activity
20152023
most citedDense Nuclear Matter Equation of State from Heavy-Ion Collisions

189 citations · 845 across the 15 of their papers we have counts for

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nucl-th2023★ 189 cited

Dense Nuclear Matter Equation of State from Heavy-Ion Collisions

Agnieszka Sorensen, Kshitij Agarwal, Kyle W. Brown +133

The nuclear equation of state (EOS) is at the center of numerous theoretical and experimental efforts in nuclear physics. With advances in microscopic theories for nuclear interact…

nucl-th2022★ 147 cited

Trace anomaly as signature of conformality in neutron stars

Yuki Fujimoto, Kenji Fukushima, Larry D. McLerran +1

We discuss an interpretation that a peak in the sound velocity in neutron star matter, as suggested by the observational data, signifies strongly-coupled conformal matter. The norm…

nucl-th2021★ 12 cited

Equation of state of neutron star matter and its warm extension with an interacting hadron resonance gas

Yuki Fujimoto, Kenji Fukushima, Yoshimasa Hidaka +2

We propose an interpolating equation of state that satisfies phenomenologically established boundary conditions in two extreme regimes at high temperature and low baryon density an…

nucl-th2021★ 60 cited

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

We discuss deep learning inference for the neutron star equation of state (EoS) using the real observational data of the mass and the radius. We make a quantitative comparison betw…

nucl-th2019★ 110 cited

Mapping neutron star data to the equation of state using the deep neural network

Yuki Fujimoto, Kenji Fukushima, Koichi Murase

The densest state of matter in the universe is uniquely realized inside central cores of the neutron star. While first-principles evaluation of the equation of state of such matter…

nucl-th2017★ 70 cited

Methodology study of machine learning for the neutron star equation of state

Yuki Fujimoto, Kenji Fukushima, Koichi Murase

We discuss a methodology of machine learning to deduce the neutron star equation of state from a set of mass-radius observational data. We propose an efficient procedure to deal wi…