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

Author:
Zeviel Imani, Shuchin Aeron, Taritree Wongjirad
Keyword:
High Energy Physics - Experiment, High Energy Physics - Experiment (hep-ex)
journal:
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date:
2023-07-24 16:00:00
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.
PDF: Score-based Diffusion Models for Generating Liquid Argon Time Projection Chamber Images.pdf
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