21 citations · 43 across the 14 of their papers we have counts for
7 papers · 1 filter
Real-Time SiPM Pulse Deconvolution for a High-granularity Dual-readout Calorimeter with Neutral Networks
Spencer Allen, Matteo Cremonesi, Jordan Damgov +6
The High-Granularity Dual-Readout Calorimeter (HG-DREAM) designed for FCC-ee aims to achieve unprecedented energy resolution through fine three-dimensional shower imaging, simultan…
On-chip probabilistic inference for charged-particle tracking at the sensor edge
Arghya Ranjan Das, David Jiang, Rachel Kovach-Fuentes +31
Modern scientific instruments operate under increasingly extreme constraints on bandwidth, latency, and power. Inference at the sensor edge determines experimental data collection…
Characterization of a 28 nm ASIC With On-Chip ML for Particle Tracking Detectors
Benjamin Parpillon, Anthony Badea, Danush Shekar +35
We present a 28 nm CMOS pixel readout integrated circuit implementing in-pixel analog signal processing and on-chip machine learning data filtering for particle tracking detectors.…
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…
Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter
M. Aamir, G. Adamov, T. Adams +568
A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transv…
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,…