5 papers
The Darkside-20k Data Acquisition System
Fabio Acerbi, Pushparaj Adhikari, Paolo Agnes +289
DarkSide-20k is a WIMP search experiment using liquid argon as a target, designed to perform a background-free search for dark matter with unprecedented sensitivity, and is current…
Quality control of PEN wavelength shifters for DarkSide-20k veto
Sarthak Choudhary
Efficient Wavelength Shifters (WLS) are crucial for Liquid Argon (LAr) dark matter detectors. As they grow larger in volume, the scalability of WLS becomes an important concern. Te…
Attacking Byzantine Robust Aggregation in High Dimensions
Sarthak Choudhary, Aashish Kolluri, Prateek Saxena
Training modern neural networks or models typically requires averaging over a sample of high-dimensional vectors. Poisoning attacks can skew or bias the average vectors used to tra…
Scalable Neural Network Training over Distributed Graphs
Aashish Kolluri, Sarthak Choudhary, Bryan Hooi +1
Graph neural networks (GNNs) fuel diverse machine learning tasks involving graph-structured data, ranging from predicting protein structures to serving personalized recommendations…
The optical simulation model of the DarkSide-20k Veto detector
Cenk Türkoğlu, Sarthak Choudhary
DarkSide-20k is a rare-event search experiment aimed at finding signals of dark matter particles. It is a dual-phase detector that registers ionisation and scintillation signals or…