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In this paper, a diffusion-aggregation equation with delta potential is introduced. Based on the global existence and uniform estimates of solutions to the diffusion-aggregation equation, we also provide the rigorous derivation from a…

Analysis of PDEs · Mathematics 2019-12-13 Li Chen , Simone Göttlich , Stephan Knapp

The continuous variable quantum computing platform constitutes a promising candidate for realizing quantum advantage, as exemplified in Gaussian Boson Sampling. While noise in the experiments makes the computation attainable for classical…

Quantum Physics · Physics 2025-08-11 Jonas Vinther , Michael James Kastoryano

We propose a general strategy to discretize the Dyson series without applying direct numerical quadrature to high-dimensional integrals, and extend this framework to open quantum systems. The resulting discretization can also be interpreted…

Quantum Physics · Physics 2025-10-20 Zhenning Cai , Yixiao Sun , Geshuo Wang

Boson sampling, a computational problem conjectured to be hard to simulate on a classical machine, is a promising candidate for an experimental demonstration of quantum advantage using bosons. However, inevitable experimental noise and…

Quantum Physics · Physics 2022-10-12 Gabriele Bressanini , Hyukjoon Kwon , M. S. Kim

In this paper we examine a number of models that generate random fractals. The models are studied using the tools of computational complexity theory from the perspective of parallel computation. Diffusion limited aggregation and several…

Condensed Matter · Physics 2009-10-28 J. Machta , R. Greenlaw

We describe an approximate rational arithmetic with round-off errors (both absolute and relative) controlled by the user. The rounding procedure is based on the continued fraction expansion of real numbers. Results of computer experiments…

Numerical Analysis · Mathematics 2025-10-20 Grigori Litvinov , Anatoli Rodionov , Andrei Chourkin

This article presents a new method to compute matrices from numerical simulations based on the ideas of sparse sampling and compressed sensing. The method is useful for problems where the determination of the entries of a matrix constitutes…

Chemical Physics · Physics 2014-10-21 Jacob N. Sanders , Xavier Andrade , Alán Aspuru-Guzik

Invariant risk minimization (IRM) aims to enable out-of-distribution (OOD) generalization in deep learning by learning invariant representations. As IRM poses an inherently challenging bi-level optimization problem, most existing approaches…

Machine Learning · Computer Science 2025-05-26 Kotaro Yoshida , Konstantinos Slavakis

We present two analytical formulae for estimating the sensitivity -- namely, the gradient or Jacobian -- at given realizations of an arbitrary-dimensional random vector with respect to its distributional parameters. The first formula…

Machine Learning · Statistics 2025-08-14 Pi-Yueh Chuang , Ahmed Attia , Emil Constantinescu

We present a method for computing nearly singular integrals that occur when single or double layer surface integrals, for harmonic potentials or Stokes flow, are evaluated at points nearby. Such values could be needed in solving an integral…

Numerical Analysis · Mathematics 2024-06-21 J. Thomas Beale , Svetlana Tlupova

The distance between the true and numerical solutions in some metric is considered as the discretization error magnitude. If error magnitude ranging is known, the triangle inequality enables the estimation of the vicinity of the approximate…

Computational Physics · Physics 2018-05-11 A. K. Alekseev , A. E. Bondarev , I. M. Navon

A celebrated method for Variational Inequalities (VIs) is Extragradient (EG), which can be viewed as a standard discrete-time integration scheme. With this view in mind, in this paper we show that EG may suffer from discretization bias when…

Machine Learning · Computer Science 2026-05-08 Zhankun Luo , M. Berk Sahin , Antesh Upadhyay , Behzad Sharif , Abolfazl Hashemi

We study the Richardson equations close to the critical values of the paring strength g_c where the occurrence of divergencies preclude numerical solutions. We derive a set of equations for determining the critical g values and the…

Mathematical Physics · Physics 2008-11-26 F. Dominguez , C. Esebbag , J. Dukelsky

Molecular dynamics refers to the computer simulation of a material at the atomic level. An open problem in numerical analysis is to explain the apparent reliability of molecular dynamics simulations. The difficulty is that individual…

Numerical Analysis · Mathematics 2015-05-13 P. F. Tupper

We propose a robust and scalable procedure for general optimization and inference problems on manifolds leveraging the classical idea of `median-of-means' estimation. This is motivated by ubiquitous examples and applications in modern data…

Methodology · Statistics 2020-06-16 Lizhen Lin , Drew Lazar , Bayan Sarpabayeva , David B. Dunson

In the past few years, following the differentiable programming paradigm, there has been a growing interest in computing the gradient information of physical processes (e.g., physical simulation, image rendering). However, such processes…

Robotics · Computer Science 2022-06-24 Quentin Le Lidec , Louis Montaut , Cordelia Schmid , Ivan Laptev , Justin Carpentier

Molecular simulations and biophysical experiments can be used to provide independent and complementary insights into the molecular origin of biological processes. A particularly useful strategy is to use molecular simulations as a modelling…

Chemical Physics · Physics 2019-12-10 Simone Orioli , Andreas Haahr Larsen , Sandro Bottaro , Kresten Lindorff-Larsen

A simple and general implementation of Hamiltonian replica exchange for the popular molecular-dynamics software GROMACS is presented. In this implementation, arbitrarily different Hamiltonians can be used for the different replicas without…

Computational Physics · Physics 2014-09-30 Giovanni Bussi

Chance constraints provide a principled framework to mitigate the risk of high-impact extreme events by modifying the controllable properties of a system. The low probability and rare occurrence of such events, however, impose severe…

Optimization and Control · Mathematics 2022-01-11 Shanyin Tong , Anirudh Subramanyam , Vishwas Rao

Simulation is a fundamental research tool in the computer architecture field. These kinds of tools enable the exploration and evaluation of architectural proposals capturing the most relevant aspects of the highly complex systems under…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-11 Adrian Colaso , Pablo Prieto , Jose-Angel Herrero , Pablo Abad , Valentin Puente , Jose-Angel Gregorio