activity
20182026
most citedInvestigating the Topology Dependence of Quark and Gluon Jets

25 citations · 63 across the 10 of their papers we have counts for

collaborators

10 papers

cs.LG2026

Sven: Singular Value Descent as a Computationally Efficient Natural Gradient Method

Samuel Bright-Thonney, Thomas R. Harvey, Andre Lukas +1

We introduce Sven (Singular Value dEsceNt), a new optimization algorithm for neural networks that exploits the natural decomposition of loss functions into a sum over individual da…

hep-ex2026

AI Agents Can Already Autonomously Perform Experimental High Energy Physics

Eric A. Moreno, Samuel Bright-Thonney, Andrzej Novak +2

Large language model-based AI agents are now able to autonomously execute substantial portions of a high energy physics (HEP) analysis pipeline with minimal expert-curated input. G…

cs.LG2025

Sparse, self-organizing ensembles of local kernels detect rare statistical anomalies

Gaia Grosso, Sai Sumedh R. Hindupur, Thomas Fel +3

Modern artificial intelligence has revolutionized how we extract representations from scientific data, yet the statistical properties of these representations remain poorly control…

cs.LG2025

AutoSciDACT: Automated Scientific Discovery through Contrastive Embedding and Hypothesis Testing

Samuel Bright-Thonney, Christina Reissel, Gaia Grosso +6

Novelty detection in large scientific datasets faces two key challenges: the noisy and high-dimensional nature of experimental data, and the necessity of making statistically robus…

hep-ph2023★ 6 cited

Safe but Incalculable: Energy-weighting is not all you need

Samuel Bright-Thonney, Benjamin Nachman, Jesse Thaler

Infrared and collinear (IRC) safety has long been used a proxy for robustness when developing new jet substructure observables. This guiding philosophy has been carried into the de…

hep-ph2023★ 3 cited

Chained Quantile Morphing with Normalizing Flows

Samuel Bright-Thonney, Philip Harris, Patrick McCormack +1

Accounting for inaccuracies in Monte Carlo simulations is a crucial step in any high energy physics analysis. It becomes especially important when training machine learning models,…

hep-ph2022★ 20 cited

Report of the Topical Group on Higgs Physics for Snowmass 2021: The Case for Precision Higgs Physics

Sally Dawson, Patrick Meade, Isobel Ojalvo +78

A future Higgs Factory will provide improved precision on measurements of Higgs couplings beyond those obtained by the LHC, and will enable a broad range of investigations across t…

hep-ph2022★ 9 cited

Systematic Quark/Gluon Identification with Ratios of Likelihoods

Samuel Bright-Thonney, Ian Moult, Benjamin Nachman +1

Discriminating between quark- and gluon-initiated jets has long been a central focus of jet substructure, leading to the introduction of numerous observables and calculations to hi…

hep-ex2022

Strange quark as a probe for new physics in the Higgs sector

Alexander Albert, Matthew J. Basso, Samuel K. Bright-Thonney +25

This paper describes a novel algorithm for tagging jets originating from the hadronisation of strange quarks (strange-tagging) with the future International Large Detector (ILD) at…

hep-ph2018★ 25 cited

Investigating the Topology Dependence of Quark and Gluon Jets

Samuel Bright-Thonney, Benjamin Nachman

As most target final states for searches and measurements at the Large Hadron Collider have a particular quark/gluon composition, tools for distinguishing quark- from gluon-initiat…