An artificial neural network generates a new effective interaction jj44b_nn from jj44b, yielding shell model results for proton-rich Zn isotopes that are comparable to the original and closer to experiment in some cases.
Nuclear shell-model code for massive parallel computation, "KSHELL"
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abstract
A new code for nuclear shell-model calculations, "KSHELL", is developed. It aims at carrying out both massively parallel computation and single-node computation in the same manner. We solve the Schr\"{o}dinger's equation in the $M$-scheme shell-model model space, utilizing Thick-Restart Lanczos method. During the Lanczos iteration, the whole Hamiltonian matrix elements are generated "on-the-fly" in every matrix-vector multiplication. The vectors of the Lanczos method are distributed and stored on memory of each parallel node. We report that the newly developed code has high parallel efficiency on FX10 supercomputer and a PC with multi-cores.
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Shell Model Calculations for Proton-rich Zn Isotopes via New Generated Effective Interaction by Artificial Neural Networks
An artificial neural network generates a new effective interaction jj44b_nn from jj44b, yielding shell model results for proton-rich Zn isotopes that are comparable to the original and closer to experiment in some cases.