The identification of α-clustered doorway states in 44,48,52Ti using machine learning

Sam Bailey; Tzany Kokalova; Martin Freer; Carl Wheldon; Robin Smith; Joseph Walshe; Neven Soić; Lovro Prepolec; Vedrana Tokić; Francisco Miguel Marqués; Lynda Achouri; Franck Delaunay; Marian Parlog; Quentin Deshayes; Beatriz Fernández-Dominguez; Bertrand Jacquot

doi:10.1140/epja/s10050-021-00357-3

The identification of α-clustered doorway states in ^44,48,52Ti using machine learning

Sam Bailey, Tzany Kokalova, Martin Freer, Carl Wheldon, Robin Smith, Joseph Walshe, Neven Soić, Lovro Prepolec, Vedrana Tokić, Francisco Miguel Marqués, Lynda Achouri, Franck Delaunay, Marian Parlog, Quentin Deshayes, Beatriz Fernández-Dominguez, Bertrand Jacquot

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Abstract

A novel experimental analysis method has been developed, making use of the continuous wavelet transform and machine learning to rapidly identify α-clustering in nuclei in regions of high nuclear state density. This technique was applied to resonant scattering measurements of the ⁴He(^40,44,48Ca,α) resonant reactions, allowing the α-cluster structure of ^44,48,52Ti to be investigated. Fragmented α-clustering was identified in ⁴⁴Ti and ⁵²Ti, while the results for ⁴⁸Ti were less conclusive, but suggest no such clustering.

Original language	English
Article number	108
Journal	The European Physical Journal A
Volume	57
Issue number	3
DOIs	https://doi.org/10.1140/epja/s10050-021-00357-3
Publication status	Published - 29 Mar 2021

Bibliographical note

Funding Information:
The authors would like to thank the STFC (Grant No. ST/J000140/1) and gratefully acknowledge that the research leading to these results has received funding from the European Union’s Seventh Framework Programme under Grant Agreement No. 262010 (ENSAR). The GANIL facility is thanked for the delivery of the beams and the beamline preparation. ECT* Trento has supported this work and this infrastructure is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824093.

Publisher Copyright:
© 2021, The Author(s).

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10.1140/epja/s10050-021-00357-3Licence: Creative Commons: Attribution (CC BY)

BaileyS2021identificationFinal published version, 1.62 MBLicence: Creative Commons: Attribution (CC BY)

Birmingham Nuclear Physics Consolidated Grant
Freer, M., Evans, P., Jones, P., Wheldon, C. & Lazzeroni, C.
SCIENCE & TECHNOLOGY FACILITIES COUNCIL
1/08/11 → 31/07/14
Project: Research Councils

Cite this

Bailey, S., Kokalova, T., Freer, M., Wheldon, C., Smith, R., Walshe, J., Soić, N., Prepolec, L., Tokić, V., Marqués, F. M., Achouri, L., Delaunay, F., Parlog, M., Deshayes, Q., Fernández-Dominguez, B., & Jacquot, B. (2021). The identification of α-clustered doorway states in ^44,48,52Ti using machine learning. The European Physical Journal A, 57(3), Article 108. https://doi.org/10.1140/epja/s10050-021-00357-3

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title = "The identification of α-clustered doorway states in 44,48,52Ti using machine learning",

abstract = "A novel experimental analysis method has been developed, making use of the continuous wavelet transform and machine learning to rapidly identify α-clustering in nuclei in regions of high nuclear state density. This technique was applied to resonant scattering measurements of the 4He(40,44,48Ca,α) resonant reactions, allowing the α-cluster structure of 44,48,52Ti to be investigated. Fragmented α-clustering was identified in 44Ti and 52Ti, while the results for 48Ti were less conclusive, but suggest no such clustering.",

author = "Sam Bailey and Tzany Kokalova and Martin Freer and Carl Wheldon and Robin Smith and Joseph Walshe and Neven Soi{\'c} and Lovro Prepolec and Vedrana Toki{\'c} and Marqu{\'e}s, {Francisco Miguel} and Lynda Achouri and Franck Delaunay and Marian Parlog and Quentin Deshayes and Beatriz Fern{\'a}ndez-Dominguez and Bertrand Jacquot",

note = "Funding Information: The authors would like to thank the STFC (Grant No. ST/J000140/1) and gratefully acknowledge that the research leading to these results has received funding from the European Union{\textquoteright}s Seventh Framework Programme under Grant Agreement No. 262010 (ENSAR). The GANIL facility is thanked for the delivery of the beams and the beamline preparation. ECT* Trento has supported this work and this infrastructure is part of a project that has received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement No 824093. Publisher Copyright: {\textcopyright} 2021, The Author(s).",

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doi = "10.1140/epja/s10050-021-00357-3",

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Bailey, S, Kokalova, T , Freer, M , Wheldon, C, Smith, R, Walshe, J, Soić, N, Prepolec, L, Tokić, V, Marqués, FM, Achouri, L, Delaunay, F, Parlog, M, Deshayes, Q, Fernández-Dominguez, B & Jacquot, B 2021, 'The identification of α-clustered doorway states in ^44,48,52Ti using machine learning', The European Physical Journal A, vol. 57, no. 3, 108. https://doi.org/10.1140/epja/s10050-021-00357-3

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AU - Bailey, Sam

AU - Kokalova, Tzany

AU - Freer, Martin

AU - Wheldon, Carl

AU - Smith, Robin

AU - Walshe, Joseph

AU - Soić, Neven

AU - Prepolec, Lovro

AU - Tokić, Vedrana

AU - Marqués, Francisco Miguel

AU - Achouri, Lynda

AU - Delaunay, Franck

AU - Parlog, Marian

AU - Deshayes, Quentin

AU - Fernández-Dominguez, Beatriz

AU - Jacquot, Bertrand

N1 - Funding Information: The authors would like to thank the STFC (Grant No. ST/J000140/1) and gratefully acknowledge that the research leading to these results has received funding from the European Union’s Seventh Framework Programme under Grant Agreement No. 262010 (ENSAR). The GANIL facility is thanked for the delivery of the beams and the beamline preparation. ECT* Trento has supported this work and this infrastructure is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824093. Publisher Copyright: © 2021, The Author(s).

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Y1 - 2021/3/29

N2 - A novel experimental analysis method has been developed, making use of the continuous wavelet transform and machine learning to rapidly identify α-clustering in nuclei in regions of high nuclear state density. This technique was applied to resonant scattering measurements of the 4He(40,44,48Ca,α) resonant reactions, allowing the α-cluster structure of 44,48,52Ti to be investigated. Fragmented α-clustering was identified in 44Ti and 52Ti, while the results for 48Ti were less conclusive, but suggest no such clustering.

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JF - The European Physical Journal A

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ER -

The identification of α-clustered doorway states in 44,48,52Ti using machine learning

Abstract

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Birmingham Nuclear Physics Consolidated Grant

Cite this

The identification of α-clustered doorway states in ^44,48,52Ti using machine learning