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A solution to the ultra-relativistic strong explosion problem with a non-power law density gradient is delineated. We consider a blast wave expanding into a density profile falling off as a steep radial power-law with small, spherically…

High Energy Astrophysical Phenomena · Physics 2014-11-20 Yonatan Oren , Re'em Sari

A new self-similar solution describing the dynamical condensation of a radiative gas is investigated under a plane-parallel geometry. The dynamical condensation is caused by thermal instability. The solution is applicable to generic flow…

Astrophysics · Physics 2009-11-13 Kazunari Iwasaki , Toru Tsuribe

This paper addresses the construction and the stability of self-similar solutions to the isentropic compressible Euler equations. These solutions model a gas that implodes isotropically, ending in a singularity formation in finite time. The…

Analysis of PDEs · Mathematics 2021-09-17 Anxo Biasi

Motivated by recent breakthrough on smooth imploding solutions of compressible Euler, we construct self-similar smooth imploding solutions of isentropic relativistic Euler equations with isothermal equation of state $p=\frac1\ell\varrho$…

Analysis of PDEs · Mathematics 2024-03-19 Feng Shao , Dongyi Wei , Zhifei Zhang

We solve the continuation problem for the non-isentropic Euler equations following the collapse of an imploding shock wave. More precisely, we prove that the self-similar G\"uderley imploding shock solutions for a perfect gas with adiabatic…

Analysis of PDEs · Mathematics 2024-03-20 Juhi Jang , Jiaqi Liu , Matthew Schrecker

We study the 2D isentropic Euler equations with the ideal gas law. We exhibit a set of smooth initial data that give rise to shock formation at a single point near the planar symmetry. These solutions are associated with non-zero vorticity…

Analysis of PDEs · Mathematics 2023-03-01 Wenze Su

We extend Guderley's problem of finding a self-similar scaling solution for a converging cylindrical or spherical shock wave from the ideal gas case to the case of flows with an arbitrary equation of state closure model, giving necessary…

Fluid Dynamics · Physics 2017-07-13 Zachary M. Boyd , Scott D. Ramsey , Roy S. Baty

We explore self-similar dynamical processes in a spherical isothermal self-gravitational fluid with an emphasis on shocks and outline astrophysical applications of such shock solutions. The previous similarity shock solutions of Tsai & Hsu…

Astrophysics · Physics 2009-11-13 Fu-Yan Bian , Yu-Qing Lou

(accepted for publication in the Ap.J.) I present a general classification of self-similar solutions to the equations of gravitational hydrodynamics that contain many previous results as special cases. For cold flows with spherical…

Astrophysics · Physics 2009-10-22 Ue-Li Pen

We derive self similar solutions for ultra-relativistic shock waves propagating into cold material of powerlaw density profile in radius rho ~ r^-k. We treat both implosions and explosions in three geometries: planar, cylindrical and…

Astrophysics · Physics 2009-11-11 Re'em Sari

Probabilistic solvers for ordinary differential equations (ODEs) have emerged as an efficient framework for uncertainty quantification and inference on dynamical systems. In this work, we explain the mathematical assumptions and detailed…

Machine Learning · Statistics 2021-10-25 Nicholas Krämer , Nathanael Bosch , Jonathan Schmidt , Philipp Hennig

The solution of self-similar shock dynamics satisfying the inviscid Burgers equation are provided in closed form for planar, cylindrical and spherical problems. The approach follows Lee's method for obtaining self-similar solutions for the…

Fluid Dynamics · Physics 2023-11-17 Matei Ioan Rădulescu

Differential Equations are among the most important Mathematical tools used in creating models in the science, engineering, economics, mathematics, physics, aeronautics, astronomy, dynamics, biology, chemistry, medicine, environmental…

History and Overview · Mathematics 2020-12-15 Byakatonda Denis

The smoothed particle hydrodynamics (SPH) method is a useful numerical tool for the study of a variety of astrophysical and planetlogical problems. However, it turned out that the standard SPH algorithm has problems in dealing with…

Instrumentation and Methods for Astrophysics · Physics 2015-06-16 Natsuki Hosono , Takayuki R. Saitoh , Junichiro Makino

Probabilistic solvers for ordinary differential equations (ODEs) provide efficient quantification of numerical uncertainty associated with simulation of dynamical systems. Their convergence rates have been established by a growing body of…

Machine Learning · Statistics 2020-12-21 Nicholas Krämer , Philipp Hennig

We employ granular hydrodynamics to investigate a paradigmatic problem of clustering of particles in a freely cooling dilute granular gas. We consider large-scale hydrodynamic motions where the viscosity and heat conduction can be…

Soft Condensed Matter · Physics 2009-11-13 Itzhak Fouxon , Baruch Meerson , Michael Assaf , Eli Livne

The ultra-relativistic Euler equations for an ideal gas are described in terms of the pressure $p$, the spatial part $\underline{u} \in \R^3$ of the dimensionless four-velocity and the particle density $n$. Radially symmetric solutions of…

Numerical Analysis · Mathematics 2020-02-05 Matthias Kunik , Hailiang Liu , Gerald Warnecke

In this paper we extend and complement some recent results by Chiodaroli, De Lellis and Kreml on the well-posedness issue for weak solutions of the compressible isentropic Euler system in $2$ space dimensions with pressure law…

Analysis of PDEs · Mathematics 2014-08-26 Elisabetta Chiodaroli , Ondřej Kreml

Shocks due to hyperbolic partial differential equations (PDEs) appear throughout mathematics and science. The canonical example is shock formation in the inviscid Burgers' equation $\frac{\partial u}{\partial t}+u\frac{\partial u}{\partial…

Analysis of PDEs · Mathematics 2026-04-14 Jun Eshima , Luc Deike , Howard A. Stone

Recent work has introduced a simple numerical method for solving partial differential equations (PDEs) with deep neural networks (DNNs). This paper reviews and extends the method while applying it to analyze one of the most fundamental…

Machine Learning · Computer Science 2019-05-14 Craig Michoski , Milos Milosavljevic , Todd Oliver , David Hatch