arXiv subjects

Alessandro Lovato

Publications and source records attributed to Alessandro Lovato.

At least 19 recordsLinked to original sources

arXiv2026

Accurate Charge Radius Measurement of $^{14}$C Confronts \textit{Ab Initio} Theory

Located at the neutron shell closure $N = 8$, the long-lived radioactive isotope $^{14}\mathrm{C} $ plays a critical role in geochronology and nuclear structure studies. Despite its widespread use, the nuclear charge radius of $^{14}$C has remained less precisely known compared to its stable counterpart $^{12}$C. Here, we report a high-precision determination of the $^{14}$C charge radius using collinear laser spectroscopy at the COALA setup at TU Darmstadt, improving upon the precision of previous muonic measurements by a factor $5$ and revealing a $1.9\sigma$ discrepancy of combined uncertainty, indicating a likely underestimated uncertainty in the muonic determination. This measurement challenges state-of-the-art \textit{ab initio} nuclear theory calculations, including auxiliary field diffusion Monte Carlo, the valence-space in-medium similarity renormalization group, and the no-core shell model, augmented by neural-network techniques. With $^{12}$C and $^{14}$C now forming one of the most precisely characterized even-even isotope pairs, these results also enable improved QED tests.

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arXiv2026

Medium-mass nuclei with neural quantum states

We compute ground-state energies and charge radii of light- to medium-mass nuclei with up to $A=58$ nucleons, leveraging a variational Monte Carlo method based on Pfaffian-Jastrow neural quantum states. To further understand which elements of the nuclear Hamiltonian are "essential" to predict binding energies and charge radii across the nuclear chart with few-percent errors, we consider different interactions inspired by pionless effective field theory. Specifically, in addition to model "o" of [Phys. Rev. C 103, 054003 (2021)], we study the impact of charge-symmetry-breaking and charge-dependent terms in the nucleon-nucleon force, as well as $p$-wave contributions, which have been found to be critical for the stability of $p$-shell nuclei. In addition to its intrinsic interest, our work assesses the performance of neural quantum states in the medium-mass regime and examines the impact of these interaction modifications. Using the resulting ground-state simulations, we analyze the computational scaling of variational Monte Carlo with neural quantum states as a function of system size and computational resources, enabling projections for future large-scale calculations.

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arXiv2026

Tomography of Atomic Nuclei

We carry out continuum quantum Monte Carlo calculations of the quantum-mechanical Wigner distribution functions of selected nuclei, up to $^{16}$O. These distributions provide a form of quantum tomography of the spatial and momentum structure of the system. They also help identify the location of high-momentum regions in atomic nuclei and provide insight into the onset of alpha clustering. Besides their intrinsic interest, these distributions will be useful for neutrino event generators, as they correlate the positions and momenta of nucleons in the initial target state. To facilitate their application, we address the need to store them compactly by developing an accurate Gaussian Process emulator that automatically preserves their normalization.

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arXiv2026

Quantum Monte Carlo calculation of $\delta_C$ in the superallowed beta decay of $^{10}$C

We perform an ab initio quantum Monte Carlo calculation of the isospin-symmetry-breaking correction $\delta_C$ to the superallowed $\beta$ decay of $^{10}{\rm C}$. Using both phenomenological and chiral nuclear interactions, we evaluate the Fermi matrix element and quantify its deviation from the canonical $\sqrt{2}$ value. The resulting $\delta_C$ values lie in the range $\approx 0.15$--$0.25\%$ and are consistent, within sizable uncertainties (approximately $34\%$--$65\%$ relative), across Hamiltonians, indicating no statistically significant dependence on the choice of nuclear interaction. The extracted values of $V_{ud}$ are also found to be compatible with current determinations within these uncertainties.

