Speaker
Description
Optical photon tracking in Geant4 is the dominant cost in simulating large neutrino detectors that rely on scintillation or Cherenkov light, and it caps the size of training samples available for ML-based reconstruction. Simphony (old name eic-opticks) is a GPU optical simulation framework built on Opticks (originally developed for JUNO) that runs inside a standard Geant4 job and delivers two orders of magnitude speedup over CPU tracking. We extend Opticks with asynchronous GPU execution that overlaps optical propagation with Geant4 stepping on the CPU, cutting walltime further on production workflows. We have also implemented wavelength-shifting that is essential for certain neutrino detectors.
On top of the speed gains, simphony propagates Monte Carlo truth through the GPU stage, every detected photon carries the pointer to the charged particle that created it. The truth propagation preserves the per-photon labels that supervised training on photon-level tasks requires with minimal performance penalty.
We report validation on a simplified DUNE FD2-VD geometry against Geant4. Together, these capabilities open up workloads that were previously impractical at scale: ML training sample generation, end-to-end detector geometry optimization, and systematic uncertainty studies that require scanning many optical configurations. Simphony is packaged as a framework-independent module so other experiments are able to adopt it.
