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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2312.07031 |
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| _version_ | 1866917569988919296 |
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| author | Qiu, Mengying Cai, Bao-Jun Chen, Lie-Wen Yuan, Cen-Xi Zhang, Zhen |
| author_facet | Qiu, Mengying Cai, Bao-Jun Chen, Lie-Wen Yuan, Cen-Xi Zhang, Zhen |
| contents | The data-driven Bayesian model averaging is a rigorous statistical approach to combining multiple models for a unified prediction. Compared with the individual model, it provides more reliable information, especially for problems involving apparent model dependence. In this work, within both the non-relativistic Skyrme energy density functional and the nonlinear relativistic mean field model, the effective proton-neutron chemical potential difference $Δμ^*_{\rm{pn}}$ of neutron-rich nuclei is found to be strongly sensitive to the symmetry energy $E_{\rm{sym}}(ρ)$ around $2ρ_0/3$, with $ρ_0$ being the nuclear saturation density. Given discrepancies on the $Δμ^*_{\rm{pn}}$-$E_{\rm{sym}}(2ρ_0/3)$ correlations between the two models, we carry out a Bayesian model averaging analysis based on Gaussian process emulators to extract the symmetry energy around $2ρ_0/3$ from the measured $Δμ^*_{\rm{pn}}$ of 5 doubly magic nuclei $^{48}$Ca, $^{68}$Ni, $^{88}$Sr, $^{132}$Sn and $^{208}$Pb. Specifically, the $E_{\mathrm{sym}}(2ρ_0/3)$ is inferred to be $E_{\mathrm{sym}}(2ρ_0/3) = 25.6_{-1.3}^{+1.4}\,\mathrm{MeV}$ at $1σ$ confidence level. The obtained constraints on the $E_{\mathrm{sym}}(ρ)$ around $2ρ_0/3$ agree well with microscopic predictions and results from other isovector indicators. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_07031 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Bayesian model averaging for nuclear symmetry energy from effective proton-neutron chemical potential difference of neutron-rich nuclei Qiu, Mengying Cai, Bao-Jun Chen, Lie-Wen Yuan, Cen-Xi Zhang, Zhen Nuclear Theory The data-driven Bayesian model averaging is a rigorous statistical approach to combining multiple models for a unified prediction. Compared with the individual model, it provides more reliable information, especially for problems involving apparent model dependence. In this work, within both the non-relativistic Skyrme energy density functional and the nonlinear relativistic mean field model, the effective proton-neutron chemical potential difference $Δμ^*_{\rm{pn}}$ of neutron-rich nuclei is found to be strongly sensitive to the symmetry energy $E_{\rm{sym}}(ρ)$ around $2ρ_0/3$, with $ρ_0$ being the nuclear saturation density. Given discrepancies on the $Δμ^*_{\rm{pn}}$-$E_{\rm{sym}}(2ρ_0/3)$ correlations between the two models, we carry out a Bayesian model averaging analysis based on Gaussian process emulators to extract the symmetry energy around $2ρ_0/3$ from the measured $Δμ^*_{\rm{pn}}$ of 5 doubly magic nuclei $^{48}$Ca, $^{68}$Ni, $^{88}$Sr, $^{132}$Sn and $^{208}$Pb. Specifically, the $E_{\mathrm{sym}}(2ρ_0/3)$ is inferred to be $E_{\mathrm{sym}}(2ρ_0/3) = 25.6_{-1.3}^{+1.4}\,\mathrm{MeV}$ at $1σ$ confidence level. The obtained constraints on the $E_{\mathrm{sym}}(ρ)$ around $2ρ_0/3$ agree well with microscopic predictions and results from other isovector indicators. |
| title | Bayesian model averaging for nuclear symmetry energy from effective proton-neutron chemical potential difference of neutron-rich nuclei |
| topic | Nuclear Theory |
| url | https://arxiv.org/abs/2312.07031 |