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arXiv2026

Neural Quantum States in Non-Stabilizer Regimes: Benchmarks with Atomic Nuclei

As neural networks are known to efficiently represent classes of tensor-network states as well as volume-law-entangled states, identifying which properties determine the representational capabilities of neural quantum states (NQS) remains an open question. We construct NQS representations of ground states of medium-mass atomic nuclei, which typically exhibit significant entanglement and non-stabilizerness, to study their performance in relation to the quantum complexity of the target state. Leveraging a second-quantized formulation of NQS tailored for nuclear-physics applications, we perform calculations in active orbital spaces using a restricted Boltzmann machine (RBM), a prototypical NQS ansatz. For a fixed number of configurations, we find that states with larger non-stabilizerness are systematically harder to learn, as evidenced by reduced accuracy. This finding suggests that non-stabilizerness is a primary factor governing the compression and representational efficiency of RBMs in entangled regimes, and motivates extending these studies to more sophisticated network architectures.

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arXiv2026

Nuclear binding, correlations, and the $A$-dependence of the EMC effect

The measurements of inclusive electron scattering from nuclear targets carried out at the Thomas Jefferson National Accelerator Facility in the mid 2000s have provided valuable novel information on the $A$-dependence of the modifications of nuclear structure functions known as EMC effect. We argue that these data are best described in terms of the scaling variable $\widetilde{y}$, designed to take into account dynamical effects in interacting many-particle systems, and analyse the $A$-dependence of the slope of the inclusive cross section ratios, $R_A = (\sigma_A/A)/(\sigma_2/2)$, providing a measure of the size of the EMC effect in the region where nuclear binding plays a leading role. The results of our study clearly hint at a linear correlation between $dR_A(\widetilde{y})/d\widetilde{y}$ and the average nucleon removal energy $\langle E_A \rangle$. The role of correlation effects in the determination of $\langle E_A \rangle$ is highlighted.

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arXiv2026

Neural-network quantum states for the nuclear many-body problem

A long-standing goal of nuclear theory is to explain how the structure and dynamics of atomic nuclei and neutron-star matter emerge from the underlying interactions among protons and neutrons. Achieving this goal requires solving the nuclear quantum many-body problem with high accuracy across a wide range of length scales and density regimes. In this review, we discuss how artificial neural network representations of the nuclear many-body wave function have significantly extended the capabilities of continuum quantum Monte Carlo methods. In particular, neural network quantum states enable calculations of larger systems than were previously accessible and provide a flexible framework for capturing phenomena that challenge conventional approaches, including the emergence of nuclear clusters and superfluid phases in dense matter. We highlight recent applications to finite nuclei, infinite nuclear and neutron matter, and dynamical processes relevant to lepton-nucleus and nucleus-nucleus scattering. We also discuss conceptual and methodological connections with condensed matter physics, emphasizing developments in neural network quantum states that bridge strongly correlated systems across disciplines. Together, these developments demonstrate how neural-network methods open new avenues toward unified and accurate descriptions of nuclear structure, matter, and reactions.

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arXiv2025

Nuclear collectivity and the harmonic spectrum of two-body correlations

High-energy nuclear collisions have opened a new experimental method to reveal collective behavior in nuclear ground states through the lens of many-body correlations of nucleons. Using ab initio lattice and variational calculations of $^{20}$Ne and $^{16}$O, we study how emergent phenomena such as deformation or clustering can be identified in these systems from the dependence of their two-body density distributions on the relative azimuthal angle of nucleon pairs. A harmonic analysis of the correlation functions reveals in particular a dominant quadrupole component in $^{20}$Ne, consistent with a bowling-pin picture, and a prominent triangular modulation in $^{16}$O, possibly indicative of alpha-cluster correlations. Given that such structures can be accurately identified in high-energy collider experiments, these findings open a new paradigm for analyzing emergent collective behavior in atomic nuclei, relating their intrinsic shapes to the harmonic spectrum of microscopic correlations.

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arXiv2025

Single pion-production and pion propagation in Achilles

We extend the applicability of Achilles (A CHIcagoLand Lepton Event Simulator) by incorporating the single-pion production mechanism in a fully exclusive fashion. The electroweak interaction vertex is modeled by combining the state-of-the-art Dynamical Coupled-Channels approach with realistic hole spectral functions, which account for correlations in both the initial target state and the residual spectator system. Final-state interactions are treated using a semi-classical intranuclear cascade that leverages nuclear configurations to determine the correlated spatial distribution of protons and neutrons. The meson-baryon scattering amplitudes used in the cascade are computed within the Dynamical Coupled-Channels framework, consistent with the electroweak vertex. To model pion absorption, we employ the optical potential approach of Oset and Salcedo. As an alternative approach, we explicitly model the production and propagation of resonances which mediate pion-nucleon scattering and pion absorption. We validate out approach against pion-nucleon and pion-nucleus scattering data, and present comparisons with electron- and neutrino-nucleus measurements from e4$\nu$, T2K, MINER$\nu$A, and MicroBooNE.

