Machine-Learning Compression for Particle Physics Discoveries. (arXiv:2210.11489v1 [hep-ph])

In collider-based particle and nuclear physics experiments, data are produced
at such extreme rates that only a subset can be recorded for later analysis.
Typically, algorithms select individual collision events for preservation and
store the complete experimental response. A relatively new alternative strategy
is to additionally save a partial record for a larger subset of events,
allowing for later specific analysis of a larger fraction of events. We propose
a strategy that bridges these paradigms by compressing entire events for …

arxiv compression discoveries machine particle physics physics