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For several decades now, Bayesian inference techniques have been applied to theories of particle physics, cosmology and astrophysics to obtain the probability density functions of their free parameters. In this study, we review and compare…

High Energy Physics - Phenomenology · Physics 2025-09-03 Joshua Albert , Csaba Balazs , Andrew Fowlie , Will Handley , Nicholas Hunt-Smith , Roberto Ruiz de Austri , Martin White

Novel fully discrete schemes are developed to numerically approximate a semilinear stochastic wave equation driven by additive space-time white noise. Spectral Galerkin method is proposed for the spatial discretization, and exponential time…

Numerical Analysis · Mathematics 2020-08-10 Xiaojie Wang , Siqing Gan , Jingtian Tang

This paper introduces an efficient algorithm for computing the best approximation of a given matrix onto the intersection of linear equalities, inequalities and the doubly nonnegative cone (the cone of all positive semidefinite matrices…

Optimization and Control · Mathematics 2018-03-20 Ying Cui , Defeng Sun , Kim-Chuan Toh

This chapter offers a comprehensive introduction to the least-squares neural network (LSNN) method introduced in [14,16], for solving scalar first-order hyperbolic partial differential equations, specifically linear advection-reaction…

Numerical Analysis · Mathematics 2026-01-29 Min Liu , Zhiqiang Cai

The Crank-Nicolson (short for C-N) scheme for solving {\it backward stochastic differential equation} (BSDE), driven by Brownian motions, was first developed by the authors W. Zhao, L. Chen and S. Peng [SIAM J. Sci. Comput., 28 (2006),…

Numerical Analysis · Mathematics 2017-02-17 Yang Li , Jie Yang , Weidong Zhao

Friedrichs' systems (FS) are symmetric positive linear systems of first-order partial differential equations (PDEs), which provide a unified framework for describing various elliptic, parabolic and hyperbolic semi-linear PDEs such as the…

Numerical Analysis · Mathematics 2023-08-08 Francesco Romor , Davide Torlo , Gianluigi Rozza

In this paper, neural network approximation methods are developed for elliptic partial differential equations with multi-frequency solutions. Neural network work approximation methods have advantages over classical approaches in that they…

Numerical Analysis · Mathematics 2023-11-08 Deok-Kyu Jang , Hyea Hyun Kim , Kyungsoo Kim

This work develops a new method to calculate non-perturbative corrections in one-dimensional Quantum Mechanics, based on trans-series solutions to the refined holomorphic anomaly equations of topological string theory. The method can be…

High Energy Physics - Theory · Physics 2018-10-15 Santiago Codesido , Marcos Marino , Ricardo Schiappa

This paper is concerned with the approximation of solutions to a class of second order non linear abstract differential equations. The finite-dimensional approximate solutions of the given system are built with the aid of the projection…

Numerical Analysis · Mathematics 2024-02-02 Shahin Ansari , Muslim Malik , Javid Ali

Computational methods for fractional differential equations exhibit essential instability. Even a minor modification of the coefficients or other entry data may switch good results to the divergent. The goal of this paper is to suggest the…

Numerical Analysis · Mathematics 2021-12-20 P. B. Dubovski , J. A. Slepoi

We study the evolution of cosmological perturbations, using a hybrid approximation scheme which upgrades the weak-field limit of Einstein's field equations to account for post-Newtonian scalar and vector metric perturbations and for…

Astrophysics · Physics 2007-05-23 Carmelita Carbone , Sabino Matarrese

Update formulas for the Hessian approximations in quasi-Newton methods such as BFGS can be derived as analytical solutions to certain nearest-matrix problems. In this article, we propose a similar idea for deriving new limited memory…

Optimization and Control · Mathematics 2024-03-06 Erik Berglund , Mikael Johansson

We present optimal quadratic estimators for the Fourier analysis of cosmological surveys that detect several different types of tracers of large-scale structure. Our estimators can be used to simultaneously fit the matter power spectrum and…

Cosmology and Nongalactic Astrophysics · Physics 2015-12-09 L. Raul Abramo , Lucas F. Secco , Arthur Loureiro

Quasinormal modes describe the ringdown of compact objects deformed by small perturbations. In generic theories of gravity that extend General Relativity, the linearized dynamics of these perturbations is described by a system of coupled…

General Relativity and Quantum Cosmology · Physics 2023-10-04 Lam Hui , Alessandro Podo , Luca Santoni , Enrico Trincherini

The Shifman-Vainshtein-Zakharov (SVZ) sum rules provide a method to obtain trans-series expansions in many quantum field theories, in which exponentially small corrections are calculated by combining the operator product expansion with the…

High Energy Physics - Theory · Physics 2025-03-19 Marcos Marino , Ramon Miravitllas

Perturbation theory of large-scale structures of the Universe at next-to-leading order and next-to-next-to-leading order provides us with predictions of cosmological statistics at sub-percent level in the mildly non-linear regime. Its use…

Cosmology and Nongalactic Astrophysics · Physics 2021-11-08 Ken Osato , Takahiro Nishimichi , Atsushi Taruya , Francis Bernardeau

We study linear perturbations of the Friedmann-Lemaitre-Robertson-Walker (FLRW) cosmological model in the Regge-Wheeler formalism which is a standard framework to study perturbations of spherically-symmetric black holes. In particular, we…

General Relativity and Quantum Cosmology · Physics 2020-04-15 Andrzej Rostworowski

We present a novel numerical framework for studying nonlinear dispersive equations in higher-dimensional settings, specifically designed for solutions featuring traveling waves along a preferred axis (or field-aligned traveling waves).…

Numerical Analysis · Mathematics 2026-04-21 Christian Klein , Svetlana Roudenko , Nikola Stoilov

The conforming finite element Galerkin method is applied to discretise in the spatial direction for a class of strongly nonlinear parabolic problems. Using elliptic projection of the associated linearised stationary problem with Gronwall…

Numerical Analysis · Mathematics 2021-08-04 Ambit Kumar Pany , Morrakot Khebchareon , Amiya K. Pani

Stochastic dynamical systems provide essential mathematical frameworks for modeling complex real-world phenomena. The Fokker-Planck-Kolmogorov (FPK) equation governs the evolution of probability density functions associated with stochastic…

Computation · Statistics 2025-10-13 Yi Zhang , Yiting Duan , Xiangjun Wang , Zhikun Zhang