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arXiv:2609.07452

Universal reduced order modelling for the nuclear finite amplitude method

Emma Vancayseele, Pepijn Demol, Luis González-Miret Zaragoza, Mikaël Frosini, Wouter Ryssens

Published Sep 7, 2026• 0 citations
arXivHTMLPDF

Abstract

The quasiparticle random phase approximation or QRPA has been a foundational many-body technique for decades across quantum chemistry, condensed matter and nuclear physics. Although computing power has increased and the matrix-free Finite Amplitude Method (FAM) exists, the computational complexity of FAM-QRPA calculations remains a limiting factor for the generation of linear response data on atomic nuclei that are crucial for several research fields. In this work, we establish that the FAM-QRPA equations are inherently suited to a reduced order modelling framework and can be emulated efficiently. Moreover, we present a greedy snapshot selection strategy that leverages the reduced cost of FAM-QRPA calculations when the imaginary part of the excitation frequency is large. Even when accounting for its construction, the resulting emulator accelerates strength function calculations by significantly more than an order of magnitude. We demonstrate that this framework and its speed-up generalize to light and heavy nuclei, different numerical representations, and diverse nuclear models including chiral EFT and configuration-interaction shell model approaches, as well as Skyrme, Gogny, and relativistic energy density functionals.

DOI
10.48550/arxiv.2609.07452

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The quasiparticle random phase approximation or QRPA has been a foundational many-body technique for decades across quantum chemistry, condensed matter and nuclear physics. Although computing power has increased and the matrix-free Finite Amplitude Method (FAM) exists, the computational complexity of FAM-QRPA calculations remains a limiting factor for the generation of linear response data on atomic nuclei that are crucial for several research fields. In this work, we establish that the FAM-QRPA equations are inherently suited to a reduced order modelling framework and can be emulated efficiently. Moreover, we present a greedy snapshot selection strategy that leverages the reduced cost of FAM-QRPA calculations when the imaginary part of the excitation frequency is large. Even when accounting for its construction, the resulting emulator accelerates strength function calculations by significantly more than an order of magnitude. We demonstrate that this framework and its speed-up generalize to light and heavy nuclei, different numerical representations, and diverse nuclear models including chiral EFT and configuration-interaction shell model approaches, as well as Skyrme, Gogny, and relativistic energy density functionals.
Background: The quasiparticle random-phase approximation (QRPA) within nuclear density functional theory provides a powerful framework for describing collective excitations. Although the finite-amplitude method (FAM) efficiently solves the QRPA problem, repeated calculations for different external-field parameters remain computationally demanding. Purpose: We construct a reduced basis method (RBM)-based emulator for the FAM that treats the complex energy of the external field as a model parameter to efficiently reproduce FAM amplitudes and QRPA eigenmodes. Methods: High-fidelity FAM calculations are performed at a small set of training points in the complex-energy plane. The resulting FAM amplitudes form a non-orthogonal reduced basis. A variational equation yields an emulator that can predict the response at arbitrary complex energies and QRPA eigensolutions without additional full FAM calculations. Results: The RBM emulator accurately reproduces FAM strength distributions in both giant-resonance and low-energy regions when the relevant energy domain is covered by the training set. It also reproduces imaginary QRPA modes associated with shape instabilities of the HFB state. Applied to the Kπ=0+K^π=0^+Kπ=0+ mode of rare-earth Dy isotopes in a realistic model space, the emulator reproduces strength distributions and the lowest 0+0^+0+ collective states with precision comparable to full FAM calculations, reducing the computational cost by more than an order of magnitude. Conclusions: The RBM provides an efficient and accurate FAM emulator. Its ability to reproduce giant-resonance, low-energy, and imaginary-energy modes at drastically reduced computational cost makes it promising for density-functional optimization, calculations of collective inertia, and large-scale surveys of nuclear collective excitations.
Abstract The linear response theory is a powerful tool to study properties of quantum many-particle systems. It uses a one-body perturbation field (as a pump) and measures a change in another (or the same) one-body observable (as a probe). In the context of time-dependent density functional theory (TDDFT), the primary target of the linear response is the density response. The finite amplitude method (FAM) significantly reduces both computational cost and coding tasks, and succeeds in facilitating the linear response calculations in a variety of fields in nuclear physics. We start with a review of the linear response theory and present the essence of the FAM theory and various applications, especially in studies of nuclear collective dynamics.
Reduced-basis methods provide a powerful framework for building efficient and accurate emulators. Although widely applied in many fields to simplify complex models, reduced-basis methods have only been recently introduced into nuclear physics. In this Letter we build an emulator to study the single-particle structure of atomic nuclei. By scaling a suitable mean-field Hamiltonian, a ``universal'' reduced basis is constructed capable of accurately and efficiently reproduce the entire single-particle spectrum of a variety of nuclei. Indeed, the reduced-basis model reproduces both ground- and excited-state energies as well as the associated wave functions with remarkable accuracy. Our results bode well for more demanding applications that use Bayesian optimization to calibrate nuclear energy density functionals.
The extension of ab initio quantum many-body theory to higher accuracy and larger systems is intrinsically limited by the handling of large data objects in form of wave-function expansions and/or many-body operators. In this work we present matrix factorization techniques as a systematically improvable and robust tool to significantly reduce the computational cost in many-body applications at the price of introducing a moderate decomposition error. We demonstrate the power of this approach for the nuclear two-body systems, for many-body perturbation theory calculations of symmetric nuclear matter, and for non-perturbative in-medium similarity renormalization group simulations of finite nuclei. Establishing low-rank expansions of chiral nuclear interactions offers possibilities to reformulate many-body methods in ways that take advantage of tensor factorization strategies.
The shell model provides a powerful framework for nuclear structure calculations. The nucleons beyond an inert magic core are confined in a valence shell and interact through an effective two-body potential generally determined from the G-matrix method. However, the applicability of the shell model remains limited by the exponential growth of the many-body space with the number of valence nucleons and with the size of the one-body space. The quantum Monte Carlo (QMC) methods may thus be considered as a potentially attractive alternative to the direct diagonalization of the Hamiltonian matrix. The many-body problem is indeed reduced to a set of stochastic one-body problems describing independent particles in a fluctuating external field. Up to date, the QMC approaches of the shell model lead to the ground-state and the thermodynamic properties, but a detailed spectroscopy of nuclei is not reachable. Furthermore, they suffer from a common pathology of fermionic QMC methods, namely the sign/phase problem, which strongly contaminates the convergence of the calculation. In this context, we will present a new QMC method, providing the "yrast spectroscopy" of nuclei, and in which the sign/phase problem is managed through the constrained path approximation that is widely used in the ab initio nuclear calculations and in condensed matter physics.
The ground state of a many body Hamiltonian considered in the quasiparticle representation is redefined by accounting for the quasiparticle quadrupole pairing interaction. The residual interaction of the newly defined quasiparticles is treated by the quasiparticle random phase approximation (QRPA). Solutions of the resulting equations exhibit specific features. In particular, there is no interaction strength where the first root is vanishing. A comparison with other renormalization methods is presented. Application to a single [Formula: see text]-shell allows for the results interpretation by comparing them with those obtained by exact calculations.