Speaker
Description
FlashSim is an end-to-end machine-learning simulation in CMS that produces analysis-level events (NanoAOD) directly from generator-level input, at a small fraction of the cost of detailed simulation. Each reconstructed object is generated by its own model, continuous normalizing flows trained with flow matching, conditioned on generator-level information and the per-object models are combined at inference to build complete events, keeping the physical and identification variables correlated as in data. Recent developments make the output more complete and bring it closer to what analyses actually use. We show comparisons with fully simulated samples on analysis-level observables, indicating that FlashSim now covers more of what real analyses need.