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arXiv2025

Hypernuclei with Neural Network Quantum States

Leveraging complementary machine-learning-based approaches, we compute properties of $s$- and $p$-shell $Λ$ hypernuclei - including binding energies, single-particle densities, and radii - starting from the individual interactions among their constituents. These interactions are modeled using an improved leading-order pionless effective field theory expansion, with coefficients determined via a Gaussian Process framework anchored on virtually exact few-body techniques. We solve the many-body Schrödinger equation using a variational Monte Carlo method based on neural network quantum states, extending it for the first time to include $Λ$ particles alongside protons and neutrons. The predicted binding energies show remarkably good agreement with experimental results, given the simplicity of the input Hamiltonian. We also confirm the experimentally observed shrinkage of the proton radius in $^7_Λ$Li compared to its parent nucleus, $^6$Li. This work paves the way for an ab initio description of medium-mass and heavy hypernuclei, as well as for understanding the onset of strange degrees of freedom in the core of neutron stars.

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arXiv2025

Nuclear responses with neural-network quantum states

We introduce a variational Monte Carlo framework that combines neural-network quantum states with the Lorentz integral transform technique to compute the dynamical properties of self-bound quantum many-body systems in continuous Hilbert spaces. While broadly applicable to various quantum systems, including atoms and molecules, in this initial application we focus on the photoabsorption cross section of light nuclei, where benchmarks against numerically exact techniques are available. Our accurate theoretical predictions are complemented by robust uncertainty quantification, enabling meaningful comparisons with experiments. We demonstrate that a simple nuclear Hamiltonian, based on a leading-order pionless effective field theory expansion and known to accurately reproduce the ground-state energies of nuclei with $A\leq 20$ nucleons also provides a reliable description of the photoabsorption cross section.

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arXiv2024

Relativistic Corrections to the CBF Effective Nuclear Hamiltonian

We discuss the inclusion of relativistic boost corrections into the CBF effective nuclear Hamiltonian, derived from a realistic model of two- and three-nucleon interactions using the formalism of correlated basis functions and the cluster expansion technique. Different procedures to take into account the effects of boost interactions are compared on the basis of the ability to reproduce the nuclear matter equation of state obtained from accurate many-body calculations. The results of our study show that the repulsive contribution of the boost interaction significantly depends on the underlying model of the non relativistic potential. On the other hand, the dominant relativistic correction turns out to be the corresponding reduction of the strength of repulsive three-nucleon interactions, leading to a significant softening of the equation of state at supranuclear densities.

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arXiv2024

Investigating the crust of neutron stars with neural-network quantum states

An accurate description of low-density nuclear matter is crucial for explaining the physics of neutron star crusts. In the density range between approximately 0.01 fm$^{-3}$ and 0.1 fm$^{-3}$, matter transitions from neutron-rich nuclei to various higher-density pasta shapes, before ultimately reaching a uniform liquid. In this work, we introduce a variational Monte Carlo method based on a neural Pfaffian-Jastrow quantum state, which allows us to model the transition from the liquid phase to neutron-rich nuclei microscopically. At low densities, nuclear clusters dynamically emerge from the microscopic interactions among protons and neutrons, which we model based on pionless effective field theory. Our variational Monte Carlo approach represents a significant improvement over the state-of-the-art auxiliary-field diffusion Monte Carlo method, which is severely hindered by the fermion-sign problem in this low-density regime and cannot capture the onset of clusters. In addition to computing the energy per particle of symmetric nuclear matter and pure neutron matter, we analyze an intermediate isospin-asymmetry configuration to elucidate the formation of nuclear clusters. We also provide evidence that the presence of such nuclear clusters influences the amount of protons in the crust compared to protons in beta-equilibrated, neutrino-transparent matter.

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arXiv2024

Restricted Boltzmann Machines Propagators for Auxiliary Field Diffusion Monte Carlo

The auxiliary field diffusion Monte Carlo method uses imaginary-time projection techniques to accurately solve the ground-state wave function of atomic nuclei and infinite nuclear matter. In this work, we present a novel representation of the imaginary-time propagator based on restricted Boltzmann machines. We test its accuracy against the routinely employed Hubbard-Stratonovich transformations by evaluating ground-state energies and single-particle densities of selected light nuclei. This analysis paves the way for incorporating more realistic nuclear potentials in the auxiliary field diffusion Monte Carlo method, including isospin-dependent spin-orbit terms and cubic spin-isospin operators, which characterize accurate phenomenological and chiral effective field theory Hamiltonians.

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arXiv2024

Modeling inclusive electron-nucleus scattering with Bayesian artificial neural networks

We introduce a Bayesian protocol based on artificial neural networks that is suitable for modeling inclusive electron-nucleus scattering on a variety of nuclear targets with quantified uncertainties. Unlike previous applications in the field, which directly parameterize the cross sections, our approach employs artificial neural networks to represent the longitudinal and transverse response functions. In contrast to cross sections, which depend on the incoming energy, scattering angle, and energy transfer, the response functions are determined solely by the energy and momentum transfer to the system, allowing the angular component to be treated analytically. We assess the accuracy and predictive power of our framework against the extensive data in the quasielastic inclusive electron-scattering database. Additionally, we present novel extractions of the longitudinal and transverse response functions and compare them with previous experimental analysis and nuclear ab-initio calculations.

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arXiv2024

Static and dynamic properties of atomic nuclei with high-resolution potentials

We compute ground-state and dynamical properties of $^4$He and $^{16}$O nuclei using as input high-resolution, phenomenological nucleon-nucleon and three-nucleon forces that are local in coordinate space. The nuclear Schrödinger equation for both nuclei is accurately solved employing the auxiliary-field diffusion Monte Carlo approach. For the $^4$He nucleus, detailed benchmarks are carried out with the hyperspherical harmonics method. In addition to presenting results for the binding energies and radii, we also analyze the momentum distributions of these nuclei and their Euclidean response function corresponding to the isoscalar density transition. The latter quantity is particularly relevant for lepton-nucleus scattering experiments, as it paves the way to quantum Monte Carlo calculations of electroweak response functions of $^{16}$O.

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arXiv2023

One and Two-Body Current Contributions to Lepton-Nucleus Scattering

Modeling lepton-nucleus scattering with the accuracy required to extract neutrino-oscillation parameters from long- and short-baseline experiments necessitates retaining most quantum-mechanical effects. One such effect is the interference between one- and two-body current operators in the transition currents, which has been known to enhance the cross-sections, especially in transverse kinematics. In this work, we incorporate such interference in the spectral function formalism, which combines relativistic currents and kinematics with an accurate description of the initial target state. Our analysis of lepton-scattering off $^{12}$C demonstrates that interference effects appreciably enhance the transverse electromagnetic response functions and the flux-folded neutrino-nucleus cross section, in both cases, improving the agreement with experimental data. We discuss the impact on the neutrino-oscillation program and the determination of nucleon axial form factors.

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arXiv2023

Message-Passing Neural Quantum States for the Homogeneous Electron Gas

We introduce a message-passing-neural-network-based wave function Ansatz to simulate extended, strongly interacting fermions in continuous space. Symmetry constraints, such as continuous translation symmetries, can be readily embedded in the model. We demonstrate its accuracy by simulating the ground state of the homogeneous electron gas in three spatial dimensions at different densities and system sizes. With orders of magnitude fewer parameters than state-of-the-art neural-network wave functions, we demonstrate better or comparable ground-state energies. Reducing the parameter complexity allows scaling to $N=128$ electrons, previously inaccessible to neural-network wave functions in continuous space, enabling future work on finite-size extrapolations to the thermodynamic limit. We also show the Ansatz's capability of quantitatively representing different phases of matter.

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