Prediction of the 1st excitation energy of odd–odd nuclei with the Bayesian neural network approach Article Swipe
Tianjiao Gao
,
Haodi Wang
,
Jingbin Lu
,
Yi Lu
,
Pei-Yao Yang
,
Mengmeng Qin
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1088/1361-6471/ad5196
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1088/1361-6471/ad5196
A Bayesian neural network (BNN) is developed to predict the 1st excitation energy of odd–odd nuclei. Aside from the proton number and neutron number, we introduce two empirical physical quantities into the input layer. is introduced to distinguish even–even, odd–odd and odd-A nuclei; and the so-called Casten factor is introduced to stand for collectivity. The BNN is trained with an experimental dataset of the 1st excitation energy for 434 odd–odd, 649 even–even and 1050 odd-A nuclei. After training, the BNN predicts the 1st excitation energy of odd–odd nuclei with a rms of 0.21 MeV. Examples of Dy, Gd, Eu and Cs isotopes are also shown. The BNN results show moderate predictive ability, in comparison with results from the projected Hartree–Fock method.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1361-6471/ad5196
- https://iopscience.iop.org/article/10.1088/1361-6471/ad5196/pdf
- OA Status
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- References
- 21
- Related Works
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- OpenAlex ID
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https://openalex.org/W4399119307Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1088/1361-6471/ad5196Digital Object Identifier
- Title
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Prediction of the 1st excitation energy of odd–odd nuclei with the Bayesian neural network approachWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-05-29Full publication date if available
- Authors
-
Tianjiao Gao, Haodi Wang, Jingbin Lu, Yi Lu, Pei-Yao Yang, Mengmeng QinList of authors in order
- Landing page
-
https://doi.org/10.1088/1361-6471/ad5196Publisher landing page
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https://iopscience.iop.org/article/10.1088/1361-6471/ad5196/pdfDirect link to full text PDF
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hybridOpen access status per OpenAlex
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https://iopscience.iop.org/article/10.1088/1361-6471/ad5196/pdfDirect OA link when available
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Artificial neural network, Excitation, Bayesian probability, Computer science, Physics, Statistical physics, Artificial intelligence, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.Casten | 93 |
| abstract_inverted_index.energy | 13, 161, 179 |
| abstract_inverted_index.factor | 94 |
| abstract_inverted_index.layer. | 34 |
| abstract_inverted_index.neural | 3 |
| abstract_inverted_index.nuclei | 182 |
| abstract_inverted_index.number | 21 |
| abstract_inverted_index.proton | 20 |
| abstract_inverted_index.shown. | 199 |
| abstract_inverted_index.<mml:mo | 40, 73, 76 |
| abstract_inverted_index.dataset | 156 |
| abstract_inverted_index.method. | 215 |
| abstract_inverted_index.network | 4 |
| abstract_inverted_index.neutron | 23 |
| abstract_inverted_index.nuclei. | 16, 170 |
| abstract_inverted_index.nuclei; | 89 |
| abstract_inverted_index.number, | 24 |
| abstract_inverted_index.predict | 9 |
| abstract_inverted_index.results | 202, 210 |
| abstract_inverted_index.trained | 152 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Bayesian | 2 |
| abstract_inverted_index.Examples | 189 |
| abstract_inverted_index.ability, | 206 |
| abstract_inverted_index.isotopes | 196 |
| abstract_inverted_index.moderate | 204 |
| abstract_inverted_index.physical | 29 |
| abstract_inverted_index.predicts | 175 |
| abstract_inverted_index.<mml:math | 35, 95 |
| abstract_inverted_index.close=")" | 45, 61 |
| abstract_inverted_index.developed | 7 |
| abstract_inverted_index.empirical | 28 |
| abstract_inverted_index.introduce | 26 |
| abstract_inverted_index.odd–odd | 15, 86, 181 |
| abstract_inverted_index.open="("> | 46, 62 |
| abstract_inverted_index.projected | 213 |
| abstract_inverted_index.so-called | 92 |
| abstract_inverted_index.training, | 172 |
| abstract_inverted_index.<mml:mrow> | 43, 47, 53, 59, 63, 69, 75, 103, 105, 108, 113, 116, 121, 123, 126, 132, 135 |
| abstract_inverted_index.<mml:msub> | 104, 112, 122, 131 |
| abstract_inverted_index.<mml:msup> | 42, 58 |
| abstract_inverted_index.comparison | 208 |
| abstract_inverted_index.excitation | 12, 160, 178 |
| abstract_inverted_index.introduced | 82, 144 |
| abstract_inverted_index.odd–odd, | 164 |
| abstract_inverted_index.predictive | 205 |
| abstract_inverted_index.quantities | 30 |
| abstract_inverted_index.</mml:math> | 80, 142 |
| abstract_inverted_index.</mml:mrow> | 50, 52, 55, 66, 68, 71, 78, 107, 110, 115, 118, 120, 125, 128, 134, 137, 139 |
| abstract_inverted_index.</mml:msub> | 111, 119, 129, 138 |
| abstract_inverted_index.</mml:msup> | 56, 72 |
| abstract_inverted_index.<mml:mfrac> | 102 |
| abstract_inverted_index.<mml:mstyle | 100 |
| abstract_inverted_index.distinguish | 84 |
| abstract_inverted_index.even–even | 166 |
| abstract_inverted_index.</mml:mfrac> | 140 |
| abstract_inverted_index.<mml:mfenced | 44, 60 |
| abstract_inverted_index.even–even, | 85 |
| abstract_inverted_index.experimental | 155 |
| abstract_inverted_index.</mml:mstyle> | 141 |
| abstract_inverted_index.collectivity. | 148 |
| abstract_inverted_index.</mml:mfenced> | 51, 67 |
| abstract_inverted_index.Hartree–Fock | 214 |
| abstract_inverted_index.<mml:mi>N</mml:mi> | 54 |
| abstract_inverted_index.<mml:mi>P</mml:mi> | 98 |
| abstract_inverted_index.<mml:mi>Z</mml:mi> | 70 |
| abstract_inverted_index.<mml:mi>n</mml:mi> | 117, 136 |
| abstract_inverted_index.<mml:mi>p</mml:mi> | 109, 127 |
| abstract_inverted_index.<mml:mi>v</mml:mi> | 106, 114, 124, 133 |
| abstract_inverted_index.<mml:mn>1</mml:mn> | 49, 65 |
| abstract_inverted_index.<mml:mn>2</mml:mn> | 79 |
| abstract_inverted_index.<mml:mo>+</mml:mo> | 57, 130 |
| abstract_inverted_index.<mml:mo>=</mml:mo> | 39 |
| abstract_inverted_index.overflow="scroll"> | 37, 97 |
| abstract_inverted_index.<mml:mi>δ</mml:mi> | 38 |
| abstract_inverted_index.<mml:mo>−</mml:mo> | 48, 64 |
| abstract_inverted_index.<mml:mo>≡</mml:mo> | 99 |
| abstract_inverted_index.displaystyle="false"> | 101 |
| abstract_inverted_index.stretchy="true">/</mml:mo> | 77 |
| abstract_inverted_index.stretchy="false">[</mml:mo> | 41 |
| abstract_inverted_index.stretchy="false">]</mml:mo> | 74 |
| abstract_inverted_index.xmlns:mml="http://www.w3.org/1998/Math/MathML" | 36, 96 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.7200000286102295 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.0321746 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |