210 citations · 678 across the 40 of their papers we have counts for
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ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems
Veronica Saz Ulibarrena, Simon Portegies Zwart
Astrophysical simulations frequently address multi-scale, multi-physics problems through subsystem decomposition, problem-tailored integration schemes, and coupling on fixed manual…
Nemesis: A Multi-Scale, Multi-Physics Algorithm for Astrophysics
Erwan Hochart, Simon Portegies Zwart
In this work, an updated version of the multi-scale, multi-physics algorithm, Nemesis which makes use of the Astrophysical Multipurpose Software Environment (AMUSE). The algorithm…
Reinforcement Learning for Adaptive Time-Stepping in the Chaotic Gravitational Three-Body Problem
Veronica Saz Ulibarrena, Simon Portegies Zwart
Many problems in astrophysics cover multiple orders of magnitude in spatial and temporal scales. While simulating systems that experience rapid changes in these conditions, it is e…
Venice: a multi-scale operator-splitting algorithm for multi-physics simulations
Maite Wilhelm, Simon Portegies Zwart
We present {\sc Venice}, an operator splitting algorithm to integrate a numerical model on a hierarchy of timescales. {\sc Venice} allows a wide variety of different physical proce…
Gargantuan chaotic gravitational three-body systems and their irreversibility to the Planck length
Tjarda Boekholt, Simon Portegies Zwart, Mauri Valtonen
Chaos is present in most stellar dynamical systems and manifests itself through the exponential growth of small perturbations. Exponential divergence drives time irreversibility an…