Bi-CFM learns bidirectional mappings between initial and final state distributions to solve ill-posed inverse problems in chaotic systems, reporting metric improvements and speedups on Lorenz variants plus conservation-respecting results on three-body and globular cluster data.
Million-Body Star Cluster Simulations: Comparisons between Monte Carlo and Direct $N$-body
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abstract
We present the first detailed comparison between million-body globular cluster simulations computed with a H\'enon-type Monte Carlo code, CMC, and a direct $N$-body code, NBODY6++GPU. Both simulations start from an identical cluster model with $10^6$ particles, and include all of the relevant physics needed to treat the system in a highly realistic way. With the two codes "frozen" (no fine-tuning of any free parameters or internal algorithms of the codes) we find excellent agreement in the overall evolution of the two models. Furthermore, we find that in both models, large numbers of stellar-mass black holes (> 1000) are retained for 12 Gyr. Thus, the very accurate direct $N$-body approach confirms recent predictions that black holes can be retained in present-day, old globular clusters. We find only minor disagreements between the two models and attribute these to the small-$N$ dynamics driving the evolution of the cluster core for which the Monte Carlo assumptions are less ideal. Based on the overwhelming general agreement between the two models computed using these vastly different techniques, we conclude that our Monte Carlo approach, which is more approximate, but dramatically faster compared to the direct $N$-body, is capable of producing a very accurate description of the long-term evolution of massive globular clusters even when the clusters contain large populations of stellar-mass black holes.
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2026 1verdicts
UNVERDICTED 1representative citing papers
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Solving Inverse Problems of Chaotic Systems with Bidirectional Conditional Flow Matching
Bi-CFM learns bidirectional mappings between initial and final state distributions to solve ill-posed inverse problems in chaotic systems, reporting metric improvements and speedups on Lorenz variants plus conservation-respecting results on three-body and globular cluster data.