CRYO: a System-On-Chip ASIC for Noble Liquid TPC Experiments

Pena-Perez, Aldo; Doering, D.; Gupta, Aseem; Tamma, C.; Marković, Bojan; Ali, Hussein; Caragiulo, P.; Rota, Lorenzo; Kamath, Umanath; Petrignani, Savino; Xu, Xiaobin; Abu-Nimeh, Faisal T.; Breur, P. A.; Tsang, Patrick; Convery, M. R.; Dragone, Angelo

doi:10.1109/nss/mic42677.2020.9507812

Cited by 4 publications

(2 citation statements)

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“…This in turn allows a high-granularity readout, which directly leads to good angular resolution, while the minimal interior dead material maximizes event reconstruction efficiency. In our case, the readout, which builds on recent advances in cryogenic complementary metal-oxide semiconductor (CMOS) charge readout (Dwyer et al 2018;Adams et al 2020;Pena-Perez et al 2020), uses a triggered, ultra−low-power submillimeter pixel readout to provide submillimeter 3D sampling of the tracks. The trigger for pixel readout is provided by a separate set of "coarse grid" wire electrodes with a nominal ∼1 cm pitch.…”

Section: The Gammatpc Instrument Concept and Compton Event Reconstruc...mentioning

confidence: 99%

Low-energy Electron-track Imaging for a Liquid Argon Time-projection-chamber Telescope Concept Using Probabilistic Deep Learning

Buuck

Mishra

Charles

et al. 2023

ApJ

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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.

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Section: The Gammatpc Instrument Concept and Compton Event Reconstruc...mentioning

confidence: 99%

Low-energy Electron-track Imaging for a Liquid Argon Time-projection-chamber Telescope Concept Using Probabilistic Deep Learning

Buuck

Mishra

Charles

et al. 2023

ApJ

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“…The ultimate goal is to accurately image the mm-scale recoiling electron tracks to determine both their head (the location of the interaction) and their initial direction. Recent development of cold complementary metal-oxide-semiconductor (CMOS) readout electronics for DUNE [518][519][520] lay a foundation for this. However two problems must be overcome: the power resulting from high channel count, and loss of charge due to diffusion spreading the signal over many sub-threshold sensors.…”

Section: Thomas Shuttmentioning

confidence: 99%

The Future of Gamma-Ray Experiments in the MeV-EeV Range

Engel¹,

Goodman²,

Huentemeyer³

et al. 2022

Preprint

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Naturally occurring particle accelerators shine brightly throughout the universe, inviting us to discover fundamental laws and hone our theories if we look in their directions with the right detectors. Gamma-rays, the most energetic photons, carry information from the far reaches of extragalactic space with minimal interaction or loss of information. They bring messages about particle acceleration in environments so extreme they cannot be reproduced on earth for a closer look. Gamma-ray astrophysics is so complementary with collider work that particle physicists and astroparticle physicists are often one in the same.Gamma-ray instruments, especially the Fermi Gamma-ray Space Telescope, have been pivotal in major multi-messenger discoveries over the past decade. There is presently a great deal of interest and scientific expertise available to push forward new technologies, to plan and build space-and ground-based gamma-ray facilities, and to build multimessenger networks with gamma rays at their core. It is therefore concerning that before the community comes together for planning exercises again, much of that infrastructure could be lost to a lack of long-term planning for support of gamma-ray astrophysics. Gamma-rays with energies from the MeV to the EeV band are therefore central to multiwavelength and multi-messenger studies to everything from astroparticle physics with compact objects, to dark matter studies with diffuse large scale structure.These science goals and the excitement of new discoveries have generated a wave of new gamma-ray facility proposals and programs. Since the legacy of existing facilities is well covered in many other places, this paper highlights new and proposed gamma-ray technologies and facilities that have each been designed to address specific needs in the measurement of extreme astrophysical sources that probe some of the most pressing questions in fundamental physics for the next decade. The proposed instrumentation would also address the priorities laid out in the recent Decadal Survey of Astronomy and Astrophysics (Astro2020), a complementary study by the astrophysics community that provides opportunities also relevant to Snowmass.

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