Machine-learning optimization produces candidate truncated modular-invariant partition functions for 2d CFTs in the central-charge window 1 to 8/7, indicating a continuous solution space and a stricter spectral-gap bound than the prior c/6 + 1/3 limit.
How to Trust Learned Loop Amplitudes
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A review of initiatives to make LHC Monte Carlo event generations available as open data to minimize redundant simulations and resource use.
A primer that surveys the architecture, methodologies, computational challenges, and future trajectory of the Monte Carlo event generator ecosystem in collider physics.
citing papers explorer
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Descending into the Modular Bootstrap
Machine-learning optimization produces candidate truncated modular-invariant partition functions for 2d CFTs in the central-charge window 1 to 8/7, indicating a continuous solution space and a stricter spectral-gap bound than the prior c/6 + 1/3 limit.
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Open LHC Monte Carlo Event Generation
A review of initiatives to make LHC Monte Carlo event generations available as open data to minimize redundant simulations and resource use.
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The Monte Carlo Ecosystem in High-Energy Physics: A Primer
A primer that surveys the architecture, methodologies, computational challenges, and future trajectory of the Monte Carlo event generator ecosystem in collider physics.