DENSE Collaboration
Deep-learning Equation of state for Neutron-Star Enterprise
How can we reconstruct the equation of state in neutron stars from observations?
This project gives one answer to the question!
Introduction
[TBA later]
Downloads
[TBA later]
Publications
- Extensive Studies of the Neutron Star Equation of State from the Deep Learning Inference with the Observational Data Augmentation,
Yuki Fujimoto, Kenji Fukushima, Koichi Murase,
JHEP 03 (2021) 273 / arXiv:2101.08156 [nucl-th] / PDF / Inspire HEP
- Mapping neutron star data to the equation of state using the deep neural network,
Yuki Fujimoto, Kenji Fukushima, Koichi Murase,
Phys. Rev. D 101 (2020) 5, 054016 / arXiv:1903.03400 [nucl-th] / PDF / Inspire HEP.
- Methodology study of machine learning for the neutron star equation of state,
Yuki Fujimoto, Kenji Fukushima, Koichi Murase,
Phys. Rev. D 98 (2018) 2, 023019 / arXiv:1711.06748 [nucl-th] / PDF / Inspire HEP.
Awards
- JPS 16th Young Researcher Encouragement Award / 23rd Nuclear Theory Paper Award, The Physical Society of Japan (JPS), March, 2022
Yuki Fujimoto, Mapping neutron star data to the equation of state using the deep neural network
Acknowledgments
This project is fully or partially supported by the following grants.
Contact e-mail address: DENSE Collaboration <TBA@TBA>
Hadron Theoretical Physics, Nuclear Theory (A0), Department of Physics, School of Science, The University of Tokyo,
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8654, Japan.