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Hamiltonian formulations of lattice field theories provide access to real-time dynamics, but their simulation is difficult to implement efficiently. Trotter-Suzuki decompositions are at the center of time evolution computation, either on…

High Energy Physics - Lattice · Physics 2026-02-25 Marko Maležič , Johann Ostmeyer

We introduce a fast Fourier spectral method for the multi-species Boltzmann collision operator. The method retains the riveting properties of the single-species fast spectral method (Gamba et al. SIAM J. Sci. Comput., 39 pp. B658--B674…

Computational Physics · Physics 2019-05-07 Shashank Jaiswal , Alina A. Alexeenko , Jingwei Hu

The generalized massive Thirring model (GMT) with three fermion species is bosonized in the context of the functional integral and operator formulations and shown to be equivalent to a generalized sine-Gordon model (GSG) with three…

High Energy Physics - Theory · Physics 2009-11-10 Harold Blas

We present a mapping of elementary fermion operators onto a quadratic form of composite fermionic and bosonic operators. The mapping is an exact isomorphism as long as the physical constraint of one composite particle per cluster is…

We study the generalized forward-reflected-backward (GFRB) method, an extension of the forward-reflected-backward (FRB) scheme due to Malitsky and Tam, for solving monotone inclusion problems in real Hilbert spaces. We first analyze GFRB…

Optimization and Control · Mathematics 2026-01-22 Santanu Soe , V. Vetrivel , Jen-Chih Yao

We propose an exponential integrator Fourier pseudospectral method DEI-FP for solving the "Good" Boussinesq (GB) equation. The numerical scheme is based on a Deuflhard-type exponential integrator and a Fourier pseudospectral method for…

Numerical Analysis · Mathematics 2019-10-09 Chunmei Su , Wenqi Yao

A generalized Gaussian process model (GGPM) is a unifying framework that encompasses many existing Gaussian process (GP) models, such as GP regression, classification, and counting. In the GGPM framework, the observation likelihood of the…

Machine Learning · Statistics 2013-11-28 Lifeng Shang , Antoni B. Chan

Path integral molecular dynamics (PIMD) has been successfully applied to perform simulations of large bosonic systems in a recent work (Hirshberg et al., PNAS, 116, 21445 (2019)). In this work we extend PIMD techniques to study Green's…

Quantum Physics · Physics 2022-04-22 Xiong Yunuo , Xiong Hongwei

We present a unified algorithmic framework for quantum simulation of non-unitary dynamics and matrix functions, governed by the principle of spectral aliasing derived from the Poisson Summation Formula (PSF). By reinterpreting…

Quantum Physics · Physics 2026-04-21 Chao Wang , Xi-Ning Zhuang , Menghan Dou , Zhao-Yun Chen , Guo-Ping Guo

In the last few years it has been proposed a one-dimensional factorization of the fermion determinant in lattice QCD with Wilson-type fermions that leads to a block-local action of the auxiliary bosonic fields. Here we propose a…

High Energy Physics - Lattice · Physics 2022-04-20 Leonardo Giusti , Matteo Saccardi

This paper introduces the generalized forward-backward splitting algorithm for minimizing convex functions of the form $F + \sum_{i=1}^n G_i$, where $F$ has a Lipschitz-continuous gradient and the $G_i$'s are simple in the sense that their…

Optimization and Control · Mathematics 2014-02-11 Hugo Raguet , Jalal Fadili , Gabriel Peyré

Within the soft collinear effective theory (SCET), we derive a factorization theorem which resums Sudakov logarithms $(\alpha_s\ln^2(-t))^n$ to all orders in the quark-in-quark generalized parton distribution (GPD) at large momentum…

High Energy Physics - Phenomenology · Physics 2025-11-12 Yoshitaka Hatta , Jakob Schoenleber

The direct simulation Monte Carlo (DSMC) method is widely used to describe rarefied gas flows. The DSMC method accounts for the transport and collisions of computational particles, resulting in higher computational costs in the continuum…

Computational Physics · Physics 2025-08-11 Joonbeom Kim , Eunji Jun

A common problem in cosmology is to integrate the product of two or more spherical Bessel functions (sBFs) with different configuration-space arguments against the power spectrum or its square, weighted by powers of wavenumber. Naively…

Cosmology and Nongalactic Astrophysics · Physics 2019-12-03 Zachary Slepian , Yin Li , Marcel Schmittfull , Zvonimir Vlah

Symmetric Nonnegative Matrix Factorization (SNMF) models arise naturally as simple reformulations of many standard clustering algorithms including the popular spectral clustering method. Recent work has demonstrated that an elementary…

Computer Vision and Pattern Recognition · Computer Science 2016-09-20 Reza Borhani , Jeremy Watt , Aggelos Katsaggelos

A parallel, blocked, one-sided Hari--Zimmermann algorithm for the generalized singular value decomposition (GSVD) of a real or a complex matrix pair $(F,G)$ is here proposed, where $F$ and $G$ have the same number of columns, and are both…

Numerical Analysis · Mathematics 2021-02-18 Vedran Novaković , Sanja Singer

The potential of employing higher orders of the Trotter-Suzuki decomposition of the evolution operator for more effective simulations of quantum systems on a noisy quantum computer is explored. By examining the transverse-field Ising model…

Quantum Physics · Physics 2024-12-31 A. A. Avtandilyan , W. V. Pogosov

Accurate modelling of the interaction between fast electrons and partially ionized atoms is important for evaluating tokamak disruption mitigation schemes based on material injection. This requires accounting for the effect of screening of…

Plasma Physics · Physics 2018-11-28 L Hesslow , O Embréus , M Hoppe , T C DuBois , G Papp , M Rahm , T Fülöp

Path integral techniques in collective fields are shown to be a useful analytical tool to reformulate a field theory defined in terms of microscopic quark (gluon) degrees of freedom as an effective theory of collective boson (meson) fields.…

High Energy Physics - Phenomenology · Physics 2009-10-30 D. Ebert

In Bayesian inference, we are usually interested in the numerical approximation of integrals that are posterior expectations or marginal likelihoods (a.k.a., Bayesian evidence). In this paper, we focus on the computation of the posterior…

Computation · Statistics 2025-02-05 F. Llorente , L. Martino , D. Delgado