Wed·Oct 4, 2023Wednesday·October 4, 2023

1. 01*

   Re-evaluation of the ${}^{22}$Ne($p$,$\gamma$)${}^{23}$Na reaction rate: $R-$matrix analysis of the non-resonant capture and effect of the 8945 keV (${7/2}^{-}$) resonance strength

   Sk Mustak Ali🇮🇳 · Rajkumar Santra🇮🇳 · Sathi Sharma · Ashok kumar Mondal🇮🇳

   The ${}^{22}$Ne($p,\gamma$)${}^{23}$Na capture reaction is a key member of the Ne-Na cycle of hydrogen burning. The rate of this reaction is critical in classical novae nucleosynthesis and hot bottom burning processes (HBB) in asymptotic giant branch (AGB) stars. Despite its astrophysical importance, significant uncertainty remains in the reaction rate due to several narrow low energy resonances lying near the Gamow window. The present work revisits this reaction by examining the contribution of the 8664 keV subthreshold state and the 151 keV doublet resonance state of 7/2${}^{-}$ configuration in ${}^{23}$Na. Finite range distorted-wave Born approximation (FRDWBA) analyses of existing ${}^{22}$Ne(${}^3$He,$d$)${}^{23}$Na transfer reaction data were carried out to extract the peripheral asymptotic normalization coefficients (ANC) of the 8664 keV state. The ANC value obtained in the present work is $\sim 25\%$ higher compared to the previous work by Santra et al.~\cite{SA20}. Systematic $R$-matrix calculations were performed to obtain the non-resonant astrophysical $S$-factor utilizing the enhanced ANC value. The resonance strengths of the 8945 keV doublets were deduced from shell model calculations. The total reaction rate is found to be $\sim 15\%$ higher at temperatures relevant for the HBB processes, compared to the recent rate measured by Williams et al.~\cite{WI20}, and matches the rate by Williams et al.~\cite{WI20} at temperatures of interest for classical novae nucleosynthesis.

   ↳ nucl-thnucl-ex0 citations
2. 02*

   Real-time Signal Detection for Cyclotron Radiation Emission Spectroscopy Measurements using Antenna Arrays

   A. Ashtari Esfahani🇺🇸 · S. Böser🇩🇪 · N. Buzinsky🇺🇸 · M. C. Carmona-Benitez🇺🇸 · C. Claessens🇺🇸 · L. de Viveiros🇺🇸 · M. Fertl🇩🇪 · J. A. Formaggio🇺🇸 · B. T. Foust🇺🇸 · J. K. Gaison🇺🇸 · M. Grando🇺🇸 · J. Hartse🇺🇸 and 39 other authors

   Cyclotron Radiation Emission Spectroscopy (CRES) is a technique for precision measurement of the energies of charged particles, which is being developed by the Project 8 Collaboration to measure the neutrino mass using tritium beta-decay spectroscopy. Project 8 seeks to use the CRES technique to measure the neutrino mass with a sensitivity of 40~meV, requiring a large supply of tritium atoms stored in a multi-cubic meter detector volume. Antenna arrays are one potential technology compatible with an experiment of this scale, but the capability of an antenna-based CRES experiment to measure the neutrino mass depends on the efficiency of the signal detection algorithms. In this paper, we develop efficiency models for three signal detection algorithms and compare them using simulations from a prototype antenna-based CRES experiment as a case-study. The algorithms include a power threshold, a matched filter template bank, and a neural network based machine learning approach, which are analyzed in terms of their average detection efficiency and relative computational cost. It is found that significant improvements in detection efficiency and, therefore, neutrino mass sensitivity are achievable, with only a moderate increase in computation cost, by utilizing either the matched filter or machine learning approach in place of a power threshold, which is the baseline signal detection algorithm used in previous CRES experiments by Project 8.

   ↳ physics.ins-detnucl-exJINST(2024)·4 citations

* Reconstructed cohort: no mailing for this day survives in the archive. Papers are grouped by their submission times and arXiv's announcement cut-off, assuming announcement without delay; positions follow identifier order. Validated at ~91% exact-day agreement against the archived era.