Generative diffusion and flow models are constructed to remain exactly on the Lorentz-invariant massless N-particle phase space manifold during sampling for particle physics applications.
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Simulations of pp to tau+ tau- at the LHC with ML neutrino reconstruction show Bell nonlocality above 5 sigma, proposing tau pairs as a new benchmark system for quantum information studies.
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Generative models on phase space
Generative diffusion and flow models are constructed to remain exactly on the Lorentz-invariant massless N-particle phase space manifold during sampling for particle physics applications.
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Entanglement and Bell Nonlocality in $\tau^+ \tau^-$ at the LHC using Machine Learning for Neutrino Reconstruction
Simulations of pp to tau+ tau- at the LHC with ML neutrino reconstruction show Bell nonlocality above 5 sigma, proposing tau pairs as a new benchmark system for quantum information studies.