In particle-based algorithms, the effect of binary collisions is commonly described in a statistical way, using Monte Carlo techniques. It is shown that, in the relativistic regime, stringent constraints should be considered on the sampling of particle pairs for collision, which are critical to ensure physically meaningful results, and that nonrelativistic sampling criteria e.g., uniform random pairing yield qualitatively wrong results, including equilibrium distributions that differ from the theoretical Jüttner distribution. A general procedure for relativistically consistent algorithms is provided, and verified with three-dimensional Monte Carlo simulations, thus opening the way to the numerical exploration of the statistical properties of collisional relativistic systems.

Statistical kinetic treatment of relativistic binary collisions / Peano, F; Marti, M; Silva, L. O.; Coppa, Gianni. - In: PHYSICAL REVIEW E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS. - ISSN 1539-3755. - 79:(2009), pp. 025701(1)-025701(4). [10.1103/PhysRevE.79.025701]

Statistical kinetic treatment of relativistic binary collisions

COPPA, Gianni
2009

Abstract

In particle-based algorithms, the effect of binary collisions is commonly described in a statistical way, using Monte Carlo techniques. It is shown that, in the relativistic regime, stringent constraints should be considered on the sampling of particle pairs for collision, which are critical to ensure physically meaningful results, and that nonrelativistic sampling criteria e.g., uniform random pairing yield qualitatively wrong results, including equilibrium distributions that differ from the theoretical Jüttner distribution. A general procedure for relativistically consistent algorithms is provided, and verified with three-dimensional Monte Carlo simulations, thus opening the way to the numerical exploration of the statistical properties of collisional relativistic systems.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/1916153
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