High Energy & Particle · Physics & Astronomy
High Energy Physics - Phenomenology
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139 papers, from 8 September 2026 to 5 November 2026: 139 arXiv preprints.
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Newest papers, page 7
Machine learning for the LHC physics program: a 2025-2026 stocktake
The first sentence of this abstract--and the introduction to these proceedings--was authored by a human, but the bulk of this document was generated by an agentic AI system.Prompting Particle Physics: Tokenized Multi-modal Foundation Models for Combinatorially Many Tasks
Reconstruction and simulation at a collider experiment are long chains of specialised algorithms, each tuned to a single step.Mass-Dependent Dark Matter Deficit from Inelastic Scattering
Recent stellar-kinematic and neutral-hydrogen observations indicate a dark matter deficit within the central tens of kiloparsecs of nearby galaxies that grows systematically with stellar mass…The refractive index of the medium within the volume of deep inelastic $ep$ scattering: I. Group velocity of interaction carriers
We propose a new method for measuring several characteristics of a fermion-boson medium formed during deep inelastic particle scattering.CP asymmetry and visible decay in $3+1$ neutrino oscillations on a quantum computer
We use quantum simulation to study how visible neutrino decay modifies the vacuum CP asymmetry in muon-to-electron oscillations within a $3+1$ neutrino scenario.Response of Hellinger-distance based coherence to weak decoherence in two-flavor neutrino oscillations
We evaluate the Hellinger-distance coherence of the two-flavor neutrino state subject to Lindblad damping of the mass-eigenstate interference term, and obtain a closed expression in terms of the…Fundamental Physics at the Frontier of Noisy Quantum Computation
Quantum computing offers a new, orthogonal direction for investigating fundamental physics, extending beyond classical numerical methods and conventional observables.The universe as a superconductor: How to search for a photon mass
We revisit the bounds on the photon mass when it arises from an Abelian Higgs mechanism rather than a Proca term.Axions and the RR Lyrae Period-Luminosity Relation
We investigate the impact of axions on the period-luminosity relation (PLR) of RR Lyrae stars.Quantum Computing Solution of the Bethe-Salpeter Equation for Relativistic Scalar Bound States via Tensor-Network VQE
We present a gate-based quantum computing solution of the homogeneous Bethe-Salpeter equation (hBSE) for the bound state of two massive relativistic scalar particles interacting via…Measuring correlations using local and nonlocal quenches
We present a theoretical proposal for measuring correlation functions in a quantum field system based on the use of quantum quenches.Nonlocal advantage of quantum coherence in tau-lepton pairs from electron--positron collisions
Quantum correlations have recently attracted significant attention in collider physics, with Nonlocal Advantage of Quantum Coherence (NAQC) representing the strongest form of quantum correlation…LLM-Based FORM Code Generation with Verification-Driven Fine-Tuning
FORM is a domain-specific symbolic manipulation language widely used in particle physics for processing the very large algebraic expressions arising from multi-loop Feynman diagram calculations.The shape of quark flavors
We construct the Yukawa couplings of the quark sector as overlap integrals of Gaussian wave functions in extra spatial dimensions.Machine Learning for Invisible Dark Boson Searches at the Electron-Ion Collider
We investigate whether adding $t$, the positive magnitude of the squared nuclear four-momentum transfer, enables boosted decision trees (BDTs) to improve invisible-dark-boson selection relative to…Comprehensive reconstruction of collider events with hypergraph representation learning and graph-conditioned diffusion
In particle collider experiments, event reconstruction is the task of inferring the kinematics of short-lived particles produced in the hard scatter from the stable final states recorded by detectors.Learning the Geometry of Collider Events with Metric-Aware Deep Sets
Optimal transport gives structured data a geometry, but exact evaluation is costly in large pairwise analyses that exploit relationships among distances.Searching for New Physics with Reinforcement Learning
Finding new physics (NP) is the most important problem in particle physics today.Inclusive electron-nucleus cross section models from domain adaptation
We apply transfer learning (TL) to construct data-driven models of inclusive electron-nucleus cross sections.