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Register a new userMachine Learning for Conservative-to-Primitive in Relativistic Hydrodynamics
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The numerical solution of relativistic hydrodynamics equations in conservative form requires root-finding algorithms that invert the conservative-to-primitive variables map. These algorithms employ the equation of state of the fluid and can be computationally demanding for applications involving sophisticated microphysics models. This work explores the use of machine learning methods to speed up the recovery of primitives in relativistic hydrodynamics. Artificial neural networks are trained to replace either the interpolations of a tabulated equation of state or directly the conservative-to-primitive map. The application of these neural networks to simple benchmark problems show that both approaches improve over traditional root finders with tabular equation-of-state and multi-dimensional interpolations. In particular, the neural networks for the conservative-to-primitive map accelerate the variable recovery by more than an order of magnitude over standard methods while maintaining accuracy. Neural networks are thus an interesting option to improve the speed and robustness of relativistic hydrodynamics algorithms.
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The stability and causality of the Landau-Lifshitz theory and the Israel-Stewart type causal dissipative hydrodynamics are discussed. We show that the problem of acausality and instability are correlated in relativistic dissipative hydrodynamics and instability is induced by acausality. We further discuss the stability of the scaling solution. The scaling solution of the causal dissipative hydrodynamics can be unstable against inhomogeneous perturbations.
A Riemann problem with prescribed initial conditions will produce one of three possible wave patterns corresponding to the propagation of the different discontinuities that will be produced once the system is allowed to relax. In general, when solving the Riemann problem numerically, the determination of the specific wave pattern produced is obtained through some initial guess which can be successively discarded or improved. We here discuss a new procedure, suitable for implementation in an exact Riemann solver in one dimension, which removes the initial ambiguity in the wave pattern. In particular we focus our attention on the relativistic velocity jump between the two initial states and use this to determine, through some analytic conditions, the wave pattern produced by the decay of the initial discontinuity. The exact Riemann problem is then solved by means of calculating the root of a nonlinear equation. Interestingly, in the case of two rarefaction waves, this root can even be found analytically. Our procedure is straightforward to implement numerically and improves the efficiency of numerical codes based on exact Riemann solvers.
Discontinuous Galerkin (DG) methods provide a means to obtain high-order accurate solutions in regions of smooth fluid flow while, with the aid of limiters, still resolving strong shocks. These and other properties make DG methods attractive for solving problems involving hydrodynamics; e.g., the core-collapse supernova problem. With that in mind we are developing a DG solver for the general relativistic, ideal hydrodynamics equations under a 3+1 decomposition of spacetime, assuming a conformally-flat approximation to general relativity. With the aid of limiters we verify the accuracy and robustness of our code with several difficult test-problems: a special relativistic Kelvin--Helmholtz instability problem, a two-dimensional special relativistic Riemann problem, and a one- and two-dimensional general relativistic standing accretion shock (SAS) problem. We find good agreement with published results, where available. We also establish sufficient resolution for the 1D SAS problem and find encouraging results regarding the standing accretion shock instability (SASI) in 2D.
Many phenomena in collisionless plasma physics require a kinetic description. The evolution of the phase space density can be modeled by means of the Vlasov equation, which has to be solved numerically in most of the relevant cases. One of the problems that often arise in such simulations is the violation of important physical conservation laws. Numerical diffusion in phase space translates into unphysical heating, which can increase the overall energy significantly, depending on the time scale and the plasma regime. In this paper, a general and straightforward way of improving conservation properties of Vlasov schemes is presented that can potentially be applied to a variety of different codes. The basic idea is to use fluid models with good conservation properties for correcting kinetic models. The higher moments that are missing in the fluid models are provided by the kinetic codes, so that both kinetic and fluid codes compensate the weaknesses of each other in a closed feedback loop.
We present modifications to the Athena++ framework to enable use of general equations of state (EOS). Part of our motivation for doing so is to model transient astrophysics phenomena, as these types of events are often not well approximated by an ideal gas. This necessitated changes to the Riemann solvers implemented in Athena++. We discuss the adjustments made to the HLLC, and HLLD solvers and EOS calls required for arbitrary EOS. We demonstrate the reliability of our code in a number of tests which utilize a relatively simple, but non-trivial EOS based on hydrogen ionization, appropriate for the transition from atomic to ionized hydrogen. Additionally, we perform tests using an electron-positron Helmholtz EOS, appropriate for regimes where nuclear statistical equilibrium is a good approximation. These new complex EOS tests overall show that our modifications to Athena++ accurately solve the Riemann problem with linear convergence and linear-wave tests with quadratic convergence. We provide our test solutions as a means to check the accuracy of other hydrodynamic codes. Our tests and additions to Athena++ will enable further research into (magneto)hydrodynamic problems where realistic treatments of the EOS are required.
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