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The Green's function Monte Carlo (GFMC) method provides accurate solutions to the nuclear many-body problem and predicts properties of light nuclei starting from realistic two- and three-body interactions. Controlling the GFMC fermion-sign problem is crucial, as the signal-to-noise ratio decreases exponentially with Euclidean time, requiring significant computing resources. Inspired by similar scenarios in lattice quantum field theory and spin systems, in this work, we employ integration contour deformations to improve the GFMC signal-to-noise ratio. Machine learning techniques are used to select optimal contours with minimal variance from parameterized families of deformations. As a proof of principle, we consider the deuteron binding energies and Euclidean density response functions. We only observe mild signal-to-noise improvement for the binding energy case. On the other hand, we achieve an order of magnitude reduction of the variance for Euclidean density response functions, paving the way for computing electron- and neutrino-nucleus cross-sections of larger nuclei., 21 pages, 10 figures

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., Comment: 12 pages, 7 figures

To achieve its design goals, the next generation of neutrino-oscillation accelerator experiments requires percent-level predictions of neutrino-nucleus cross sections supplemented by robust estimates of the theoretical uncertainties involved. The latter arise from both approximations in solving the nuclear many-body problem and in the determination of the single- and few-nucleon quantities taken as input by many-body methods. To quantify both types of uncertainty, we compute flux-averaged double-differential cross sections using the Green's function Monte Carlo and spectral function methods as well as different parameterizations of the nucleon axial form factors based on either deuterium bubble-chamber data or lattice quantum chromodynamics calculations. The cross-section results are compared with available experimental data from the MiniBooNE and T2K collaborations. We also discuss the uncertainties associated with $N\rightarrow \Delta$ transition form factors that enter the two-body current operator. We quantify the relations between neutrino-nucleus cross section and nucleon form factor uncertainties. These relations enable us to determine the form factor precision targets required to achieve a given cross-section precision., Comment: Minor changes to text and figure labels

We present a novel lepton-nucleus event generator: ACHILLES, A CHIcagoLand Lepton Event Simulator. The generator factorizes the primary interaction from the propagation of hadrons in the nucleus, which allows for a great deal of modularity, facilitating further improvements and interfaces with existing codes. We validate our generator against high quality electron-carbon scattering data in the quasielastic regime, including the recent CLAS/e4v reanalysis of existing data. We find good agreement in both inclusive and exclusive distributions. By varying the assumptions on the propagation of knocked out nucleons throughout the nucleus, we estimate a component of theoretical uncertainties. We also propose novel observables that will allow for further testing of lepton-nucleus scattering models. ACHILLES is readily extendable to generate neutrino-nucleus scattering events., 19 pages, 13 figures

A variety of new physics scenarios allow for neutrinos to up-scatter into a heavy neutral lepton state. For a range of couplings and neutrino energies, the heavy neutrino may travel some distance before decaying to visible final states. When both the up-scattering and decay occur within the detector volume, these "double bang" events produce distinctive phenomenology with very low background. In this work, we first consider the current sensitivity at Super-Kamiokande via the atmospheric neutrino flux, and find current data may already provide new constraints. We then examine projected future sensitivity at DUNE and Hyper-Kamiokande, including both atmospheric and beam flux contributions to double-bang signals., 17 pages, 6 figures. v2: minor changes, references added and typos fixed. Matches version accepted for publication in JHEP

The nuclei $^{151}$Sm and $^{171}$Tm have been identified as attractive candidates for the detection of the cosmic neutrino background. Both isotopes undergo first-forbidden non-unique beta decays which inhibits a prediction of their spectral shape using symmetries alone and this has, so far, obstructed a definitive prediction of their neutrino capture cross sections. In this work we point out that for both elements the so-called "$\xi$-approximation" is applicable and this effectively reduces the spectral shape to deviate by at most $1\%$ from the one that would arise if beta decays were of the allowed type. Using measured half-lives we extract the relevant nuclear matrix element and predict the neutrino capture cross sections for both isotopes at $1\%$ level, accounting for a number of relevant effects including radiative corrections and the finite size of the nuclei. We obtained $(1.12\pm 0.01)\times 10^{-46}{\rm cm}^2$ for $^{171}$Tm and $(4.77\pm 0.01)\times 10^{-48}{\rm cm}^2$ for $^{151}$Sm. This method is robust as it does not rely on the data points near the end-point of the beta spectrum which may be contaminated by atomic physics effects, namely shake-up and shake-off. Finally, we calculate the target mass which is necessary for cosmic neutrino discovery and discuss several bottlenecks and respective solutions associated to the experimental program. We conclude that the detection of cosmic neutrino background by neutrino capture on $^{151}$Sm and $^{171}$Tm is achievable and free from theoretical limitations but still subject to technical issues that should be further investigated by the experimentalists in the context of the proposed PTOLEMY project., Comment: published version; 10 pages, 2 figures

