arXiv subjects

T. J. Hobbs

Publications and source records attributed to T. J. Hobbs.

At least 19 recordsLinked to original sources

arXiv2026

First-principle predictions of fragmentation functions via quantum computing

We report on an algorithm to compute fragmentation functions from the first principles Quantum Chromodynamics (QCD) Hamiltonian quantized in Light-Front Gauge, opening a path for digital quantum computers to calculate these longitudinal jet-structure observables. Simulating the behaviour of such computers on a classical cluster (which is memory-limited to about 30 qubits, given the expansive Hilbert spaces of actual quantum computers), we run a demonstration of a heavy-quark leading parton fragmenting into quarkonium, which we benchmark against NRQCD computations. Future quantum computers, perhaps concurrently running with HL-LHC, would have ample opportunity to extract arbitrary parton-hadron combinations.

hep-ph↗

arXiv2026

An AI-ready, Polarized Electron-Positron Collision Dataset

We present a modernized, AI-ready release of reconstructed data from the SLD experiment at the SLAC Linear Collider (SLC). The dataset comprises approximately 660{,}000 reconstructed events collected at $\sqrt{s}\approx 91.2$~GeV with a highly polarized electron beam from 1996--1998. The data have been translated from legacy formats into modern, widely-used file formats with the help of AI agents. The release also includes a corpus of newly digitized SLD internal documentation. We describe the contents of both components and provide physics validation demonstrations along with illustrations of their utility for physics and machine learning research in particle physics.

hep-ex↗

arXiv2026

Precision QCD with the Electron-Ion Collider

This document summarizes the discussions at the program "Precision QCD with the Electron Ion Collider", held from May to June 2025 at the Institute for Nuclear Theory (INT) at the University of Washington. The program was co-sponsored by the INT and by the Center for Frontiers in Nuclear Science (CFNS, Stony Brook University). Over its five-week duration it brought together about 70 theorists, experimentalists and computer scientists all interested in the physics program at the future Electron Ion Collider in preparation at Brookhaven National Laboratory. Key topics at the program were: higher-order perturbative-QCD calculations and techniques; nuclear structure and tomography; comparisons of phenomenological and lattice determinations of parton distribution functions; identification of signature observables for saturated gluons; assessment of the importance of AI techniques for EIC studies and detector development.

hep-ph↗

arXiv2025

CT25: Progress toward next-generation PDFs for precision phenomenology at the LHC

We summarize recent progress toward the next generation of CTEQ-TEA parton distribution functions, CT25, based on a global NNLO analysis that incorporates a significant sample of newly included LHC data. We present a baseline fit within the forthcoming full CT25 fit, which includes new Drell-Yan, top-pair, and inclusive-jet data at 8 and 13 TeV, and exhibits non-trivial pulls on the high-$x$ gluon and the flavor structure of the quark sea. In the context of progress toward CT25, we also summarize several recent and ongoing studies of the interplay between phenomenological PDFs and lattice-QCD calculations, simultaneous extractions of $α_s(M_Z)$ within the CT framework, and an expanded program of uncertainty quantification that treats parametrization dependence as an explicit source of epistemic uncertainty, among other issues. We also briefly highlight CT efforts to understand the effects of partial implementations of N$^3$LO corrections into PDF fits, which include benchmark calculations for Higgs and vector-boson processes. We comment on the implications of recent improvements to the CT analysis for precision phenomenology at the LHC and future facilities.

hep-ph↗

arXiv2025

Reusable theory representations for colliders: a demonstrator SMEFT foundation model

