Speaker
Kevin Pedro
(Fermi National Accelerator Lab. (US))
Description
Full detector simulations using Geant4 are highly accurate but computationally intensive, while existing fast simulation techniques may not provide sufficient accuracy for all purposes. Machine learning offers potential paths to achieve both high speed and high accuracy. This may be especially important to address the computational challenges posed by the HL-LHC. Ongoing efforts from both inside and outside the LHC experimental collaborations will be presented. Challenges and opportunities will also be discussed.
Author
Kevin Pedro
(Fermi National Accelerator Lab. (US))
