Nuclear Theory·nucl-th

Monday·July 26, 2021

6 papers—5 primary·1 cross-listed

01
[Submitted on 23 Jul 2021]
Bayesian uncertainty quantification for nuclear matter incompressibility
Jun Xu · Zhen Zhang · Bao-An Li
Within a Bayesian statistical framework using the standard Skyrme-Hartree-Fock model, the maximum {\it a posteriori} (MAP) values and uncertainties of nuclear matter incompressibility and isovector interaction parameters are inferred from the experimental data of giant resonances and neutron-skin thicknesses of typical heavy nuclei. With the uncertainties of the isovector interaction parameters constrained by the data of the isovector giant dipole resonance and the neutron-skin thickness, we have obtained $K_{0} = 22 3_{- 8}^{+ 7}$ MeV at 68% confidence level using the data of the isoscalar giant monopole resonance in $^{208}$ Pb measured at the Research Center for Nuclear Physics (RCNP), Japan, and at the Texas A&M University (TAMU), USA. Although the corresponding $^{120}$ Sn data gives a MAP value for $K_{0}$ about 5 MeV smaller than the $^{208}$ Pb data, there are significant overlaps in their posterior probability distribution functions.
Comments:
7 pages, 4 figures
Subjects:
Nuclear Theory (nucl-th); Nuclear Experiment (nucl-ex)
arXiv:
2107.10962 [pdf]
PRC(2021)·29 citations
02
[Submitted on 23 Jul 2021]
Finding signatures of the nuclear symmetry energy in heavy-ion collisions with deep learning
Yongjia Wang🇨🇳 · Fupeng Li🇨🇳 · Qingfeng Li🇨🇳 · Hongliang Lü🇨🇳 · Kai Zhou🇩🇪
A deep convolutional neural network (CNN) is developed to study symmetry energy $E_{sym} (ρ)$ effects by learning the mapping between the symmetry energy and the two-dimensional (transverse momentum and rapidity) distributions of protons and neutrons in heavy-ion collisions. Supervised training is performed with labelled data-set from the ultrarelativistic quantum molecular dynamics (UrQMD) model simulation. It is found that, by using proton spectra on event-by-event basis as input, the accuracy for classifying the soft and stiff $E_{sym} (ρ)$ is about 60% due to large event-by-event fluctuations, while by setting event-summed proton spectra as input, the classification accuracy increases to 98%. The accuracy for 5-label (5 different $E_{sym} (ρ)$ ) classification task are about 58% and 72% by using proton and neutron spectra, respectively. For the regression task, the mean absolute error (MAE) which measures the average magnitude of the absolute differences between the predicted and actual $L$ (the slope parameter of $E_{sym} (ρ)$ ) are about 20.4 and 14.8 MeV by using proton and neutron spectra, respectively. Fingerprints of the density-dependent nuclear symmetry energy on the transverse momentum and rapidity distributions of protons and neutrons can be identified by convolutional neural network algorithm.
Comments:
6 pages, 7 figures
Subjects:
Nuclear Theory (nucl-th); Nuclear Experiment (nucl-ex)
arXiv:
2107.11012 [pdf]
PLB(2021)·24 citations
03
[Submitted on 23 Jul 2021]
Opening angle and dineutron correlations in knockout reactions with Borromean two-neutron halo nuclei
J. Casal · M. Gómez-Ramos
Background. Knockout reactions with proton targets provide an invaluable tool to access the properties of two-neutron halo nuclei. Recently, experimental results for the average opening angle as a function of the intrinsic neutron momentum in 11Li have shown a localization of dineutron correlations on the nucleus surface. Purpose. Study the model dependence and the effect of distortion and absorption on the opening angle distributions to assess the reliability of this observable to extract properties of Borromean two-neutron halo nuclei. Method. A quasifree sudden model is used to describe the knockout process, where absorption effects are modeled by the eikonal S-matrix between the proton target and the core of the Borromean nucleus. Final states in momentum space are built within a three-body model for the projectile, which enables the description of momenta and opening angle distributions. Results. A strong dependence on absorption effects is found for the opening angle at large intrinsic momenta, while the region of lower momenta is mostly insensitive to them. Reasonable agreement with the available data is obtained for 11Li at low momenta with weights for s and p waves different from those previously reported, showing a model dependence in their extraction. For 19B, test calculations show marked sensitivity to small p-wave components. Conclusions. The opening angle for (p,pn) knockout reactions on Borromean nuclei at small intrinsic momenta is a reliable observable mostly sensitive to the structure of the Borromean nucleus. For larger momenta, the reaction mechanism leads to a larger distortion of the distribution. In the case of nuclei with small components of opposite parity to the dominant ones, this observable can be used to explore them. The relation between dineutron in coordinate space and opening angle in momentum space is found to be model-dependent.
Comments:
14 pages, 14 figures
Subjects:
Nuclear Theory (nucl-th); Nuclear Experiment (nucl-ex)
arXiv:
2107.11081 [pdf]
PRC(2021)·12 citations
04
[Submitted on 16 Jul 2021]
Calculation of kinetic parameters $β_{eff}$ and $Λ$ with modified open source Monte Carlo code OpenMC(TD)
Jaime Romero-Barrientos · Jose Ignacio Marquez Damian · Francisco Molina · Marcelo Zambra · Pablo Aguilera · Franco Lopez-Usquiano · Byron Parra
This work presents the methodology used to expand the capabilities of the Monte Carlo code OpenMC for the calculation of reactor kinetic parameters: effective delayed neutron fraction $β_{eff}$ and neutron generation time $Λ$ . The modified code, OpenMC(Time-Dependent) or OpenMC(TD), was then used to calculate the effective delayed neutron fraction by using the prompt method, while the neutron generation time was estimated using the pulsed method, fitting $Λ$ to the decay of the neutron population. OpenMC(TD) is intended to serve as an alternative for the estimation of kinetic parameters when licensed codes are not available. The results obtained are compared to experimental data and MCNP calculated values for $18$ benchmark configurations.
Comments:
7 pages with 2 figures
Subjects:
Nuclear Theory (nucl-th)
arXiv:
2107.11197 [pdf]
0 citations
05
[Submitted on 10 Jul 2021]
Matrix Model: Emergence of a Quantum Number in the Strong Coupling Regime
Castaly Fan · Larry Zamick
We continue here to study simple matrix models of quantum mechanical Hamiltonians. The eigenvalues and eigenfunctions were associated energy levels and wave functions. Whereas previously we considered the weak coupling limits of our models, we here address the more difficult strong coupling limits. We find that the wave functions fall into 2 classes and we can assign a quantum number to distinguish them. Implications for transition rates are also discussed.
Comments:
This paper has been accepted by IJMPE ( as can be seen on their website) and given the doi number below
Subjects:
Nuclear Theory (nucl-th); Nuclear Experiment (nucl-ex)
arXiv:
2107.11200 [pdf]
IJMPE(2021)·1 citation

Affiliations

first authorsco-authorsvia INSPIRE

Bayesian uncertainty quantification for nuclear matter incompressibility

Finding signatures of the nuclear symmetry energy in heavy-ion collisions with deep learning

Opening angle and dineutron correlations in knockout reactions with Borromean two-neutron halo nuclei

Calculation of kinetic parameters βeff​ and Λ with modified open source Monte Carlo code OpenMC(TD)

Matrix Model: Emergence of a Quantum Number in the Strong Coupling Regime

Affiliations

Calculation of kinetic parameters $β_{eff}$ and $Λ$ with modified open source Monte Carlo code OpenMC(TD)