We develop a demonstrator foundation model for collider-scale explorations of the Standard Model Effective Field Theory (SMEFT), constructed from contrastive representations of theoretically simulated neutral-current Drell-Yan cross sections. Using a controlled sampling of the Warsaw-basis dimension-6 Wilson-coefficient space at $O(Λ^{-2})$, we generate a corpus of high-resolution differential distributions in $m_{\ell\ell}$ and $p_{T}$, augmented by physics-motivated Monte Carlo replicas with correlated uncertainties. A minimally parameterized encoder network is trained with a supervised contrastive loss to produce a low-dimensional latent manifold on which SMEFT-induced deformations of the Drell-Yan spectrum acquire a well-defined geometric structure. We analyze the resulting embedding and demonstrate that (i) latent directions correlate with characteristic SMEFT shape distortions, including energy-growing four-fermion contributions and electroweak vertex corrections; (ii) clusters in the embedding correspond to families of Wilson-coefficient configurations with similar phenomenological impact; and (iii) the learned representation supports downstream tasks such as classification with uncertainty quantification, anomaly detection, and nearest-neighbor retrieval. While restricted to leading-order SMEFT and simplified uncertainty modeling, this study provides the first step toward a reusable, physics-aligned foundational representation for the theory of New-Physics searches at high-energy colliders. We outline extensions towards a complete global analyses, including multi-process training corpora, higher-order corrections, and multi-objective pretraining.

hep-ph↗

arXiv2025

ArgoLOOM: agentic AI for fundamental physics from quarks to cosmos

Progress in modern physics has been supported by a steadily expanding corpus of numerical analyses and computational frameworks, which in turn form the basis for precision calculations and baseline predictions in experimental programs. These tools play a central role in navigating a complex landscape of theoretical models and current and potential observables to identify and understand fundamental interactions in physics. In addition, efforts to search for new fundamental interactions increasingly have a cross-disciplinary nature, such that understanding and leveraging interoperabilities among computational tools may be a significant enhancement. This work presents a new agentic AI framework, which we call ArgoLOOM, designed to bridge methodologies and computational analyses across cosmology, collider physics, and nuclear science. We describe the system contours, key internal aspects, and outline its potential for unifying scientific discovery pipelines. In the process, we demonstrate the use of ArgoLOOM on two small-scale problems to illustrate its conceptual foundations and potential for extensibility into a steadily growing agentic framework for fundamental physics.

hep-ph↗

arXiv2025

QED-enhanced PDF implications for the Higgs sector

In this work, we examine the implications of electroweak corrections beyond leading order for processes of special interest in the Higgs sector. We especially explore the role of these corrections given the introduction of an explicit parton distribution function (PDF) for the photon in the proton, an object which emerges necessarily in global PDF fits which include QED effects (i.e., QED-enhanced PDFs). We concentrate on several representative cases, including total Higgs-production cross sections through gluon fusion, $gg \to H$, vector-boson fusion (VBFH), and associated production, $pp \to VH$; we also examine differential distributions, taking a representative Higgs-strahlung process, $pp \to W^+H$. We find that the recently developed LUX formalism for the photon PDF significantly stabilizes the PDF dependence of both QED-PDF and electroweak corrections in the Higgs sector, while leaving overall $\sim\!3\!-\!4\%$ cross-section-level variations, depending on the chosen QED-enhanced PDF. We illustrate this QED-enhanced PDF dependence by exploring predictions based upon recent analyses of the CTEQ-TEA, MSHT, and NNPDF analysis groups, fitted either at NNLO or approximate N3LO in QCD.

hep-ph↗

arXiv2025

Fantômas Unconfined: global QCD fits with Bézier parameterizations

Fantômas is a C++ toolkit for exploring the parametrization dependence of parton distribution functions (PDFs) and other correlator functions in quantum chromodynamics (QCD). Fantômas facilitates the generation of adaptable polynomial parametrizations for PDFs, called metamorphs, to find best-fit PDF solutions and quantify the epistemic uncertainty associated with the parametrizations during their fitting. The method employs Bézier curves as universal approximators for a variety of PDF shapes. Integrated into the xFitter framework for the global QCD analysis, Fantômas provides a foundation for general models of PDFs, while reducing the computational time compared to the approaches utilizing traditional polynomial parametrizations as well as providing an interpretable alternative to neural-network-based models. This paper outlines the structure and practical usage of the Fantômas toolkit, including its inputs, outputs, and implementation within xFitter. It also provides a practical example of using Fantômas for uncertainty quantification as well as the combination of PDF fits into a single ensemble.

