250 citations · 968 across the 23 of their papers we have counts for
23 papers · 1 filter
Report of the Topical Group on Physics Beyond the Standard Model at Energy Frontier for Snowmass 2021
Tulika Bose, Antonio Boveia, Caterina Doglioni +318
This is the Snowmass2021 Energy Frontier (EF) Beyond the Standard Model (BSM) report. It combines the EF topical group reports of EF08 (Model-specific explorations), EF09 (More gen…
Machine-Learning Compression for Particle Physics Discoveries
Jack H. Collins, Yifeng Huang, Simon Knapen +2
In collider-based particle and nuclear physics experiments, data are produced at such extreme rates that only a subset can be recorded for later analysis. Typically, algorithms sel…
Snowmass2021 White Paper: Collider Physics Opportunities of Extended Warped Extra-Dimensional Models
Kaustubh Agashe, Jack H. Collins, Peizhi Du +5
While the warped extra-dimensional models provide an attractive solution to both the gauge and the flavor hierarchy problems, the mass scale of new particles predicted by the minim…
An Exploration of Learnt Representations of W Jets
Jack H. Collins
I present a Variational Autoencoder (VAE) trained on collider physics data (specifically boosted jets), with reconstruction error given by an approximation to the Earth Movers…
Comparing Weak- and Unsupervised Methods for Resonant Anomaly Detection
Jack H. Collins, Pablo Martín-Ramiro, Benjamin Nachman +1
Anomaly detection techniques are growing in importance at the Large Hadron Collider (LHC), motivated by the increasing need to search for new physics in a model-agnostic way. In th…
The LHC Olympics 2020: A Community Challenge for Anomaly Detection in High Energy Physics
Gregor Kasieczka, Benjamin Nachman, David Shih +44
A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. I…