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Cited by 507

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Relativistic mean-field theory and the high-density nuclear equation of state

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Müller, Horst, Serot, Brian D.·1996·Nuclear Physics A

Abstract

Abstract The properties of high-density nuclear and neutron matter are studied using a relativistic mean-field approximation to the nuclear matter energy functional. Based on ideas of effective field theory, nonlinear interactions between the fields are introduced to parametrize the density dependence of the energy functional. Various types of nonlinearities involving scalar-isoscalar (σ), vector-isoscalar (ω) and vector-isovector (ϱ) fields are studied. After calibrating the model parameters at equilibrium nuclear matter density, the model and parameter dependence of the resulting equation of state is examined in the neutron-rich and high-density regime. It is possible to build different models that reproduce the same observed properties at normal nuclear densities, but which yield maximum neutron star masses that differ by more than one solar mass. Implications for the existence of kaon condensates or quark cores in neutron stars are discussed.

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Metadata

Authors
Müller, H., & Serot, B. D.
Venue
Nuclear Physics A
Publisher
Elsevier BV
Published
1996-09
Volume
606
Issue
3-4
Pages
508-537
ISSN
0375-9474 (ISSN-L)
OpenAlex
W2058345843
Cited by
507
References
2
FWCI
2.80
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Relativistic mean-field theory and the high-density nuclear equation of state. https://app.cochat.ai/papers/10.1016/0375-9474(96)00187-x
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Müller, H., & Serot, B. D. (1996). Relativistic mean-field theory and the high-density nuclear equation of state. Nuclear Physics A. https://doi.org/10.1016/0375-9474(96)00187-x

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.