hep-ph↗

arXiv2025

Decoding the proton's gluonic density with lattice QCD-informed machine learning

We present a first machine learning-based decoding of the gluonic structure of the proton from lattice QCD using a variational autoencoder inverse mapper (VAIM). Harnessing the power of generative AI, we predict the parton distribution function (PDF) of the gluon given information on the reduced pseudo-Ioffe-time distributions (RpITDs) as calculated from an ensemble with lattice spacing $a\! \approx\! 0.09$ fm and a pion mass of $M_π\! \approx\! 310$ MeV. The resulting gluon PDF is consistent with phenomenological global fits within uncertainties, particularly in the intermediate-to-high-$x$ region where lattice data are most constraining. A subsequent correlation analysis confirms that the VAIM learns a meaningful latent representation, highlighting the potential of generative AI to bridge lattice QCD and phenomenological extractions within a unified analysis framework.

hep-ph↗

arXiv2025

MOSAIC: Magnonic Observations of Spin-dependent Axion-like InteraCtions

We introduce an array-scalable, magnon-based detector (MOSAIC) to search for the spin-dependent interactions of electron-coupled axion dark matter. These axions can excite single magnons in magnetic targets, such as the yttrium iron garnet (YIG) spheres used here, which are subsequently sensed by the detector. For MOSAIC, this sensing is implemented by coupling the magnons in the YIG spheres to magnetic-field-resilient single-electron charge-qubits, whose state is then interrogated with a quantum non-demolition measurement. Using standard superconducting fabrication techniques, MOSAIC can integrate many YIG sphere-qubit sensors, forming a large detector array. We outline the detector design and operation, and determine its sensitivity to axion dark matter. We find that a detector built with available technology will exceed the sensitivity of previous ferromagnetic haloscopes, and provides a platform where further improvements in performance would search for electron-coupled axion dark matter in unexplored parameter space.

hep-ph↗

arXiv2025

Quantum entropy as a harbinger of factorizability

Deeply inelastic scattering (DIS) is a powerful probe for investigating the QCD structure of hadronic matter and testing the standard model (SM). DIS can be described through QCD factorization theorems which separate contributions to the scattering interaction arising from disparate scales - e.g., with nonperturbative matrix elements associated with long distances and a perturbative hard scattering kernel applying to short-distance parton-level interactions. The fundamental underpinnings of factorization may be recast in the quantum-theoretic terms of entanglement, (de)coherence, and system localization in a fashion which sheds complementary light on the dynamics at work in DIS from QCD bound states. In this Letter, we propose and quantitatively test such a quantum-information theoretic approach for dissecting factorization in DIS and its domain of validity; we employ metrics associated with quantum entanglement such as a differential quantum entropy and associated KL divergences in numerical tests. We deploy these methods on an archetypal quark-spectator model of the proton, for which we monitor quantum decoherence in DIS as underlying model parameters are varied. On this basis, we demonstrate quantitatively how factorization-breaking effects may be imprinted on quantum entropies in a kinematic regime where leading-twist factorization increasingly receives large corrections from finite-$Q^2$ effects; our findings suggest potential applications of quantum simulation to QCD systems and their interactions.

hep-ph↗

arXiv2025

Event Generators for High-Energy Physics Experiments

We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments.

hep-ph↗

arXiv2024

Anomalous electroweak physics unraveled via evidential deep learning

The growth in beyond standard model (BSM) models and parametrizations has placed strong emphasis on systematically intercomparing within the range of possible models with controlled uncertainties. In this setting, the language of uncertainty quantification (UQ) provides quantitative metrics of assessing overlaps and discrepancies between models. We leverage recent machine learning (ML) developments in evidential deep learning (EDL) for UQ to separate data (aleatoric) and knowledge (epistemic) uncertainties in a model discrimination setting. In this study, we construct several potentially BSM-motivated scenarios for the anomalous electroweak interaction (AEWI) of neutrinos with nucleons in deep inelastic scattering ($ν$DIS). These scenarios are then quantitatively mapped, as a demonstration, alongside Monte Carlo replicas of the CT18 PDFs used to calculate the $Δχ^{2}$ statistic for a typical multi-GeV $ν$DIS experiment, CDHSW. Our framework effectively highlights areas of model agreement and provides a classification of out-of-distribution (OOD) samples. By offering the opportunity to identify unexplored regions of parameter space while understanding domains of model overlap, the approach presented in this work can help facilitate efficient BSM model exploration and exclusion for future New Physics searches.

