Low-energy Electron-track Imaging for a Liquid Argon Time-projection-chamber Telescope Concept Using Probabilistic Deep Learning
[1];
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- SLAC National Accelerator Laboratory, Menlo Park, CA (United States); Stanford University, CA (United States). Kavli Institute for Particle Astrophysics & Cosmology
- SLAC National Accelerator Laboratory, Menlo Park, CA (United States)
- Stanford University, CA (United States). Kavli Institute for Particle Astrophysics & Cosmology; Stanford University, CA (United States); Hansen Experimental Physic Laboratory, Stanford, CA (United States)
- Stanford University, CA (United States)
- SLAC National Accelerator Laboratory, Menlo Park, CA (United States); Stanford University, CA (United States). Kavli Institute for Particle Astrophysics & Cosmology; Vatican Observatory (Vatican City State)
The GammaTPC is an MeV-scale single-phase liquid argon time-projection-chamber gamma-ray telescope concept with a novel dual-scale pixel-based charge-readout system. It promises to enable a significant improvement in sensitivity to MeV-scale gamma rays over previous telescopes. The novel pixel-based charge readout allows for imaging of the tracks of electrons scattered by Compton interactions of incident gamma rays. The two primary contributors to the accuracy of a Compton telescope in reconstructing an incident gamma-ray’s original direction are its energy and position resolution. In this work, we focus on using deep learning to optimize the reconstruction of the initial position and direction of electrons scattered in Compton interactions, including using probabilistic models to estimate predictive uncertainty. We show that the deep-learning models are able to predict locations of Compton scatters of MeV-scale gamma rays from simulated 500 μm pixel-based data to better than 1 mm rms error and are sensitive to the initial direction of the scattered electron. We compare and contrast different deep-learning uncertainty estimation algorithms for reconstruction applications. Additionally, we show that event-by-event estimates of the uncertainty of the locations of the Compton scatters can be used to select those events that were reconstructed most accurately, leading to improvement in locating the origin of gamma-ray sources on the sky.
- Research Organization:
- SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), High Energy Physics (HEP)
- Grant/Contract Number:
- AC02-76SF00515
- OSTI ID:
- 1923728
- Journal Information:
- The Astrophysical Journal, Vol. 942, Issue 2; ISSN 0004-637X
- Publisher:
- IOP PublishingCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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