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Bayesian inference of nuclear symmetry energy from measured and imagined neutron skin thickness in Sn<mml:mprescripts/><mml:none/>116,118,120,122,124,130,132, Pb<mml:mprescripts/><mml:none/>208, and Ca<mml:mprescripts/><mml:none/>48

2020/07/31 by Jun Xu, Wen-Jie Xie, Bao-An Li
Mathematics · Physics and Astronomy · #Astronomical and nuclear sciences #Combinatorics #Energy (signal processing) #Hadron #Mathematical physics #Mathematics #Neutron #Nuclear Physics and Applications #Nuclear physics #Nuclear physics research studies #Particle physics #Physics #Quantum mechanics #Saturation (graph theory) #nucl-ex #nucl-th

paper · pdf · doi:10.1103/physrevc.102.044316

published as Phys. Rev. C 102, 044316 (2020) · 11 pages, 6 figures, accepted by Physical Review C

openalex created_date 2020/07/23 · arxiv created 2020/09/29 · openalex publication_date 2020/10/14 · arxiv updated 2020/10/21 · openalex updated_date 2026/08/06

Abstract

The neutron skin thickness \mathrm\ensuremathΔrnp in heavy nuclei was known as one of the most sensitive terrestrial probes of the nuclear symmetry energy Esym(\ensuremathρ) around (2)/(3) of the saturation density \ensuremathρ0 of nuclear matter. Existing neutron skin data mostly from hadronic observables suffer from large uncertainties and their extraction from experiments are often strongly model dependent. While waiting eagerly for the promised model-independent and high-precision neutron skin data for 208Pb and 48Ca from the parity-violating electron scattering experiments (PREX-II and CREX at JLab as well as MREX at MESA), within the Bayesian statistical framework using the Skyrme-Hartree-Fock model we infer the posterior probability distribution functions (PDFs) of the slope parameter L of the nuclear symmetry energy at \ensuremathρ0 from imagined \mathrm\ensuremathΔrnp(208Pb)=0.15, 0.20, and 0.30 fm with a 1\ensuremathσ error bar of 0.02, 0.04, and 0.06 fm, respectively, as well as \mathrm\ensuremathΔrnp(48Ca)=0.12, 0.15, and 0.25 fm with a 1\ensuremathσ error bar of 0.01 and 0.02 fm, respectively. The results are compared with the PDFs of L inferred using the same approach from the available \mathrm\ensuremathΔrnp data for 116,118,120,122,124,130,132Sn from hadronic probes. They are also compared with results from a recent Bayesian analysis of the radius and tidal deformability data of canonical neutron stars from GW170817 and NICER. The neutron skin data for Sn isotopes gives L=45.5_\ensuremath-21.6+26.5 MeV surrounding its mean value or L=53.4_\ensuremath-29.5+18.6 MeV surrounding its maximum a posteriori value, respectively, with the latter smaller than but consistent with the L=66_\ensuremath-20+12 MeV from the neutron star data within their 68% confidence intervals. We found that \mathrm\ensuremathΔrnp=0.17--0.18 fm in 208Pb with an error bar of about 0.02 fm leads to a PDF of L compatible with that from analyzing the Sn data. To provide additionally useful information on L extracted from the \mathrm\ensuremathΔrnp of Sn isotopes, the experimental error bar of \mathrm\ensuremathΔrnp in 208Pb should be at least smaller than 0.06 fm aimed by some current experiments. In addition, the \mathrm\ensuremathΔrnp(48Ca) needs to be larger than 0.15 fm but smaller than 0.25 fm to be compatible with the Sn and/or neutron star results. To further improve our current knowledge about L and distinguish its PDFs in the examples considered, even higher precisions leading to significantly less than \ifmmode±\else\textpm\fi20\phantom\rule0.28em0exMeV error bars for L at 68% confidence level are necessary.

Citations