Shell‐Model Applications in Nuclear Spectroscopy

Physics Today ◽  
1978 ◽  
Vol 31 (11) ◽  
pp. 68-70 ◽  
Author(s):  
P. J. Brussaard ◽  
P. W. M. Glaudemans ◽  
Abraham Klein
Keyword(s):  
Shell Model ◽  
Nuclear Spectroscopy

Indiana Conference on Nuclear Spectroscopy and the Shell Model

Science ◽  
1953 ◽  
Vol 118 (3063) ◽  
pp. 285-288
Author(s):  
E. J. Konopinski
Keyword(s):  
Shell Model ◽  
Nuclear Spectroscopy

scholarly journals Three Particle Nuclear Spectroscopy of91Y on the Shell Model

1966 ◽  
Vol 35 (1) ◽  
pp. 176-177
Author(s):  
Naresh Kumar ◽  
Vijay Kumar ◽  
Gian Aggarwal
Keyword(s):  
Shell Model ◽  
Nuclear Spectroscopy

Large scale shell model study of nuclear spectroscopy in nuclei around [sup 132]Sn

2012 ◽  
Author(s):  
N. Lo Iudice ◽  
D. Bianco ◽  
F. Andreozzi ◽  
A. Porrino ◽  
F. Knapp
Keyword(s):  
Shell Model ◽  
Large Scale ◽  
Nuclear Spectroscopy ◽  
Model Study

MONTE CARLO SHELL MODEL CALCULATIONS FOR ATOMIC NUCLEI

2001 ◽  
Vol 15 (10n11) ◽  
pp. 1463-1473
Author(s):  
T. OTSUKA ◽  
T. MIZUSAKI ◽  
Y. UTSUNO ◽  
N. SHIMIZU ◽  
M. HONMA
Keyword(s):  
Monte Carlo ◽  
Shell Model ◽  
Quantum Monte Carlo ◽  
Level Structure ◽  
Nuclear Spectroscopy ◽  
Model Calculations ◽  
Atomic Nuclei ◽  
Truncation Scheme ◽  
Transition Matrix Elements ◽  
Monte Carlo Shell Model

The formulation and recent applications of the Quantum Monte Carlo diagonalization (QMCD) method are reported. The QMCD has been proposed for solving the quantum many-body inteacting systems, providing us with energy eigenvalues, transition matrix elements and wave functions. Its application to the nuclear shell model is referred to as the Monte Carlo Shell Model. By the Monte Carlo Shell Model calculations, the level structure of low-lying states can be studied with realistic interactions, providing a useful tool for nuclear spectroscopy. The Monte Carlo Shell Model has been applied to the study of a variety of nuclei, and can be characterized as the importance truncation scheme to the full diagonalization which is infeasible in many cases due to extremely large dimensions.

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