8 citations · 8 across the 5 of their papers we have counts for
6 papers
Robustness of the \textit{smartpixels} classifier for different simulated sensor geometries and non-ideal detector conditions
Danush Shekar, Ben Weiss, Morris Swartz +40
Pixel tracking detectors at upcoming collider experiments will see unprecedented charged-particle densities. Real-time data reduction on the detector will enable higher granularity…
Smart Pixels: In-pixel AI for on-sensor data filtering
Benjamin Parpillon, Chinar Syal, Jieun Yoo +16
We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine…
Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e
Chenwei Xu, Jerry Yao-Chieh Hu, Aakaash Narayanan +21
We introduce a novel Proximal Policy Optimization (PPO) algorithm aimed at addressing the challenge of maintaining a uniform proton beam intensity delivery in the Muon to Electron…
Smartpixels: Towards on-sensor inference of charged particle track parameters and uncertainties
Jennet Dickinson, Rachel Kovach-Fuentes, Lindsey Gray +20
The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-g…
Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning
Jieun Yoo, Jennet Dickinson, Morris Swartz +19
Highly granular pixel detectors allow for increasingly precise measurements of charged particle tracks. Next-generation detectors require that pixel sizes will be further reduced,…
GNN-based end-to-end reconstruction in the CMS Phase 2 High-Granularity Calorimeter
Saptaparna Bhattacharya, Nadezda Chernyavskaya, Saranya Ghosh +11
We present the current stage of research progress towards a one-pass, completely Machine Learning (ML) based imaging calorimeter reconstruction. The model used is based on Graph Ne…