A new variational Monte Carlo framework using neural-network wave functions and the Lorentz integral transform accurately reproduces deuteron and helium-4 photon absorption cross sections.
Relativistic effects in Green's function Monte Carlo calculations of neutrino-nucleus scattering
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abstract
Microscopic calculations of neutrino-nucleus scattering cross sections are critical for the success of the neutrino-oscillation program. In addition to retaining nuclear correlations in the initial and final state of the reaction, they are based on consistent nuclear interactions and transition current operators, thereby enabling robust uncertainty quantification. In this work, we address a significant limitation of these microscopic methods, which arises from their nonrelativistic nature. By performing the calculations in a reference frame that minimizes nucleon momenta and utilizing the so-called ``two-fragment'' model, we extend the applicability of Green's function Monte Carlo calculations of neutrino-nucleus scattering to higher momenta than currently possible. To validate this approach, we compare our theoretical predictions against inclusive data measured by the MiniBooNE, T2K, and MINER$\nu$A experiments.
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Nuclear responses with neural-network quantum states
A new variational Monte Carlo framework using neural-network wave functions and the Lorentz integral transform accurately reproduces deuteron and helium-4 photon absorption cross sections.