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Studying the propagation of uncertainties in a nonlinear dynamical system usually involves generating a set of samples in the stochastic parameter space and then repeated simulations with different sampled parameters. The main difficulty…

Numerical Analysis · Mathematics 2017-09-19 Nan Jiang , Michael Schneier

Kohn-Sham Density Functional Theory (KS-DFT) has been traditionally solved by the Self-Consistent Field (SCF) method. Behind the SCF loop is the physics intuition of solving a system of non-interactive single-electron wave functions under…

This paper focuses on the distributed optimization of stochastic saddle point problems. The first part of the paper is devoted to lower bounds for the centralized and decentralized distributed methods for smooth (strongly) convex-(strongly)…

Machine Learning · Computer Science 2025-04-28 Aleksandr Beznosikov , Valentin Samokhin , Alexander Gasnikov

In this paper, we propose beamforming schemes to simultaneously transmit data securely to multiple information receivers (IRs) while transferring power wirelessly to multiple energy-harvesting receivers (ERs). Taking into account the…

Information Theory · Computer Science 2017-05-19 Tuan Anh Le , Quoc-Tuan Vien , Huan X. Nguyen , Derrick Wing Kwan Ng , Robert Schober

We propose Deep Closed-Form Subspace Clustering (DCFSC), a new embarrassingly simple model for subspace clustering with learning non-linear mapping. Compared with the previous deep subspace clustering (DSC) techniques, our DCFSC does not…

Computer Vision and Pattern Recognition · Computer Science 2019-08-27 Junghoon Seo , Jamyoung Koo , Taegyun Jeon

We present a novel approach to solve the advection-diffusion equation under arbitrary transporting fields using a quantum-inspired 'Schrodingerisation' technique for Hamiltonian simulation. Although numerous methods exist for solving…

Quantum Physics · Physics 2025-08-26 Niladri Gomes , Gautam Sharma , Jay Pathak

Density matrix embedding theory (DMET) is a fully quantum-mechanical embedding method which shows great promise as a method of defeating the inherent exponential cost scaling of multiconfigurational wave function-based calculations by…

Chemical Physics · Physics 2019-02-07 Matthew R. Hermes , Laura Gagliardi

Neural time-series data contain a wide variety of prototypical signal waveforms (atoms) that are of significant importance in clinical and cognitive research. One of the goals for analyzing such data is hence to extract such…

Machine Learning · Statistics 2017-06-15 Mainak Jas , Tom Dupré La Tour , Umut Şimşekli , Alexandre Gramfort

Kohn-Sham density functional theory (KS-DFT) has found widespread application in accurate electronic structure calculations. However, it can be computationally demanding especially for large-scale simulations, motivating recent efforts…

Computational Physics · Physics 2024-06-25 Feitong Song , Ji Feng

We present a stability and error analysis of an embedded-hybridized discontinuous Galerkin (EDG-HDG) finite element method for coupled Stokes--Darcy flow and transport. The flow problem, governed by the Stokes--Darcy equations, is…

Numerical Analysis · Mathematics 2023-07-07 Aycil Cesmelioglu , Sander Rhebergen

This work introduces a new higher-order accurate super compact (HOSC) finite difference scheme for solving complex unsteady three-dimensional (3D) non-Newtonian fluid flow problems. As per the author's knowledge, the proposed scheme is the…

Fluid Dynamics · Physics 2024-07-30 Ashwani Punia , Rajendra K. Ray

First of all, this paper presents some improvements of DSMC method in the form of new schemes and approaches, that, for a wide class of problems, increase performance and reduce the demands on computer resources. The most important…

Fluid Dynamics · Physics 2012-01-16 Roman V. Maltsev

We analyze the full counting statistics (FCS) of a single-site quantum dot coupled to multiple metallic electrodes in the normal state and a superconductor for arbitrary transmission. We present an analytical solution of the problem taking…

Mesoscale and Nanoscale Physics · Physics 2011-09-22 H. Soller , A. Komnik

In recent years, the embedding approach for solving switched optimal control problems has been developed in a series of papers. However, the embedding approach, which advantageously converts the hybrid optimal control problem to a classical…

Optimization and Control · Mathematics 2018-04-04 Richard Meyer , Miloš Žefran , Raymond A. DeCarlo

The nonlocal Cahn-Hilliard (NCH) equation with nonlocal diffusion operator is more suitable for the simulation of microstructure phase transition than the local Cahn-Hilliard (LCH) equation. In this paper, based on the exponential…

Numerical Analysis · Mathematics 2023-07-27 Xiaoqing Meng , Aijie Cheng , Zhengguang Liu

A second-order many-body perturbation correction to the relativistic Dirac-Hartree-Fock energy is evaluated stochastically by integrating 13-dimensional products of four-component spinors and Coulomb potentials. The integration in the real…

Quantum Physics · Physics 2022-06-16 J. César Cruz , Jorge Garza , Takeshi Yanai , So Hirata

Transport phenomena play a key role in a variety of application domains, and efficient simulation of these dynamics remains an outstanding challenge. While quantum computers offer potential for significant speedups, existing algorithms…

Quantum Physics · Physics 2026-02-04 Joseph Li , Gengzhi Yang , Jiaqi Leng , Xiaodi Wu

In order to study 4-body atomic collisions such as excitation-ionization, transfer with target excitation, and double electron capture, the calculation of a nine-dimensional numerical integral is often required. This calculation can become…

Computational Physics · Physics 2013-05-09 A. L. Harris

Many high power electronic devices operate in a regime where the current they draw is limited by the self-fields of the particles. This space-charge-limited current poses particular challenges for numerical modeling where common techniques…

Plasma Physics · Physics 2020-07-07 Peter H. Stoltz , John W. Luginsland , Andrew M. Chap , David N. Smithe , John R. Cary

Designing distributed filter circuits (DFCs) is complex and time-consuming, involving setting and optimizing multiple hyperparameters. Traditional optimization methods, such as using the commercial finite element solver HFSS (High-Frequency…

Machine Learning · Computer Science 2024-07-30 Peng Gao , Tao Yu , Fei Wang , Ru-Yue Yuan