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We derive deterministic equations for the evolution of non-Gaussian fluctuations in relativistic stochastic hydrodynamics. This is achieved by defining the average local Landau frame and corresponding fluctuating hydrodynamic variables.…

Nuclear Theory · Physics 2026-04-16 Xin An , Gokce Basar , Mikhail Stephanov

We present a sampling method for the transition from relativistic hydrodynamics to particle transport, commonly referred to as particlization, which preserves the local event-by-event conservation of energy, momentum, baryon number,…

High Energy Physics - Phenomenology · Physics 2019-10-31 Dmytro Oliinychenko , Volker Koch

Hydrodynamics is a general theoretical framework for describing the long-time large-distance behaviors of various macroscopic physical systems, with its equations based on conservation laws such as energy-momentum conservation and charge…

Nuclear Theory · Physics 2022-12-06 Duan She , Anping Huang , Defu Hou , Jinfeng Liao

In this proceedings contribution I review recent progress in our understanding of the bulk dynamics of relativistic systems that possess potentially large local rest frame momentum-space anisotropies. In order to deal with these…

Nuclear Theory · Physics 2014-06-17 Michael Strickland

In this lecture note, we present several topics on relativistic hydrodynamics and its application to relativistic heavy ion collisions. In the first part we give a brief introduction to relativistic hydrodynamics in the context of heavy ion…

Nuclear Theory · Physics 2015-05-13 Tetsufumi Hirano , Naomi van der Kolk , Ante Bilandzic

A new set of equations for relativistic viscous hydrodynamics that captures both weak-coupling and strong-coupling physics to second order in gradients has been developed recently. We apply this framework to bulk physics at RHIC, both for…

Nuclear Theory · Physics 2014-11-18 Matthew Luzum , Paul Romatschke

In this paper we consider a new probability sampling methods based on Langevin diffusion dynamics to resolve the problem of existing Monte Carlo algorithms when draw samples from high dimensional target densities. We extent…

Machine Learning · Computer Science 2025-03-31 Z. Zarezadeh , N. Zarezadeh

In this work, we use a tempering-based adaptive particle filter to infer from a partially observed stochastic rotating shallow water (SRSW) model which has been derived using the Stochastic Advection by Lie Transport (SALT) approach. The…

Numerical Analysis · Mathematics 2022-01-03 Peter Jan van Leeuwen , Dan Crisan , Oana Lang , Roland Potthast

We present an algorithm for simulating the equations of ideal magnetohydrodynamics and other systems of differential equations on an unstructured set of points represented by sample particles. Local, third-order, least-squares, polynomial…

Instrumentation and Methods for Astrophysics · Physics 2015-05-30 Jason L. Maron , Colin P. McNally , Mordecai-Mark Mac Low

Hamiltonian dynamics can be used to produce distant proposals for the Metropolis algorithm, thereby avoiding the slow exploration of the state space that results from the diffusive behaviour of simple random-walk proposals. Though…

Computation · Statistics 2021-06-30 Radford M. Neal

A new formulation of second-order viscous hydrodynamics, based on an expansion around a locally anisotropic momentum distribution, is presented. It generalizes the previously developed formalism of anisotropic hydrodynamics (aHydro) to…

Nuclear Theory · Physics 2015-06-22 Ulrich W. Heinz , Dennis Bazow , Michael Strickland

We propose new ideal hydrodynamics in the function space which describes a fluid composed of the 1+1 dimensional real scalar field in the framework of the stochastic variational method (SVM). In the derivation, the thermal equilibrium is…

Nuclear Theory · Physics 2023-03-23 T. Koide , T. Kodama

The challenging problem of conducting fully Bayesian inference for the reaction rate constants governing stochastic kinetic models (SKMs) is considered. Given the challenges underlying this problem, the Markov jump process representation is…

Computation · Statistics 2019-01-10 Andrew Golightly , Emma Bradley , Tom Lowe , Colin S. Gillespie

An algorithm for simulating self-gravitating cosmological astrophysical fluids is presented. The advantages include a large dynamic range, parallelizability, high resolution per grid element and fast execution speed. The code is based on a…

Astrophysics · Physics 2009-10-30 Ue-Li Pen

Modern techniques for physical simulations rely on numerical schemes and mesh-refinement methods to address trade-offs between precision and complexity, but these handcrafted solutions are tedious and require high computational power.…

Machine Learning · Computer Science 2024-02-21 Janny Steeven , Nadri Madiha , Digne Julie , Wolf Christian

For conventional smoothed particle hydrodynamics (SPH), obtaining the static solution of a problem is time-consuming. To address this drawback, we propose an efficient dynamic relaxation method by adding large artificial-viscosity-based…

Computational Engineering, Finance, and Science · Computer Science 2021-03-17 Yujie Zhu , Chi Zhang , Xiangyu Hu

We study linearized stability in first-order relativistic viscous hydrodynamics in the most general frame. There is a region in the parameter space of transport coefficients where the perturbations of the equilibrium state are stable. This…

High Energy Physics - Theory · Physics 2019-10-22 Pavel Kovtun

Relativistic non-ideal fluid dynamics is formulated in 3+1 space--time dimensions. The equations governing dissipative relativistic hydrodynamics are given in terms of the time and the 3-space quantities which correspond to those familiar…

Nuclear Theory · Physics 2008-11-26 Azwinndini Muronga

This study considers using Metropolis-Hastings algorithm for stochastic simulation of chemical reactions. The proposed method uses SSA (Stochastic Simulation Algorithm) distribution which is a standard method for solving well-stirred…

Numerical Analysis · Computer Science 2014-10-31 Azam S. Zavar Moosavi , Paul Tranquilli , Adrian Sandu

The characteristic decomposition for GRMHD is not known in a form useful for current numerical simulations. This prevents us from using the most accurate known computational methods, such as full-wave Riemann solvers. In this paper, we…

General Relativity and Quantum Cosmology · Physics 2025-11-19 Saul A. Teukolsky