944 citations · 7.6k across the 135 of their papers we have counts for
137 papers
Reining in an Agentic Harness for High Energy Physics
Tony Menzo, George T. Fleming, Konstantin T. Matchev +2
Agentic systems now address tasks across theoretical, phenomenological, and experimental high energy physics (HEP), but their scientific capabilities remain difficult to reuse acro…
Efficient Hamiltonian Truncation: Fast Matrix Construction and Quantum Krylov Diagonalization
Rachel Houtz, Marco Knipfer, Konstantin Matchev +2
Hamiltonian truncation offers a nonperturbative route to quantum field theory, yet its accuracy is limited by the rapid expansion of the truncated Hilbert space, which drives up co…
Analytical Landscape of Maximal Magic for Two-Qutrit States and Beyond
Marco Knipfer, Alexander Roman, Katia Matcheva +1
Achieving a genuine quantum advantage relies on two distinct non-classical resources that restrict efficient classical simulation: entanglement and magic (nonstabilizerness). We in…
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…
ASTER -- Agentic Science Toolkit for Exoplanet Research
Emilie Panek, Alexander Roman, Gaurav Shukla +3
The expansion of exoplanet observations has created a need for flexible, accessible, and user-friendly workflows. Transmission spectroscopy has become a key technique for probing a…
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…
AI Agents for Variational Quantum Circuit Design
Marco Knipfer, Alexander Roman, Konstantin T. Matchev +2
Variational quantum circuits (VQCs) constitute a central building block of near-term quantum machine learning (QML), yet the principled design of expressive and trainable architect…
Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision
Thea Klaeboe Aarrestad, Alaa Abdelhamid, Haider Abidi +457
Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape co…
Hunting for "Oddballs" with Machine Learning: Detecting Anomalous Exoplanets Using a Deep-Learned Low-Dimensional Representation of Transit Spectra with Autoencoders
Alexander Roman, Emilie Panek, Roy T. Forestano +3
This study explores the application of autoencoder-based machine learning techniques for anomaly detection to identify exoplanet atmospheres with unconventional chemical signatures…
Balancing Variety and Sample Size: Optimal Parameter Sampling for Ariel Target Selection
Emilie Panek, Alexander Roman, Katia Matcheva +2
Targeted astrophysical surveys are limited by the amount of telescope time available, which makes it impossible to observe every single object of interest. In order to maximize the…
HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency
Tony Menzo, Alexander Roman, Sergei Gleyzer +5
Many theoretical and experimental workflows in high-energy-physics (HEP) stand to benefit from recent advances in transformer-based large language models (LLMs). While early applic…
Supervised Machine Learning Methods with Uncertainty Quantification for Exoplanet Atmospheric Retrievals from Transmission Spectroscopy
Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva +1
Standard Bayesian retrievals for exoplanet atmospheric parameters from transmission spectroscopy, while well understood and widely used, are generally computationally expensive. In…
The Electroweak Sphaleron Revisited: II. Study of Decay Dynamics
Konstantin T. Matchev, Sarunas Verner
We present a comprehensive analysis of electroweak sphaleron decay dynamics, employing both analytical techniques and high-resolution numerical simulations. Using a spherically sym…
The Electroweak Sphaleron Revisited: I. Static Solutions, Energy Barrier, and Unstable Modes
Konstantin T. Matchev, Sarunas Verner
The electroweak sphaleron is a static, unstable solution of the Standard Model classical field equations, representing the energy barrier between topologically distinct vacua. In t…
United States Muon Collider Community White Paper for the European Strategy for Particle Physics Update
A. Abdelhamid, D. Acosta, P. Affleck +301
This document is being submitted to the 2024-2026 European Strategy for Particle Physics Update (ESPPU) process on behalf of the US Muon Collider community, with its preparation co…
Quantum generative adversarial networks for gluon initiated jets generation
Rey Guadarrama, Sergei Gleyzer, Mariia Baidachna +6
Quantum computing has the potential to offer significant advantages over classical computing, making it a promising avenue for exploring alternative methods in High Energy Physics…
The Linear Collider Facility (LCF) at CERN
H. Abramowicz, E. Adli, F. Alharthi +406
In this paper we outline a proposal for a Linear Collider Facility as the next flagship project for CERN. It offers the opportunity for a timely, cost-effective and staged construc…
A Linear Collider Vision for the Future of Particle Physics
H. Abramowicz, E. Adli, F. Alharthi +446
In this paper we review the physics opportunities at linear colliders with a special focus on high centre-of-mass energies and beam polarisation, take a fresh look at the…
Quantum Diffusion Model for Quark and Gluon Jet Generation
Mariia Baidachna, Rey Guadarrama, Gopal Ramesh Dahale +6
Diffusion models have demonstrated remarkable success in image generation, but they are computationally intensive and time-consuming to train. In this paper, we introduce a novel d…
Lie-Equivariant Quantum Graph Neural Networks
Jogi Suda Neto, Roy T. Forestano, Sergei Gleyzer +3
Discovering new phenomena at the Large Hadron Collider (LHC) involves the identification of rare signals over conventional backgrounds. Thus binary classification tasks are ubiquit…
Quantum Attention for Vision Transformers in High Energy Physics
Alessandro Tesi, Gopal Ramesh Dahale, Sergei Gleyzer +4
We present a novel hybrid quantum-classical vision transformer architecture incorporating quantum orthogonal neural networks (QONNs) to enhance performance and computational effici…
Quantum Vision Transformers for Quark-Gluon Classification
Marçal Comajoan Cara, Gopal Ramesh Dahale, Zhongtian Dong +8
We introduce a hybrid quantum-classical vision transformer architecture, notable for its integration of variational quantum circuits within both the attention mechanism and the mul…
Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics
Eyup B. Unlu, Marçal Comajoan Cara, Gopal Ramesh Dahale +8
Models based on vision transformer architectures are considered state-of-the-art when it comes to image classification tasks. However, they require extensive computational resource…
is all you need: production of multiple semi-invisible resonances at hadron colliders
Zhongtian Dong, Kyoungchul Kong, Konstantin T. Matchev +1
The stransverse mass variable was originally proposed for the study of hadron collider events in which parent particles are produced and then decay semi-invisibly. H…