activity
20132026
most citedSearch for supersymmetry in hadronic final states with missing transverse energy using the variables AlphaT and b-quark multiplicity in pp collisions at 8 TeV

177 citations · 1.3k across the 60 of their papers we have counts for

collaborators

61 papers

hep-ph2026

HEPTABench: A framework for portable and controlled agentic evaluations in high energy physics

Tony Menzo, Alexander Roman, George T. Fleming +3

Quantifying the capability and reliability of agentic systems in high-energy physics (HEP) requires repeated evaluations under controlled configurations. Establishing whether chang…

astro-ph.IM2026

Denoising Interferometric Observations Using Visibility-Informed Neural Networks

Jason P. Terry, Cassandra Hall, Sergei Gleyzer

The upcoming observations from the Square Kilometer Array Observatory will provide the astronomical community with a wealth of observations of important objects at long wavelengths…

hep-ph2026

Agentic Diagrammatica: Towards Autonomous Symbolic Computation in High Energy Physics

Tony Menzo, Alexander Roman, George T. Fleming +3

We present Diagrammatica, a symbolic computation extension to the HEPTAPOD agentic framework, which enables LLM agents to plan and execute multi-step theoretical calculations. Symb…

quant-ph2026

The Pareto Frontiers of Magic and Entanglement: The Case of Two Qubits

Alexander Roman, Marco Knipfer, Jogi Suda Neto +3

Magic and entanglement are two measures that are widely used to characterize quantum resources. We study the interplay between magic and entanglement in two-qubit systems, focusing…

physics.data-an2026

GNN For Muon Particle Momentum estimation

Vishak K Bhat, Eric A. F. Reinhardt, Sergei Gleyzer

Due to a high rate of overall data generation relative to data generation of interest, the CMS experiment at the Large Hadron Collider uses a combination of hardware- and software-…

hep-ex2026

Continual Learning via Ensemble-Based Depth-Wise Masked Autoencoders for Data Quality Monitoring in High-Energy Physics

Dale Julson, Eric Reinhardt, Andrii Krutsylo +5

Machine learning (ML) techniques have been demonstrated to improve the accuracy and efficiency of anomaly detection (AD) when compared to conventional methods. This has led to the…