Abstract
An estimation method of the nuclear level density stochastically based on nuclear shell-model calculations is introduced. In order to count the number of the eigen-values of the shell-model Hamiltonian matrix, we perform the contour integral of the matrix element of a resolvent. The shifted block Krylov subspace method enables us its efficient computation. Utilizing this method, the contamination of center-of-mass motion is clearly removed.
Highlights
Nuclear level density is a key ingredient of the Hauser-Feshbach calculations [1] to understand neutron-capture processes and compound nucleus microscopically
Much effort has been paid to develop efficient methods to estimate nuclear level densities based on shell model, e.g. the shell model Monte Carlo (SMMC) [3], the moment-based methods [4, 5], and the Lanczos-based method [6]
We review stochastic estimation of the eigenvalue distribution based on shifted Krylov-subspace method [7] and its application to nuclear shell model calculations [8]
Summary
Nuclear level density is a key ingredient of the Hauser-Feshbach calculations [1] to understand neutron-capture processes and compound nucleus microscopically. Much effort has been paid to develop efficient methods to estimate nuclear level densities based on shell model, e.g. the shell model Monte Carlo (SMMC) [3], the moment-based methods [4, 5], and the Lanczos-based method [6]. In this proceedings, we review stochastic estimation of the eigenvalue distribution based on shifted Krylov-subspace method [7] and its application to nuclear shell model calculations [8].
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