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First application of Markov Chain Monte Carlo-based Bayesian data analysis to the Doppler-Shift Attenuation Method

First application of Markov Chain Monte Carlo-based Bayesian data analysis to the Doppler-Shift Attenuation Method

来源:Arxiv_logoArxiv
英文摘要

Motivated primarily by the large uncertainties in the thermonuclear rate of the $^{30}$P$(p,\gamma)^{31}$S reaction that limit our understanding of classical novae, we carried out lifetime measurements of $^{31}$S excited states using the Doppler Shift Lifetimes (DSL) facility at the TRIUMF Isotope Separator and Accelerator (ISAC-II) facility. The $^{31}$S excited states were populated by the $^{3}$He$(^{32}$S$,\alpha)^{31}$S reaction. The deexcitation $\gamma$ rays were detected by a clover-type high-purity germanium detector in coincidence with the $\alpha$ particles detected by a silicon detector telescope. We have applied modern Markov chain Monte Carlo-based Bayesian methods to perform lineshape analyses of Doppler-shift attenuation method $\gamma$-ray data for the first time. We have determined the lifetimes of the two lowest-lying $^{31}$S excited states. First experimental upper limits on the lifetimes of four higher-lying states have been obtained. The experimental results were compared to shell-model calculations using five universal $sd$-shell Hamiltonians. Evidence for $\gamma$ rays originating from the astrophysically important $J^\pi=3/2^+$, 260-keV $^{30}$P$(p,\gamma)^{31}$S resonance has also been observed, although strong constraints on the lifetime will require better statistics.

J. Park、L. E. Weghorn、G. Hackman、P. Ruotsalainen、R. Caballero-Folch、M. Bowry、N. Esker、J. Smallcombe、C. Wrede、M. Friedman、P. Machule、B. E. Glassman、A. B. Garnsworthy、J. Measures、O. S. Kirsebom、L. Evitts、M. Moukaddam、J. Henderson、C. Fry、B. Davids、M. Williams、J. Surbrook、C. Pearson、D. Southall、C. Ruiz、S. Bhattacharjee、A. Kurkjian、J. Lighthall、D. P¨|rez-Loureiro、J. K. Smith、B. A. Brown、T. Budner、M. Alcorta、L. J. Sun

10.1016/j.physletb.2023.137801

原子能技术基础理论物理学

J. Park,L. E. Weghorn,G. Hackman,P. Ruotsalainen,R. Caballero-Folch,M. Bowry,N. Esker,J. Smallcombe,C. Wrede,M. Friedman,P. Machule,B. E. Glassman,A. B. Garnsworthy,J. Measures,O. S. Kirsebom,L. Evitts,M. Moukaddam,J. Henderson,C. Fry,B. Davids,M. Williams,J. Surbrook,C. Pearson,D. Southall,C. Ruiz,S. Bhattacharjee,A. Kurkjian,J. Lighthall,D. P¨|rez-Loureiro,J. K. Smith,B. A. Brown,T. Budner,M. Alcorta,L. J. Sun.First application of Markov Chain Monte Carlo-based Bayesian data analysis to the Doppler-Shift Attenuation Method[EB/OL].(2022-03-19)[2025-05-14].https://arxiv.org/abs/2203.10336.点此复制

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