Nuclear mass predictions for the crustal composition of neutron stars: A Bayesian neural network approach
- Authors:
- Publication Date:
- Sponsoring Org.:
- USDOE Office of Science (SC), Nuclear Physics (NP)
- OSTI Identifier:
- 1235770
- Grant/Contract Number:
- FD05-92ER40750
- Resource Type:
- Publisher's Accepted Manuscript
- Journal Name:
- Physical Review C
- Additional Journal Information:
- Journal Name: Physical Review C Journal Volume: 93 Journal Issue: 1; Journal ID: ISSN 2469-9985
- Publisher:
- American Physical Society
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Utama, R., Piekarewicz, J., and Prosper, H. B. Nuclear mass predictions for the crustal composition of neutron stars: A Bayesian neural network approach. United States: N. p., 2016.
Web. doi:10.1103/PhysRevC.93.014311.
Utama, R., Piekarewicz, J., & Prosper, H. B. Nuclear mass predictions for the crustal composition of neutron stars: A Bayesian neural network approach. United States. https://doi.org/10.1103/PhysRevC.93.014311
Utama, R., Piekarewicz, J., and Prosper, H. B. Wed .
"Nuclear mass predictions for the crustal composition of neutron stars: A Bayesian neural network approach". United States. https://doi.org/10.1103/PhysRevC.93.014311.
@article{osti_1235770,
title = {Nuclear mass predictions for the crustal composition of neutron stars: A Bayesian neural network approach},
author = {Utama, R. and Piekarewicz, J. and Prosper, H. B.},
abstractNote = {},
doi = {10.1103/PhysRevC.93.014311},
journal = {Physical Review C},
number = 1,
volume = 93,
place = {United States},
year = {Wed Jan 20 00:00:00 EST 2016},
month = {Wed Jan 20 00:00:00 EST 2016}
}
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https://doi.org/10.1103/PhysRevC.93.014311
https://doi.org/10.1103/PhysRevC.93.014311
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Cited by: 113 works
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