AI RESEARCH
JetPrism: diagnosing convergence for generative simulation and inverse problems in nuclear physics
arXiv CS.LG
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ArXi:2604.01313v1 Announce Type: new High-fidelity Monte Carlo simulations and complex inverse problems, such as mapping smeared experimental observations to ground-truth states, are computationally intensive yet essential for robust data analysis. Conditional Flow Matching (CFM) offers a mathematically robust approach to accelerating these tasks, but we nstrate its standard