Nuclear Theory·nucl-th

Wednesday·September 10, 2025

10 papers—5 primary·5 cross-listed

01
Bayesian Analysis of the Neutron Star Equation of State and Model Comparison: Insights from PSR J0437+4715, PSR J0614+3329, and Other Multi-Physics Data
Sk Md Adil Imam🇨🇱 · N. K. Patra🇨🇳
We perform a comprehensive Bayesian analysis to constrain the neutron star (NS) equation of state (EoS) using a wide range of terrestrial and astrophysical data. The terrestrial inputs include quantities related to symmetric nuclear matter (SNM) and symmetry energy up to two times saturation density ( $ρ_{0} \sim$ 0.16 fm $^{- 3}$ ), derived from finite nuclei and heavy-ion collisions (HICs). The astrophysical constraints incorporate NS radii and tidal deformabilities from recent NICER observations and GW170817, respectively. We consider five different EoS models: Taylor, $n /3$ , Skyrme, RMF, and sound speed(CS), are analyzed by sequentially updating the priors with (i) $χ$ EFT based pure neutron matter, (ii) terrestrial, empirical and earlier astrophysical data, (iii) case (ii) including NICER radii of PSR J0437+4715 and J0614+3329, (iv) all data combined, and (v) excluding empirical nuclear inputs. We also perform Bayesian model comparison which favors the Skyrme model under all combined data (scenario (iv)), yielding tight constraints on symmetry energy parameters: $L_{0} = 56 \pm 3$ ~MeV, $K_{sym 0} = - 132 \pm 15$ ~MeV and also on SNM parameters: $K_{0} = 265 \pm 12$ ~MeV, $Q_{0} = - 366 \pm 43$ ~MeV. The mass-radius and mass-tidal deformability posterior distributions are also well constrained. The radius and tidal deformability of a $1.4 M_{⊙}$ neutron star are found to be $R_{1.4} = 11.85 \pm 0.11$ ~km and $Λ_{1.4} = 354 \pm 25$ , respectively.
nucl-thastro-ph.HEastro-ph.SRgr-qc+1PRD(2025)·7 citations
02
Quantum Monte Carlo calculation of $δ_{NS}$ in $^{10}$ C using an effective field theory approach
Garrett B. King🇺🇸 · Joseph Carlson🇺🇸 · Abraham R. Flores🇺🇸 · Stefano Gandolfi🇺🇸 · Emanuele Mereghetti🇺🇸 · Saori Pastore🇺🇸 · Maria Piarulli🇺🇸 · Robert B. Wiringa🇺🇸
We compute radiative corrections to the superallowed $β$ decay of $^{10} C$ in an effective field theory approach using nuclear matrix elements obtained from quantum Monte Carlo calculations. These corrections are an important ingredient in the extraction of the Cabibbo-Kobayashi-Masakawa quark mixing matrix element $V_{u d}$ , and the role of this work is to illuminate the uncertainties arising from nuclear structure. Our results provide good agreement with both the traditional extraction of $V_{u d}$ , as well as with a more recent evaluation performed using the no-core shell model and a dispersion formalism. The dominant uncertainty in this approach is the presence of two unknown low-energy constants that enter into the relevant nuclear matrix elements. Future determinations of these low-energy constants -- either from QCD or modeling them with two nucleon amplitudes -- would improve the precision of the extraction in this formalism.
nucl-thPRC(2026)·10 citations
03
$K^{*} (892)$ Resonance Suppression in Ar+Sc Collisions at SPS Energies
Amine Chabane🇩🇪 · Tom Reichert🇩🇪 · Jan Steinheimer🇩🇪 · Marcus Bleicher🇩🇪
We investigate the production and suppression of short-lived $K^{*} (892)$ resonances in p+p and Ar+Sc collisions at CERN-SPS energies ( $s_{NN} =$ 8.8, 11.9, and 16.8~GeV) using the Ultra-relativistic Quantum Molecular Dynamics (UrQMD) model. We present multiplicities, rapidity and transverse momentum distributions, and analyze the $K^{*} / K$ yield ratios as a function of energy and centrality. We further estimate the time interval between chemical and kinetic freeze-out using the experimental method. A detailed comparison with recent NA61/SHINE data demonstrates that the UrQMD model captures the essential features of resonance dynamics, although the very strong resonance suppression in central collisions observed in the data cannot be quantitatively reproduced.
nucl-thPRC(2026)·1 citation
04
$B (E 2; 2_{1}^{+} \to 0_{1}^{+})$ anomaly in $^{166}$ Os
Chen-guang Zhang🇨🇳 · Suo-chang Jin🇨🇳 · Tie Wang🇨🇳 · Tao Wang🇨🇳
Recently, the very small $B (E 2; 2_{1}^{+} \to 0_{1}^{+})$ value was found in $^{166}$ Os, which is 7(4) W.u. \textbf{and} much smaller than the values of adjacent nuclei $^{168, 170}$ Os, 74(13) W.u. and 97(9) W.u.. With the help of a new technique ``SU(3) analysis" and a new explanatory framework of the B(E2) anomaly, it was found that, the $B (E 2; 2_{1}^{+} \to 0_{1}^{+})$ anomaly really can exist. In this paper, we discuss the $B (E 2; 2_{1}^{+} \to 0_{1}^{+})$ anomaly in $^{166}$ Os for the first time. Four results are used to fit the experimental data in $^{166, 168, 170}$ Os successfully. This implies that the level-crossing or level-anticrossing explanation is more reasonable.
nucl-th0 citations
05
Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark -- A Bayesian Inverse UQ-based Approach for Data Assimilation
Christopher Brady (1) · Xu Wu (1) ((1) North Carolina State University)
The Organization for Economic Cooperation and Development (OECD) Working Party on Nuclear Criticality Safety (WPNCS) proposed a benchmark exercise to assess the performance of current nuclear data adjustment techniques applied to nonlinear applications and experiments with low correlation to applications. This work introduces Bayesian Inverse Uncertainty Quantification (IUQ) as a method for nuclear data adjustments in this benchmark, and compares IUQ to the more traditional methods of Generalized Linear Least Squares (GLLS) and Monte Carlo Bayes (MOCABA). Posterior predictions from IUQ showed agreement with GLLS and MOCABA for linear applications. When comparing GLLS, MOCABA, and IUQ posterior predictions to computed model responses using adjusted parameters, we observe that GLLS predictions fail to replicate computed response distributions for nonlinear applications, while MOCABA shows near agreement, and IUQ uses computed model responses directly. We also discuss observations on why experiments with low correlation to applications can be informative to nuclear data adjustments and identify some properties useful in selecting experiments for inclusion in nuclear data adjustment. Performance in this benchmark indicates potential for Bayesian IUQ in nuclear data adjustments.
nucl-thcs.LG0 citations

Affiliations

first authorsco-authorsvia INSPIRE

Bayesian Analysis of the Neutron Star Equation of State and Model Comparison: Insights from PSR J0437+4715, PSR J0614+3329, and Other Multi-Physics Data

Quantum Monte Carlo calculation of δNS​ in 10C using an effective field theory approach

K∗(892) Resonance Suppression in Ar+Sc Collisions at SPS Energies

B(E2;21+​→01+​) anomaly in 166Os

Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark -- A Bayesian Inverse UQ-based Approach for Data Assimilation

Affiliations

Quantum Monte Carlo calculation of $δ_{NS}$ in $^{10}$ C using an effective field theory approach

$K^{*} (892)$ Resonance Suppression in Ar+Sc Collisions at SPS Energies

$B (E 2; 2_{1}^{+} \to 0_{1}^{+})$ anomaly in $^{166}$ Os