activity
20232026
collaborators

10 papers

hep-ex2026

On-Detector Machine Learning for Beam-Induced Background Rejection at a 10 TeV Muon Collider

Daniel Abadjiev, Eliza Howard, Tsz Ngong You +35

A 10 TeV Muon Collider is a compelling candidate for a future energy-frontier facility, offering unprecedented opportunities to explore the fundamental laws of particle physics. Mu…

physics.ins-det2026

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…

physics.ins-det2026

Towards a Self-Driving Trigger at the LHC: Adaptive Response in Real Time

Shaghayegh Emami, Cecilia Tosciri, Giovanna Salvi +7

Real-time data filtering and selection -- or trigger -- systems at high-throughput scientific facilities such as the experiments at the Large Hadron Collider (LHC) must process ext…

physics.ins-det2025

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…

physics.ins-det2025

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.…

physics.ins-det2024

Intelligent Pixel Detectors: Towards a Radiation Hard ASIC with On-Chip Machine Learning in 28 nm CMOS

Anthony Badea, Alice Bean, Doug Berry +16

Detectors at future high energy colliders will face enormous technical challenges. Disentangling the unprecedented numbers of particles expected in each event will require highly g…

physics.ins-det2024

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…

hep-ex2024

ACE Science Workshop Report

Stefania Gori, Nhan Tran, Karri DiPetrillo +20

We summarize the Fermilab Accelerator Complex Evolution (ACE) Science Workshop, held on June 14-15, 2023. The workshop presented the strategy for the ACE program in two phases: ACE…

hep-ex2023

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…

physics.ins-det2023

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,…