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 $$ t\overline{t} $$ t t ¯ system.