Use of Bayesian Optimization to understand the structure of nuclei

Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approa...
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Gespeichert in:

Autor*in:	Hooker, J. [verfasserIn] Kovoor, J. Jones, K.L. Kanungo, R. Alcorta, M. Allen, J. Andreoiu, C. Atar, L. Bardayan, D.W. Bhattacharjee, S.S. Blankstein, D. Burbadge, C. Burcher, S. Catford, W.N. Cha, S. Chae, K. Connolly, D. Davids, B. Esker, N. Garcia, F.H. Gillespie, S. Ghimire, R. Gula, A. Hackman, G. Hallam, S. Hellmich, M. Henderson, J. Holl, M. Jassal, P. King, S. Knight, T. Kruecken, R. Lepailleur, A. Liang, J. Morrison, L. O’Malley, P.D. Pain, S.D. Pereira-Lopez, X. Psaltis, A. Radich, A. Shotter, A.C. Vostinar, M. Williams, M. Workman, O.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022transfer abstract

Schlagwörter:	Direct reaction Transfer reaction Geant4 simulation Bayesian optimization Low-energy reactions Stable ion beam Radioactive ion beam

Umfang:	6

Übergeordnetes Werk:	Enthalten in: Editorial Comment - Unwala, Darius J. ELSEVIER, 2013, a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics, Amsterdam [u.a.]
Übergeordnetes Werk:	volume:512 ; year:2022 ; day:1 ; month:02 ; pages:6-11 ; extent:6

