Speaker
Description
Optical-photon tracking is a major computational bottleneck in segmented plastic-scintillator detectors, where a single particle crossing can produce tens of thousands of photons. We present FastSimu, a conditional generative surrogate for the response of a 25-mm scintillator voxel at the first entry of photons into three orthogonal wavelength-shifting fibers. Conditioned on a multidimensional muon state vector, FastSimu generates per-fiber photon counts, timing summaries, and spatial distributions.
The model is designed around the structure of the detector response: a heavy-tailed multivariate density model captures correlated scalar quantities, a diffusion model generates normalized spatial profiles, and multinomial sampling converts the generated totals and profiles into integer histograms with exact per-fiber count conservation. This combination provides physically valid outputs without relying on bin-wise independent predictions.
FastSimu is evaluated on 200,000 Geant4 events. On held-out data, it closely reproduces the principal Geant4 distributions of photon counts, timing, and fiber-entry positions, with an average spatial discrepancy well below one histogram bin. In paired single-core benchmarks on the same workers, FastSimu achieves roughly a $4\times10^{3}$ improvement in amortized throughput at batch size 100.
Because the voxel response can be evaluated independently and in parallel, FastSimu provides a scalable building block for hybrid simulation of large scintillator arrays. Downstream wavelength shifting, fiber transport, and SiPM response remain future extensions.