A 10-qubit convolutional quantum graph neural network fed by autoencoder-compressed jet data achieves performance comparable to classical graph networks in distinguishing boosted Z jets from gluon jets.
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representative citing papers
Neutron activation resolves the 71Ge M-shell X-ray line at 158.7 eVee in a CONUS+ germanium detector, reducing CEvNS signal prediction uncertainty below 4%.
A modification to the Laplace transform of the quark propagator is introduced in a nonlocal model to align confining and deconfining regimes, allowing computation of meson screening masses over a wide temperature range and pole masses up to the transition.
AI4EOSC combines federated cloud scheduling, serverless inference, FAIR metadata, and provenance into one open platform for European research AI.
The Standard Model partial unification scale of non-Abelian gauge couplings at 2.8e16 GeV serves as the natural full unification scale M_X for new physics models where corrections to those couplings are equal or nearly equal.
Jarvis-HEP introduces a YAML-based Python framework for composing workflows and performing parameter scans in high-energy physics.
ACADA is the central software for CTAO that controls telescopes, manages multi-Gbps data, generates real-time science alerts, and enables sub-minute observation changes via its Transients Handler and Short-Term Scheduler.
A review of how quantum information science is expected to provide new tools and insights for nuclear and high-energy physics phenomenology and quantum simulations.
This paper overviews the LHCb Stripping framework's Python-based architecture, GitLab workflows, automation, and roadmap for processing both legacy and new high-energy physics data.
A pedagogical review of lattice QCD results on the thermodynamics of hot, dense, and magnetized QCD matter with an outlook on open questions.
citing papers explorer
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Quantum enhanced identification of boosted jets with quantum graph neural networks
A 10-qubit convolutional quantum graph neural network fed by autoencoder-compressed jet data achieves performance comparable to classical graph networks in distinguishing boosted Z jets from gluon jets.
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Sub-keV energy calibration of CONUS+ via 71Ge M-shell neutron activation
Neutron activation resolves the 71Ge M-shell X-ray line at 158.7 eVee in a CONUS+ germanium detector, reducing CEvNS signal prediction uncertainty below 4%.
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Mesonic modes in confining model at finite temperature
A modification to the Laplace transform of the quark propagator is introduced in a nonlocal model to align confining and deconfining regimes, allowing computation of meson screening masses over a wide temperature range and pole masses up to the transition.
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AI4EOSC: a Federated Cloud Platform for Artificial Intelligence in Scientific Research
AI4EOSC combines federated cloud scheduling, serverless inference, FAIR metadata, and provenance into one open platform for European research AI.
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The Standard Model partial unification scale as a guide to new physics model building
The Standard Model partial unification scale of non-Abelian gauge couplings at 2.8e16 GeV serves as the natural full unification scale M_X for new physics models where corrections to those couplings are equal or nearly equal.
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Jarvis-HEP: A lightweight Python framework for workflow composition and parameter scans in high-energy physics
Jarvis-HEP introduces a YAML-based Python framework for composing workflows and performing parameter scans in high-energy physics.
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The Array Control and Data Acquisition software of the Cherenkov Telescope Array Observatory
ACADA is the central software for CTAO that controls telescopes, manages multi-Gbps data, generates real-time science alerts, and enables sub-minute observation changes via its Transients Handler and Short-Term Scheduler.
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Quantum Complexity and New Directions in Nuclear Physics and High-Energy Physics Phenomenology
A review of how quantum information science is expected to provide new tools and insights for nuclear and high-energy physics phenomenology and quantum simulations.
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The LHCb Stripping Project: Sustainable Legacy Data Processing for High-Energy Physics
This paper overviews the LHCb Stripping framework's Python-based architecture, GitLab workflows, automation, and roadmap for processing both legacy and new high-energy physics data.
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Thermodynamics of magnetized matter in hot and dense QCD
A pedagogical review of lattice QCD results on the thermodynamics of hot, dense, and magnetized QCD matter with an outlook on open questions.
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