Links:	Volltext

DOI / URN:	10.1016/j.nimb.2021.11.014

Katalog-ID:	ELV056372167

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520			\|a Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be.
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700	1		\|a Liang, J. \|4 oth
700	1		\|a Morrison, L. \|4 oth
700	1		\|a O’Malley, P.D. \|4 oth
700	1		\|a Pain, S.D. \|4 oth
700	1		\|a Pereira-Lopez, X. \|4 oth
700	1		\|a Psaltis, A. \|4 oth
700	1		\|a Radich, A. \|4 oth
700	1		\|a Shotter, A.C. \|4 oth
700	1		\|a Vostinar, M. \|4 oth
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author_variant	j h jh
matchkey_str	hookerjkovoorjjonesklkanungoralcortamall:2022----:sobysaotmztotudrtntet
hierarchy_sort_str	2022transfer abstract
bklnumber	44.85
publishDate	2022
allfields	10.1016/j.nimb.2021.11.014 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001685.pica (DE-627)ELV056372167 (ELSEVIER)S0168-583X(21)00390-6 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.85 bkl Hooker, J. verfasserin aut Use of Bayesian Optimization to understand the structure of nuclei 2022transfer abstract 6 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be. Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be. Direct reaction Elsevier Transfer reaction Elsevier Geant4 simulation Elsevier Bayesian optimization Elsevier Low-energy reactions Elsevier Stable ion beam Elsevier Radioactive ion beam Elsevier Kovoor, J. oth Jones, K.L. oth Kanungo, R. oth Alcorta, M. oth Allen, J. oth Andreoiu, C. oth Atar, L. oth Bardayan, D.W. oth Bhattacharjee, S.S. oth Blankstein, D. oth Burbadge, C. oth Burcher, S. oth Catford, W.N. oth Cha, S. oth Chae, K. oth Connolly, D. oth Davids, B. oth Esker, N. oth Garcia, F.H. oth Gillespie, S. oth Ghimire, R. oth Gula, A. oth Hackman, G. oth Hallam, S. oth Hellmich, M. oth Henderson, J. oth Holl, M. oth Jassal, P. oth King, S. oth Knight, T. oth Kruecken, R. oth Lepailleur, A. oth Liang, J. oth Morrison, L. oth O’Malley, P.D. oth Pain, S.D. oth Pereira-Lopez, X. oth Psaltis, A. oth Radich, A. oth Shotter, A.C. oth Vostinar, M. oth Williams, M. oth Workman, O. oth Enthalten in Elsevier Unwala, Darius J. ELSEVIER Editorial Comment 2013 a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics Amsterdam [u.a.] (DE-627)ELV011304669 volume:512 year:2022 day:1 month:02 pages:6-11 extent:6 https://doi.org/10.1016/j.nimb.2021.11.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_21 GBV_ILN_22 GBV_ILN_24 GBV_ILN_40 GBV_ILN_62 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 44.85 Kardiologie Angiologie VZ AR 512 2022 1 0201 6-11 6
spelling	10.1016/j.nimb.2021.11.014 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001685.pica (DE-627)ELV056372167 (ELSEVIER)S0168-583X(21)00390-6 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.85 bkl Hooker, J. verfasserin aut Use of Bayesian Optimization to understand the structure of nuclei 2022transfer abstract 6 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be. Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be. Direct reaction Elsevier Transfer reaction Elsevier Geant4 simulation Elsevier Bayesian optimization Elsevier Low-energy reactions Elsevier Stable ion beam Elsevier Radioactive ion beam Elsevier Kovoor, J. oth Jones, K.L. oth Kanungo, R. oth Alcorta, M. oth Allen, J. oth Andreoiu, C. oth Atar, L. oth Bardayan, D.W. oth Bhattacharjee, S.S. oth Blankstein, D. oth Burbadge, C. oth Burcher, S. oth Catford, W.N. oth Cha, S. oth Chae, K. oth Connolly, D. oth Davids, B. oth Esker, N. oth Garcia, F.H. oth Gillespie, S. oth Ghimire, R. oth Gula, A. oth Hackman, G. oth Hallam, S. oth Hellmich, M. oth Henderson, J. oth Holl, M. oth Jassal, P. oth King, S. oth Knight, T. oth Kruecken, R. oth Lepailleur, A. oth Liang, J. oth Morrison, L. oth O’Malley, P.D. oth Pain, S.D. oth Pereira-Lopez, X. oth Psaltis, A. oth Radich, A. oth Shotter, A.C. oth Vostinar, M. oth Williams, M. oth Workman, O. oth Enthalten in Elsevier Unwala, Darius J. ELSEVIER Editorial Comment 2013 a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics Amsterdam [u.a.] (DE-627)ELV011304669 volume:512 year:2022 day:1 month:02 pages:6-11 extent:6 https://doi.org/10.1016/j.nimb.2021.11.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_21 GBV_ILN_22 GBV_ILN_24 GBV_ILN_40 GBV_ILN_62 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 44.85 Kardiologie Angiologie VZ AR 512 2022 1 0201 6-11 6
allfields_unstemmed	10.1016/j.nimb.2021.11.014 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001685.pica (DE-627)ELV056372167 (ELSEVIER)S0168-583X(21)00390-6 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.85 bkl Hooker, J. verfasserin aut Use of Bayesian Optimization to understand the structure of nuclei 2022transfer abstract 6 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be. Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be. Direct reaction Elsevier Transfer reaction Elsevier Geant4 simulation Elsevier Bayesian optimization Elsevier Low-energy reactions Elsevier Stable ion beam Elsevier Radioactive ion beam Elsevier Kovoor, J. oth Jones, K.L. oth Kanungo, R. oth Alcorta, M. oth Allen, J. oth Andreoiu, C. oth Atar, L. oth Bardayan, D.W. oth Bhattacharjee, S.S. oth Blankstein, D. oth Burbadge, C. oth Burcher, S. oth Catford, W.N. oth Cha, S. oth Chae, K. oth Connolly, D. oth Davids, B. oth Esker, N. oth Garcia, F.H. oth Gillespie, S. oth Ghimire, R. oth Gula, A. oth Hackman, G. oth Hallam, S. oth Hellmich, M. oth Henderson, J. oth Holl, M. oth Jassal, P. oth King, S. oth Knight, T. oth Kruecken, R. oth Lepailleur, A. oth Liang, J. oth Morrison, L. oth O’Malley, P.D. oth Pain, S.D. oth Pereira-Lopez, X. oth Psaltis, A. oth Radich, A. oth Shotter, A.C. oth Vostinar, M. oth Williams, M. oth Workman, O. oth Enthalten in Elsevier Unwala, Darius J. ELSEVIER Editorial Comment 2013 a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics Amsterdam [u.a.] (DE-627)ELV011304669 volume:512 year:2022 day:1 month:02 pages:6-11 extent:6 https://doi.org/10.1016/j.nimb.2021.11.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_21 GBV_ILN_22 GBV_ILN_24 GBV_ILN_40 GBV_ILN_62 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 44.85 Kardiologie Angiologie VZ AR 512 2022 1 0201 6-11 6
