Improvement to the gross theory of 
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 decay by inclusion of change in parity

Koura, Hiroyuki; Chiba, Satoshi

doi:10.1103/physrevc.95.064304

Cited by 18 publications

(8 citation statements)

References 12 publications

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“…There are mainly four kinds of theoretical models for predicting nuclear β-decay half-lives, i.e. the empirical formula [19][20][21], the gross theory (GT) [22][23][24][25], the quasiparticle random-phase approximation (QRPA) approach [26][27][28][29][30], and the shell model [3,[31][32][33]. The shell model has been successfully applied to the light nuclei and the nuclei near magic numbers, but its calculations for medium and heavy nuclei far from the magic numbers are not feasible due to the limitations of large configuration spaces.…”

Section: Introductionmentioning

confidence: 99%

Comparative study of neural network and model averaging methods in nuclear β-decay half-life predictions

Li 李,

Zhang 张,

Niu 牛

et al. 2023

J. Phys. G: Nucl. Part. Phys.

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Nuclear $\beta$-decay half-lives are investigated using the two-hidden-layer neural network and compared with the model averaging method. By carefully designing the input and hidden layers of the neural network, the neural network achieves better accuracy of nuclear $\beta$-decay half-life predictions and well eliminates the too strong odd-even staggering predicted by the previous neural networks. For nuclei with half-lives less than $1$ second, the neural network can describe experimental half-lives within $1.6$ times. The half-life predictions of the neural network are further tested with the newly measured half-lives, demonstrating its reliable extrapolation ability not far from the training region. Compared to the model averaging method, the neural network has higher accuracy and smaller uncertainties of half-life predictions in the known region. When extrapolated to the unknown region, the half-life uncertainties of the neural network are still smaller than those of the model averaging method within about $5 - 10$ steps for nuclei with $35 \lesssim Z \lesssim 90$, while the model averaging method has smaller half-life uncertainties for nuclei near the drip line.

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Section: Introductionmentioning

confidence: 99%

Comparative study of neural network and model averaging methods in nuclear β-decay half-life predictions

Li 李,

Zhang 张,

Niu 牛

et al. 2023

J. Phys. G: Nucl. Part. Phys.

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“…Although the measurements of -decay half-lives have made great progress in recent years [16,17], many neutron-rich nuclei related to the r-process still cannot be reached by present or even next-generation experimental facilities, so theoretical predictions are essential to r-process simulations. Many approaches have been developed to study nuclear -decay half-lives, including the gross theory [18][19][20] and the shell model [21]. Moreover, quasiparticle random-phase approximation (QRPA) approaches based on the finiterange droplet model (FRDM) [22][23][24], density functional theory (DFT) [25][26][27], and covariant DFT [28][29][30][31][32] have also been widely employed to predict nuclear -decay half-lives.…”

Section: Introduction β β βmentioning

confidence: 99%

Exploring the uncertainties in theoretical predictions of nuclear β-decay half-lives *

Shi¹,

Fang²,

Niu³

2021

Chinese Phys. C

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Nuclear -decay half-lives are predicted based on an empirical formula and the mass predictions from various nuclear models. It is found that the empirical formula can reproduce the nuclear -decay half-lives well, especially for short-lived nuclei with s. The theoretical half-life uncertainties from -decay energies and the parameters of the empirical formula are further investigated. It is found that the uncertainties of the half-lives are relatively large for heavy nuclei and nuclei near the neutron-drip line. For nuclei on the r-process path, the uncertainties for those with are about one order of magnitude, which are much larger than the uncertainties for those with and . However, theoretical uncertainties from the parameters of the empirical formula are relatively small for the nuclei on the r-process path, which indicates that the empirical formula is very suitable for predicting the -decay half-lives in r-process simulations.

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“…Many theoretical efforts have also been paid to systematically calculate β-decay half-lives such as by FRDM [14], FRDM-QRPA [15], HFB-QRPA [16], DFT-QRPA [17,18], and the gross theory [19]. Recently, further sophisticated methods were introduced into the systematic β-decay studies by introducing the FAM-QRPA [20] and by the relativistic CDFT-QRPA [21].…”

Section: Introductionmentioning

confidence: 99%

Gamow-Teller transitions of neutron-rich $N=82,81$ nuclei by shell-model calculations

Shimizu,

Togashi,

Utsuno

2021

Preprint

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β-decay half-lives of neutron-rich nuclei around N = 82 are key data to understand the r-process nucleosynthesis. We performed large-scale shell-model calculations in this region using a newly constructed shell-model Hamiltonian, and successfully described the low-lying spectra and half-lives of neutron-rich N = 82 and N = 81 isotones with Z = 42 − 49 in a unified way. We found that their Gamow-Teller strength distributions have a peak in the low-excitation energies, which significantly contributes to the half-lives. This peak, dominated by ν0g 7/2 → π0g 9/2 transitions, is enhanced on the proton deficient side because the Pauli-blocking effect caused by occupying the valence proton 0g 9/2 orbit is weakened.

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Improvement to the gross theory of β decay by inclusion of change in parity

Cited by 18 publications

References 12 publications

Comparative study of neural network and model averaging methods in nuclear β-decay half-life predictions

Comparative study of neural network and model averaging methods in nuclear β-decay half-life predictions

Exploring the uncertainties in theoretical predictions of nuclear β-decay half-lives *

Gamow-Teller transitions of neutron-rich $N=82,81$ nuclei by shell-model calculations

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