Score-based Diffusion Models for Generating Liquid Argon Time Projection Chamber Images

2023/07/25 by Zeviel Imani, Imani, Zeviel, Shuchin Aeron +3 · 1 citation
Computer Science · #Advanced Image Processing Techniques #Advanced Vision and Imaging #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #Medical Image Segmentation Techniques

paper · pdf · doi:10.48550/arxiv.2307.13687

openalex publication_date 2023/07/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

For the first time, we show high-fidelity generation of LArTPC-like data using a generative neural network. This demonstrates that methods developed for natural images do transfer to LArTPC-produced images, which, in contrast to natural images, are globally sparse but locally dense. We present the score-based diffusion method employed. We evaluate the fidelity of the generated images using several quality metrics, including modified measures used to evaluate natural images, comparisons between high-dimensional distributions, and comparisons relevant to LArTPC experiments.

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