have counts for
62 papers
Error estimates of a bi-fidelity method for a multi-phase Navier-Stokes-Vlasov-Fokker-Planck system with random inputs
Yiwen Lin, Shi Jin
Uniform error estimates of a bi-fidelity method for a kinetic-fluid coupled model with random initial inputs in the fine particle regime are proved in this paper. Such a model is a…
Asymptotic-preserving neural networks for multiscale Vlasov-Poisson-Fokker-Planck system in the high-field regime
Shi Jin, Zheng Ma, Tian-ai Zhang
The Vlasov-Poisson-Fokker-Planck (VPFP) system is a fundamental model in plasma physics that describes the Brownian motion of a large ensemble of particles within a surrounding bat…
Capturing the Diffusive Behavior of the Multiscale Linear Transport Equations by Asymptotic-Preserving Convolutional DeepONets
Keke Wu, Xiong-bin Yan, Shi Jin +1
In this paper, we introduce two types of novel Asymptotic-Preserving Convolutional Deep Operator Networks (APCONs) designed to address the multiscale time-dependent linear transpor…
Asymptotic-Preserving Neural Networks for Multiscale Kinetic Equations
Shi Jin, Zheng Ma, Keke Wu
In this paper, we present two novel Asymptotic-Preserving Neural Networks (APNNs) for tackling multiscale time-dependent kinetic problems, encompassing the linear transport equatio…
Quantum Algorithms for Multiscale Partial Differential Equations
Junpeng Hu, Shi Jin, Lei Zhang
Partial differential equation (PDE) models with multiple temporal/spatial scales are prevalent in several disciplines such as physics, engineering, and many others. These models ar…
Quantum simulation of discrete linear dynamical systems and simple iterative methods in linear algebra via Schrodingerisation
Shi Jin, Nana Liu
Quantum simulation is known to be capable of simulating certain dynamical systems in continuous time -- Schrodinger's equations being the most direct and well-known -- more efficie…
Asymptotic-preserving schemes for kinetic-fluid modeling of mixture flows with distinct particle sizes
Shi Jin, Yiwen Lin
We consider coupled models for particulate flows, where the disperse phase is made of particles with distinct sizes. We are thus led to a system coupling the incompressible Navier-…
Quantum algorithms for uncertainty quantification: application to partial differential equations
Francois Golse, Shi Jin, Nana Liu
Most problems in uncertainty quantification, despite its ubiquitousness in scientific computing, applied mathematics and data science, remain formidable on a classical computer. Fo…
An Asymptotic-Preserving and Energy-Conserving Particle-In-Cell Method for Vlasov-Maxwell Equations
Lijie Ji, Zhiguo Yang, Zhuoning Li +3
In this paper, we develop an asymptotic-preserving and energy-conserving (APEC) Particle-In-Cell (PIC) algorithm for the Vlasov-Maxwell system. This algorithm not only guarantees t…
Time complexity analysis of quantum algorithms via linear representations for nonlinear ordinary and partial differential equations
Shi Jin, Nana Liu, Yue Yu
We construct quantum algorithms to compute the solution and/or physical observables of nonlinear ordinary differential equations (ODEs) and nonlinear Hamilton-Jacobi equations (HJE…
On multilevel Monte Carlo methods for deterministic and uncertain hyperbolic systems
Junpeng Hu, Shi Jin, Jinglai Li +1
In this paper, we evaluate the performance of the multilevel Monte Carlo method (MLMC) for deterministic and uncertain hyperbolic systems, where randomness is introduced either in…
Energy estimates and hypocoercivity analysis for a multi-phase Navier-Stokes-Vlasov-Fokker-Planck system with uncertainty
Shi Jin, Yiwen Lin
This paper is concerned with a kineitc-fluid model with random initial inputs in the fine particle regime, which is a system coupling the incompressible Navier-Stokes equations and…
Quantum algorithms for computing observables of nonlinear partial differential equations
Shi Jin, Nana Liu
We construct quantum algorithms to compute physical observables of nonlinear PDEs with M initial data. Based on an exact mapping between nonlinear and linear PDEs using the level s…
Random batch particle methods for the homogeneous Landau equation
José Antonio Carrillo, Shi Jin, Yijia Tang
We consider in this paper random batch particle methods for efficiently solving the homogeneous Landau equation in plasma physics. The methods are stochastic variations of the part…
A Deep Learning Based Discontinuous Galerkin Method for Hyperbolic Equations with Discontinuous Solutions and Random Uncertainties
Jingrun Chen, Shi Jin, Liyao Lyu
We propose a deep learning based discontinuous Galerkin method (D2GM) to solve hyperbolic equations with discontinuous solutions and random uncertainties. The main computational ch…
Random Batch Methods for classical and quantum interacting particle systems and statistical samplings
Shi Jin, Lei Li
We review the Random Batch Methods (RBM) for interacting particle systems consisting of -particles, with being large. The computational cost of such systems is of ,…
Accurate and Efficient Simulations of Hamiltonian Mechanical Systems with Discontinuous Potentials
Molei Tao, Shi Jin
This article considers Hamiltonian mechanical systems with potential functions admitting jump discontinuities. The focus is on accurate and efficient numerical approximations of th…
A Spatial-Temporal asymptotic preserving scheme for radiation magnetohydrodynamics in the equilibrium and non-equilibrium diffusion limit
Shi Jin, Min Tang, Xiaojiang Zhang
The radiation magnetohydrodynamics (RMHD) system couples the ideal magnetohydrodynamics equations with a gray radiation transfer equation. The main challenge is that the radiation…
A consensus-based global optimization method with adaptive momentum estimation
Jingrun Chen, Shi Jin, Liyao Lyu
Objective functions in large-scale machine-learning and artificial intelligence applications often live in high dimensions with strong non-convexity and massive local minima. First…
On the Random Batch Method for second order interacting particle systems
Shi Jin, Lei Li, Yiqun Sun
We investigate several important issues regarding the Random Batch Method (RBM) for second order interacting particle systems. We first show the uniform-in-time strong convergence…
A random batch Ewald method for particle systems with Coulomb interactions
Shi Jin, Lei Li, Zhenli Xu +1
We develop a random batch Ewald (RBE) method for molecular dynamics simulations of particle systems with long-range Coulomb interactions, which achieves an complexity in eac…
Random Batch Algorithms for Quantum Monte Carlo simulations
Shi Jin, Xiantao Li
Random batch algorithms are constructed for quantum Monte Carlo simulations. The main objective is to alleviate the computational cost associated with the calculations of two-body…
On the mean field limit of the Random Batch Method for interacting particle systems
Shi Jin, Lei Li
The Random Batch Method proposed in our previous work [Jin et al., J. Comput. Phys., 400(1), 2020] is not only a numerical method for interacting particle systems and its mean-fiel…
Convergence of Random Batch Method for interacting particles with disparate species and weights
Shi Jin, Lei Li, Jian-Guo Liu
We consider in this work the convergence of Random Batch Method proposed in our previous work [Jin et al., J. Comput. Phys., 400(1), 2020] for interacting particles to the case of…