Extraction of Spectra in the Shell Model Monte Carlo Method Using Imaginary-Time Correlation Matrices

IF 8.1 1区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY
Y. Alhassid, M. Bonett-Matiz, C. N. Gilbreth, S. Vartak
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引用次数: 0

Abstract

Nuclear energy levels are usually calculated using conventional diagonalization methods in the framework of the configuration-interaction (CI) shell model but these methods are prohibited in very large model spaces. The shell model Monte Carlo (SMMC) method is a powerful technique for calculating thermal and ground-state observables of nuclei in very large model spaces, but it is challenging to extract nuclear spectra in this approach. We present a novel method to extract within SMMC low-lying energy levels for given values of a set of good quantum numbers such as spin and parity. The method is based on imaginary-time correlation matrices (ITCMs) of one-body densities that satisfy asymptotically a generalized eigenvalue problem. We validate the method in a light nucleus that allows comparison with exact diagonalization results of the CI shell-model Hamiltonian. The method is broadly applicable to quantum many-body systems in other disciplines.
利用虚时相关矩阵提取贝壳模型蒙特卡洛法中的光谱
核能级通常是在构型-相互作用(CI)壳模型框架内使用传统的对角化方法计算的,但这些方法在非常大的模型空间中是被禁止的。壳模型蒙特卡洛(SMMC)方法是在超大模型空间中计算核的热态和基态观测值的强大技术,但在这种方法中提取核光谱具有挑战性。我们提出了一种在 SMMC 中提取自旋和奇偶性等一组良好量子数给定值的低洼能级的新方法。该方法基于单体密度的虚时相关矩阵(ITCM),该矩阵近似满足广义特征值问题。我们在轻核中验证了该方法,并将其与 CI 壳模型哈密顿的精确对角化结果进行了比较。该方法广泛适用于其他学科的量子多体系统。
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来源期刊
Physical review letters
Physical review letters 物理-物理:综合
CiteScore
16.50
自引率
7.00%
发文量
2673
审稿时长
2.2 months
期刊介绍: Physical review letters(PRL)covers the full range of applied, fundamental, and interdisciplinary physics research topics: General physics, including statistical and quantum mechanics and quantum information Gravitation, astrophysics, and cosmology Elementary particles and fields Nuclear physics Atomic, molecular, and optical physics Nonlinear dynamics, fluid dynamics, and classical optics Plasma and beam physics Condensed matter and materials physics Polymers, soft matter, biological, climate and interdisciplinary physics, including networks
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