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We consider the long-term dynamics of nonlinear dispersive waves in a finite periodic domain. The purpose of the work is to show that the statistical properties of the wave field rely critically on the structure of the discrete resonant…

Fluid Dynamics · Physics 2020-10-14 Alexander Hrabski , Yulin Pan

Here we propose the Variational Discrete Action Theory (VDAT) to study the ground state properties of quantum many-body Hamiltonians. VDAT is a variational theory based on the sequential product density matrix (SPD) ansatz, characterized by…

Strongly Correlated Electrons · Physics 2021-05-26 Zhengqian Cheng , Chris A. Marianetti

The dynamical low-rank (DLR) approximation is an efficient technique to approximate the solution to matrix differential equations. Recently, the DLR method was applied to radiation transport calculations to reduce memory requirements and…

Computational Physics · Physics 2022-11-23 Zhuogang Peng , Ryan G. McClarren

The variational wave functions based on neural networks have recently started to be recognized as a powerful ansatz to represent quantum many-body states accurately. In order to show the usefulness of the method among all available…

Strongly Correlated Electrons · Physics 2021-04-28 Yusuke Nomura

The energy method can be used to identify well-posed initial boundary value problems for quasi-linear, symmetric hyperbolic partial differential equations with maximally dissipative boundary conditions. A similar analysis of the discrete…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Luis Lehner , David Neilsen , Oscar Reula , Manuel Tiglio

Dynamic treatment regimes (DTRs) consist of a sequence of decision rules, one per stage of intervention, that finds effective treatments for individual patients according to patient information history. DTRs can be estimated from models…

Methodology · Statistics 2021-12-07 Zeyu Bian , Erica EM Moodie , Susan M Shortreed , Sahir Bhatnagar

The simulation of many-body open quantum systems is key to solving numerous outstanding problems in physics, chemistry, material science, and in the development of quantum technologies. Near-term quantum computers may bring considerable…

Quantum Physics · Physics 2025-02-05 Sara Santos , Xinyu Song , Vincenzo Savona

This work is devoted to the study of dissipative fluid systems, through the lens of a geometric variational formulation. Building upon previous works extending Hamilton's principle to non-equilibrium thermodynamics, the present method…

Mathematical Physics · Physics 2026-04-07 Bastien Manach-Pérennou , François Gay-Balmaz

We present a four-field Virtual Element discretization for the time-dependent resistive Magnetohydrodynamics equations in three space dimensions, focusing on the semi-discrete formulation. The proposed method employs general polyhedral…

Numerical Analysis · Mathematics 2022-12-29 Lourenço Beirão da Veiga , Franco Dassi , Gianmarco Manzini , Lorenzo Mascotto

Describing time-dependent many-body systems where correlation effects play an important role remains a major theoretical challenge. In this paper we develop a time-dependent many-body theory that is based on the two-particle reduced density…

Besides perturbation theory, which requires, of course, the knowledge of the exact unperturbed solution, variational techniques represent the main tool for any investigation of the eigenvalue problem of some semibounded operator H in…

High Energy Physics - Phenomenology · Physics 2016-12-28 Wolfgang Lucha , F. F. Schoberl

We introduce a class of variational wavefunctions that capture the long-range interaction between neutral systems (atoms and molecules) without changing the diagonal of the density matrix of each monomer. The corresponding energy…

Chemical Physics · Physics 2019-03-26 Derk P. Kooi , Paola Gori-Giorgi

Variational algorithms are promising candidates to be implemented on near-term quantum computers. The variational quantum eigensolver (VQE) is a prominent example, where a parametrized trial state of the quantum mechanical wave function is…

Representation learning and exploration are among the key challenges for any deep reinforcement learning agent. In this work, we provide a singular value decomposition based method that can be used to obtain representations that preserve…

Machine Learning · Computer Science 2023-05-03 Yash Chandak , Shantanu Thakoor , Zhaohan Daniel Guo , Yunhao Tang , Remi Munos , Will Dabney , Diana L Borsa

Visible (VIS) to near infrared (NIR) face matching is a challenging problem due to the significant domain discrepancy between the domains and a lack of sufficient data for training cross-modal matching algorithms. Existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2019-01-24 Xiang Wu , Huaibo Huang , Vishal M. Patel , Ran He , Zhenan Sun

Nuclear physics is ideal to test and develop techniques to describe the microscopic dynamics of quantum many-body systems. At low energy, nuclear dynamics is described with non-relativistic approaches based on the mean-field approximation…

Nuclear Theory · Physics 2023-02-10 Cedric Simenel

Quantum coherence and entanglement are fundamental resources in quantum technologies, yet their efficient estimation for unknown states by employing minimal resources in experimental settings remains challenging, particularly in…

Quantum Physics · Physics 2026-01-12 Ting Lin , Zhihua Chen , Kai Wu , Zhihua Guo , Zhihao Ma , Shao-Ming Fei

This paper discusses the practical development of space-time boundary element methods for the wave equation in three spatial dimensions. The employed trial spaces stem from simplex meshes of the lateral boundary of the space-time cylinder.…

Numerical Analysis · Mathematics 2021-08-25 Dominik Pölz , Martin Schanz

Introducing a reduced particle stiffness in discrete element method (DEM) allows for bigger time steps and therefore fewer total iterations in a simulation. Although this approach works well for dry non-adhesive particles, it has been shown…

Soft Condensed Matter · Physics 2018-10-17 Sheng Chen , Wenwei Liu , Shuiqing Li

Variational methods are highly valuable computational tools for solving high-dimensional quantum systems. In this paper, we explore the effectiveness of three variational methods: the density matrix renormalization group (DMRG), Boltzmann…

Quantum Physics · Physics 2024-04-18 Daming Li