Diffusion Models Generate IACT Images for Gamma-Ray Astronomy

This study presents a novel application of score-based diffusion models for generating Imaging Air Cherenkov Telescope (IACT) images. The models are used to simulate both gamma-ray and proton showers, addressing the computational challenges associated with traditional air-shower simulations. The ability to generate monoscopic images with nearly 2,000 pixels represents a significant advancement in the field.

The study's findings demonstrate that diffusion models outperform Wasserstein GANs, particularly in generating proton events. This is crucial because hadronic showers dominate the background in gamma-ray astronomy, and accurate modeling is essential for reliable analysis. The models' ability to accurately reproduce high-level correlations and generate events statistically indistinguishable from simulations at the analysis level underscores their potential as an analysis-ready surrogate model of a single IACT.

This research has significant implications for fast instrument response generation, detector optimization, and connected downstream tasks. By providing an efficient alternative to computationally intensive simulations, diffusion models can accelerate the pace of discovery in gamma-ray astronomy. However, further research is needed to extend the models to stereoscopic IACT data and to address potential limitations related to computational cost.

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