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arXiv:1407.3848 · Physical Review C

Adaptive multi-resolution 3D Hartree-Fock-Bogoliubov solver for nuclear structure

J. C. Pei, George I. Fann, Robert J. Harrison, Witold Nazarewicz, Yue Shi, S. Thornton

Published Aug 21, 2014• 38 citations
arXivHTMLPDF

Abstract

The authors use multi-resolution wavelet analysis and parallel computing to solve equations of nuclear density functional theory in three dimensions. The approach can be applied to nuclear and atomic complex quantum many-body problems involving many-particle superfluid systems, such as fissioning nuclei, pasta phases in the neutron star crust, and trapped cold fermions.

DOI
10.1103/physrevc.90.024317

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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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Solving the nuclear many-body problem engenders significant theoretical and computational challenges. I will briefly discuss the science that goes into and comes out of the nuclear problem, and then turn to the numerical implementations of coupled-cluster theory for the problem. Specific to the nuclear problem is the presence of real three-body forces which are computationally represented by six-dimensional tensors. Both memory and communications become issues as one begins to scale up the underlying coupled-cluster algorithms to thousands of processors. Another interesting feature of the nuclear problem is weak binding that occurs in very unstable nuclei. When the single-particle continuum is present, the nuclear Hamiltonian becomes complex. I also will describe our attempts to solve the complex coupled-cluster problem in the presence of complex interactions. Efficient parallelism requires spreading the interaction matrices globally and the coupled-cluster amplitudes in a more local fashion.
Given elementary inter-nucleon interactions,the resolution of the A-body Schrödinger equation gives access to the properties of the nuclear eigenstates. Many-body perturbation theory (MBPT) based on a Hartree-Fock mean field allows one to treat the dynamical correlations at play in doubly-closed-shell nuclei. Beyond shell closures,breaking U(1) symmetry associated with the conservation of neutron and proton numbers further permits to capture static correlations at the meanfield level and to formulate the well-behaved Bogoliubov many-body perturbation theory (BMBPT).Nevertheless, BMBPT results show contaminations associated with the broken symmetry that is only emergent on finite quantum system such as theatomic nucleus. Thus, the restoration of U(1) symmetry beyond the mean field is necessary for acorrect description and gives rise to the projected BMBPT method (PBMBPT). The goal is to implement PBMBPT in order to perform ab initio calculations of singly-open-shell mid-mass nuclei.The present work provides systematic solutions to the formal and technical problems arising during the implementation of PBMBPT: an automatic and safe method to generate PBMBPT diagrams and associated expressions, a framework to calculate other observables than the energy, an extension of the normal ordering approximation to symmetry breaking methods as well as an automatic and safe tool for spherical reduction of tensor networks.
Abstract Ab initio calculations have an essential role in our fundamental understanding of quantum many-body systems across many subfields, from strongly correlated fermions 1–3 to quantum chemistry 4–6 and from atomic and molecular systems 7–9 to nuclear physics 10–14 . One of the primary challenges is to perform accurate calculations for systems where the interactions may be complicated and difficult for the chosen computational method to handle. Here we address the problem by introducing an approach called wavefunction matching. Wavefunction matching transforms the interaction between particles so that the wavefunctions up to some finite range match that of an easily computable interaction. This allows for calculations of systems that would otherwise be impossible owing to problems such as Monte Carlo sign cancellations. We apply the method to lattice Monte Carlo simulations 15,16 of light nuclei, medium-mass nuclei, neutron matter and nuclear matter. We use high-fidelity chiral effective field theory interactions 17,18 and find good agreement with empirical data. These results are accompanied by insights on the nuclear interactions that may help to resolve long-standing challenges in accurately reproducing nuclear binding energies, charge radii and nuclear-matter saturation in ab initio calculations 19,20 .