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Collective neutrino oscillations with tensor networks using a time-dependent variational principle
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If a system of flavor-oscillating neutrinos is at high enough densities that neutrino-neutrino coherent forward scatterings are non-negligible, the system becomes a time-dependent many-body problem. An important and open question is whether the flavor evolution is sufficiently described by a mean-field approach or can be strongly affected by correlations arising from two-body interactions in the neutrino Hamiltonian, as measured by nontrivial quantum entanglement. Numerical computations of the time evolution of many-body quantum systems are challenging because the size of the Hilbert space scales exponentially with the number of particles N in the system. Thus, it is important to investigate approximate but beyond-mean-field numerical treatments at larger values of N. Here we investigate the efficacy of tensor network methods to calculate the time evolution of interacting neutrinos at larger values of N than are possible with conventional methods. In particular, we introduce the use of time-dependent variational principle methods to address the long-range (in momentum space) interactions of the neutrino Hamiltonian when including many distinct vacuum oscillation frequencies. We also define new error measures based upon the instantaneously conserved charge operators known for this Hamiltonian to determine validity of large-N tensor network calculations.
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Improved Approximations for Collective Neutrino Oscillations
Second-order BBGKY truncation of an su(n) one-plus-two-body Hamiltonian approximates collective neutrino dynamics beyond mean field at polynomial classical cost and reveals large-N phase and entanglement structure.
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