Entanglement and Bell nonlocality in τ+τ− at the LHC using machine learning for neutrino reconstruction

A bstract Experiments at the CERN Large Hadron Collider (LHC) have accumulated an unprecedented amount of data corresponding to a large variety of quantum states. Although searching for new particles beyond the Standard Model of particle physics remains a high priority for the LHC program, precision measurements of the physical processes predicted in the Standard Model continue to lead us to a deeper understanding of nature at high energies. We carry out detailed simulations for the process pp → τ + τ − X to perform quantum tomography and to measure the quantum entanglement and the Bell nonlocality of the τ + τ − two qubit state, including both statistical and systematic uncertainties. By using advanced machine learning techniques for neutrino momentum reconstruction, we achieve precise measurements of the full spin density matrix, a critical advantage over previous studies limited by reconstruction challenges for missing momenta. Our analysis reveals a clear observation of Bell nonlocality with high statistical significance, surpassing 5 σ , establishing τ + τ − as an ideal system for quantum information studies in high-energy collisions. Given its experimental feasibility and the high expected sensitivity for Bell nonlocality, we propose that τ + τ − should be regarded as the new benchmark system for quantum information studies at the LHC, complementing and extending the insights gained from the $$ t\overline{t} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>t</mml:mi> <mml:mover> <mml:mi>t</mml:mi> <mml:mo>¯</mml:mo> </mml:mover> </mml:math> system.

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Publication Details

Journal
Journal of High Energy Physics
Published
2026-04-23
DOI
https://doi.org/10.1007/jhep04(2026)190
Primary Topic
Particle physics theoretical and experimental studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Entanglement and Bell nonlocality in τ+τ− at the LHC using machine learning for neutrino reconstruction

Matthew Low, Tao Han, Tong Arthur Wu, B. Zhou et al.
Journal of High Energy Physics
Particle physics theoretical and experimental studies
article

Entanglement and Bell nonlocality in τ+τ− at the LHC using machine learning for neutrino reconstruction

Matthew Low, Tao Han, Tong Arthur Wu, B. Zhou, Shu Li, S.‐C. Hsu, Yulei Zhang, Qi-Bin Liu
article en

Abstract

A bstract Experiments at the CERN Large Hadron Collider (LHC) have accumulated an unprecedented amount of data corresponding to a large variety of quantum states. Although searching for new particles beyond the Standard Model of particle physics remains a high priority for the LHC program, precision measurements of the physical processes predicted in the Standard Model continue to lead us to a deeper understanding of nature at high energies. We carry out detailed simulations for the process pp → τ + τ − X to perform quantum tomography and to measure the quantum entanglement and the Bell nonlocality of the τ + τ − two qubit state, including both statistical and systematic uncertainties. By using advanced machine learning techniques for neutrino momentum reconstruction, we achieve precise measurements of the full spin density matrix, a critical advantage over previous studies limited by reconstruction challenges for missing momenta. Our analysis reveals a clear observation of Bell nonlocality with high statistical significance, surpassing 5 σ , establishing τ + τ − as an ideal system for quantum information studies in high-energy collisions. Given its experimental feasibility and the high expected sensitivity for Bell nonlocality, we propose that τ + τ − should be regarded as the new benchmark system for quantum information studies at the LHC, complementing and extending the insights gained from the $$ t\overline{t} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>t</mml:mi> <mml:mover> <mml:mi>t</mml:mi> <mml:mo>¯</mml:mo> </mml:mover> </mml:math> system.

Journal of High Energy PhysicsVol. 2026(4)
University of Pittsburgh (US), Shanghai Jiao Tong University (CN), University of Washington (US), Kavli Institute for Particle Astrophysics and Cosmology (US)
National Science Foundation, U.S. Department of Energy, University of Pittsburgh, National Natural Science Foundation of China, Shanghai Jiao Tong University
Openalex Percentile: Top 98%
Particle physics theoretical and experimental studies
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