The ground-breaking works of Weinberg have opened the way to calculations of atomic nuclei that are based on systematically improvable Hamiltonians. Solving the associated many-body Schr\"odinger equation involves non-trivial difficulties, due to the non-perturbative nature and strong spin-isospin dependence of nuclear interactions. Artificial neural networks have proven to be able to compactly represent the wave functions of nuclei with up to $A=4$ nucleons. In this work, we extend this approach to $^6$Li and $^6$He nuclei, using as input a leading-order pionless effective field theory Hamiltonian. We successfully benchmark their binding energies, point-nucleon densities, and radii with the highly accurate hyperspherical harmonics method., Comment: 15 pages, 3 figures, invited contribution to the special issue in Few-Body Systems "Celebrating 30 years of Steven Weinberg's papers on Nuclear Forces from Chiral Lagrangians"

We propose a novel approach to intranuclear cascades which takes as input quantum MonteCarlo nuclear configurations and uses a semi-classical, impact-parameter based algorithm to modelthe propagation of protons and neutrons in the nuclear medium. We successfully compare oursimulations to available proton-carbon scattering data and nuclear-transparency measurements. Byanalyzing the dependence of the simulated observables upon the ingredients entering our intranuclearcascade algorithm, we provide a quantitative understanding of their impact. Particular emphasisis devoted to the role played by nuclear correlations, the Pauli exclusion principle, and interactionprobability distributions., Comment: 14 pages, 10 figures

A neutrino community workshop was held at Fermilab in Jan 2020, with the aim of developing an implementation plan for a set of common interfaces to Neutrino Event Generators. This white paper summarizes discussions at the workshop and the resulting plan.

The electromagnetic responses of carbon obtained from the Green's function Monte Carlo and spectral function approaches using the same dynamical input are compared in the kinematical region corresponding to momentum transfer in the range 300-570 MeV. The results of our analysis, aimed at pinning down the limits of applicability of the approximations involved in the two schemes, indicate that the factorization ansatz underlying the spectral function formalism provides remarkably accurate results down to momentum transfer as low as 300 MeV. On the other hand, it appears that at 570 MeV relativistic corrections to the electromagnetic current not included in the Monte Carlo calculations may play a significant role in the transverse channel., Comment: 8 pages, 6 figures

The excitation of two particle-two hole final states in neutrino-nucleus scattering, not taken into account in Monte Carlo simulations for data analysis, has been advocated by many authors as the source of the excess cross section observed by the MiniBooNE collaboration in the quasi elastic channel. We analyse the mechanisms leading to the appearance of two particle-two hole states, and show that interference between the amplitudes involving one- and two-nucleon currents, not consistently included in existing calculations, plays a major role. A novel approach allowing to treat one- and two-nucleon current contributions on the same footing is outlined.

The complexity of many-body quantum wave functions is a central aspect of several fields of physics and chemistry where non-perturbative interactions are prominent. Artificial neural networks (ANNs) have proven to be a flexible tool to approximate quantum many-body states in condensed matter and chemistry problems. In this work we introduce a neural-network quantum state ansatz to model the ground-state wave function of light nuclei, and approximately solve the nuclear many-body Schr\"odinger equation. Using efficient stochastic sampling and optimization schemes, our approach extends pioneering applications of ANNs in the field, which present exponentially-scaling algorithmic complexity. We compute the binding energies and point-nucleon densities of $A\leq 4$ nuclei as emerging from a leading-order pionless effective field theory Hamiltonian. We successfully benchmark the ANN wave function against more conventional parametrizations based on two- and three-body Jastrow functions, and virtually-exact Green's function Monte Carlo results., Comment: 4 pages, 2 figures