hep-ph↗

arXiv2024

Quantum entropy and QCD factorization for low-$Q^2$ $ν$DIS

Deeply inelastic scattering (DIS) is an essential process for exploring the structure of visible matter and testing the standard model. At the same time, the theoretical interpretation of DIS measurements depends on QCD factorization theorems whose validity deteriorates at the lower values of $Q^2$ and $W^2$ typical of neutrino DIS in accelerator-based oscillation searches. For this reason, progress in understanding the origin and limits of QCD factorization is invaluable to the accuracy and precision of predictions for these upcoming neutrino experiments. In these short proceedings, we introduce a novel approach based on the quantum entropy associated with continuous distributions in QCD, using it to characterize the limits of factorization theorems relevant for the description of neutrino DIS. This work suggests an additional avenue for dissecting factorization-breaking dynamics through the quantum entropy, which could also play a role in quantum simulations of related systems.

hep-ph↗

arXiv2024

New results in the CTEQ-TEA global analysis of parton distributions in the nucleon

This report summarizes the latest developments in the CTEQ-TEA global analysis of parton distribution functions (PDFs) in the nucleon. The focus is on recent NNLO fits to high-precision LHC data at 8 and 13 TeV, including Drell-Yan, jet, and top-quark pair production, pursued on the way toward the release of the new generation of CTEQ-TEA general-purpose PDFs. The report also discusses advancements in statistical and numerical methods for PDF determination and uncertainty quantification, highlighting the importance of robust and replicable uncertainties for high-stakes observables. Additionally, it covers phenomenological studies related to PDF determination, such as the interplay of experimental constraints, exploration of correlations between high-$x$ nucleon sea and low-energy parity-violating measurements, fitted charm in the nucleon, the photon PDF in the neutron, and simultaneous SMEFT-PDF analyses.

hep-ph↗

arXiv2024

Confinement and Kink Entanglement Asymmetry on a Quantum Ising Chain

In this work, we explore the interplay of confinement, string breaking and entanglement asymmetry on a 1D quantum Ising chain. We consider the evolution of an initial domain wall and show that, surprisingly, while the introduction of confinement through a longitudinal field typically suppresses entanglement, it can also serve to increase it beyond a bound set for free particles. Our model can be tuned to conserve the number of domain walls, which gives an opportunity to explore entanglement asymmetry associated with link variables. We study two approaches to deal with the non-locality of the link variables, either directly or following a Kramers-Wannier transformation that maps bond variables (kinks) to site variables (spins). We develop a numerical procedure for computing the asymmetry using tensor network methods and use it to demonstrate the different types of entanglement and entanglement asymmetry.

quant-ph↗

arXiv2024

The upcoming CTEQ-TEA parton distributions in a nutshell

We review recent studies by the CTEQ-TEA group toward the development of a new generation of precision parton distribution functions in the nucleon for advanced studies at the high-luminosity LHC and in other experiments. Among several ongoing efforts, we examine sensitivity to the PDFs and mutual compatibility of new measurements in production of Drell-Yan pairs, top-quark pairs, and single-inclusive jets by the ATLAS, CMS, and LHCb collaborations in the LHC Runs 1 and 2.

hep-ph↗

arXiv2024

Explainable AI classification for parton density theory

Quantitatively connecting properties of parton distribution functions (PDFs, or parton densities) to the theoretical assumptions made within the QCD analyses which produce them has been a longstanding problem in HEP phenomenology. To confront this challenge, we introduce an ML-based explainability framework, $\texttt{XAI4PDF}$, to classify PDFs by parton flavor or underlying theoretical model using ResNet-like neural networks (NNs). By leveraging the differentiable nature of ResNet models, this approach deploys guided backpropagation to dissect relevant features of fitted PDFs, identifying x-dependent signatures of PDFs important to the ML model classifications. By applying our framework, we are able to sort PDFs according to the analysis which produced them while constructing quantitative, human-readable maps locating the x regions most affected by the internal theory assumptions going into each analysis. This technique expands the toolkit available to PDF analysis and adjacent particle phenomenology while pointing to promising generalizations.

hep-ph↗