28 citations · 28 across the 6 of their papers we have counts for
6 papers
Contrastive Learning for Interpretable Anomaly Detection at Collider Experiments
Haoyi Jia, Sagar Addepalli, Julia Gonski
Generic event-level anomaly detection for collider physics has two recurring problems: anomaly scores are hard to interpret, and they correlate strongly with energy scale and objec…
Classical Hardware Acceleration of Quantum Autoencoders for Real-Time Anomaly Detection in Collider Experiments
Ivan Ge, Sagar Addepalli, Abhilasha Dave +1
Quantum machine learning (QML) algorithms in high energy physics (HEP) can efficiently represent and leverage long-range, high-order correlations in high-dimensional collider data,…
Hardware-Aware Tensor Networks for Real-Time Quantum-Inspired Anomaly Detection at Particle Colliders
Sagar Addepalli, Prajita Bhattarai, Abhilasha Dave +1
Quantum machine learning offers the ability to capture complex correlations in high-dimensional feature spaces, crucial for the challenge of detecting beyond the Standard Model phy…
Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)
Julia Gonski, Jennifer Ott, Jenni Ott +129
The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environmen…
Early Career Researcher Input to the European Strategy for Particle Physics Update: White Paper
Jan-Hendrik Arling, Alexander Burgman, Christina Dimitriadi +42
This document, written by early career researchers (ECRs) in particle physics, aims to represent the perspectives of the European ECR community and serves as input for the 2025--20…
The ABC130 barrel module prototyping programme for the ATLAS strip tracker
Luise Poley, Craig Sawyer, Sagar Addepalli +246
For the Phase-II Upgrade of the ATLAS Detector, its Inner Detector, consisting of silicon pixel, silicon strip and transition radiation sub-detectors, will be replaced with an all…