allfieldsGer	10.1016/j.nimb.2021.11.014 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001685.pica (DE-627)ELV056372167 (ELSEVIER)S0168-583X(21)00390-6 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.85 bkl Hooker, J. verfasserin aut Use of Bayesian Optimization to understand the structure of nuclei 2022transfer abstract 6 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be. Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be. Direct reaction Elsevier Transfer reaction Elsevier Geant4 simulation Elsevier Bayesian optimization Elsevier Low-energy reactions Elsevier Stable ion beam Elsevier Radioactive ion beam Elsevier Kovoor, J. oth Jones, K.L. oth Kanungo, R. oth Alcorta, M. oth Allen, J. oth Andreoiu, C. oth Atar, L. oth Bardayan, D.W. oth Bhattacharjee, S.S. oth Blankstein, D. oth Burbadge, C. oth Burcher, S. oth Catford, W.N. oth Cha, S. oth Chae, K. oth Connolly, D. oth Davids, B. oth Esker, N. oth Garcia, F.H. oth Gillespie, S. oth Ghimire, R. oth Gula, A. oth Hackman, G. oth Hallam, S. oth Hellmich, M. oth Henderson, J. oth Holl, M. oth Jassal, P. oth King, S. oth Knight, T. oth Kruecken, R. oth Lepailleur, A. oth Liang, J. oth Morrison, L. oth O’Malley, P.D. oth Pain, S.D. oth Pereira-Lopez, X. oth Psaltis, A. oth Radich, A. oth Shotter, A.C. oth Vostinar, M. oth Williams, M. oth Workman, O. oth Enthalten in Elsevier Unwala, Darius J. ELSEVIER Editorial Comment 2013 a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics Amsterdam [u.a.] (DE-627)ELV011304669 volume:512 year:2022 day:1 month:02 pages:6-11 extent:6 https://doi.org/10.1016/j.nimb.2021.11.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_21 GBV_ILN_22 GBV_ILN_24 GBV_ILN_40 GBV_ILN_62 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 44.85 Kardiologie Angiologie VZ AR 512 2022 1 0201 6-11 6
allfieldsSound	10.1016/j.nimb.2021.11.014 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001685.pica (DE-627)ELV056372167 (ELSEVIER)S0168-583X(21)00390-6 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.85 bkl Hooker, J. verfasserin aut Use of Bayesian Optimization to understand the structure of nuclei 2022transfer abstract 6 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be. Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be. Direct reaction Elsevier Transfer reaction Elsevier Geant4 simulation Elsevier Bayesian optimization Elsevier Low-energy reactions Elsevier Stable ion beam Elsevier Radioactive ion beam Elsevier Kovoor, J. oth Jones, K.L. oth Kanungo, R. oth Alcorta, M. oth Allen, J. oth Andreoiu, C. oth Atar, L. oth Bardayan, D.W. oth Bhattacharjee, S.S. oth Blankstein, D. oth Burbadge, C. oth Burcher, S. oth Catford, W.N. oth Cha, S. oth Chae, K. oth Connolly, D. oth Davids, B. oth Esker, N. oth Garcia, F.H. oth Gillespie, S. oth Ghimire, R. oth Gula, A. oth Hackman, G. oth Hallam, S. oth Hellmich, M. oth Henderson, J. oth Holl, M. oth Jassal, P. oth King, S. oth Knight, T. oth Kruecken, R. oth Lepailleur, A. oth Liang, J. oth Morrison, L. oth O’Malley, P.D. oth Pain, S.D. oth Pereira-Lopez, X. oth Psaltis, A. oth Radich, A. oth Shotter, A.C. oth Vostinar, M. oth Williams, M. oth Workman, O. oth Enthalten in Elsevier Unwala, Darius J. ELSEVIER Editorial Comment 2013 a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics Amsterdam [u.a.] (DE-627)ELV011304669 volume:512 year:2022 day:1 month:02 pages:6-11 extent:6 https://doi.org/10.1016/j.nimb.2021.11.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_21 GBV_ILN_22 GBV_ILN_24 GBV_ILN_40 GBV_ILN_62 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2007 44.85 Kardiologie Angiologie VZ AR 512 2022 1 0201 6-11 6
language	English
source	Enthalten in Editorial Comment Amsterdam [u.a.] volume:512 year:2022 day:1 month:02 pages:6-11 extent:6
sourceStr	Enthalten in Editorial Comment Amsterdam [u.a.] volume:512 year:2022 day:1 month:02 pages:6-11 extent:6
format_phy_str_mv	Article
bklname	Kardiologie Angiologie
institution	findex.gbv.de
topic_facet	Direct reaction Transfer reaction Geant4 simulation Bayesian optimization Low-energy reactions Stable ion beam Radioactive ion beam
dewey-raw	610
isfreeaccess_bool	false
container_title	Editorial Comment
authorswithroles_txt_mv	Hooker, J. @@aut@@ Kovoor, J. @@oth@@ Jones, K.L. @@oth@@ Kanungo, R. @@oth@@ Alcorta, M. @@oth@@ Allen, J. @@oth@@ Andreoiu, C. @@oth@@ Atar, L. @@oth@@ Bardayan, D.W. @@oth@@ Bhattacharjee, S.S. @@oth@@ Blankstein, D. @@oth@@ Burbadge, C. @@oth@@ Burcher, S. @@oth@@ Catford, W.N. @@oth@@ Cha, S. @@oth@@ Chae, K. @@oth@@ Connolly, D. @@oth@@ Davids, B. @@oth@@ Esker, N. @@oth@@ Garcia, F.H. @@oth@@ Gillespie, S. @@oth@@ Ghimire, R. @@oth@@ Gula, A. @@oth@@ Hackman, G. @@oth@@ Hallam, S. @@oth@@ Hellmich, M. @@oth@@ Henderson, J. @@oth@@ Holl, M. @@oth@@ Jassal, P. @@oth@@ King, S. @@oth@@ Knight, T. @@oth@@ Kruecken, R. @@oth@@ Lepailleur, A. @@oth@@ Liang, J. @@oth@@ Morrison, L. @@oth@@ O’Malley, P.D. @@oth@@ Pain, S.D. @@oth@@ Pereira-Lopez, X. @@oth@@ Psaltis, A. @@oth@@ Radich, A. @@oth@@ Shotter, A.C. @@oth@@ Vostinar, M. @@oth@@ Williams, M. @@oth@@ Workman, O. @@oth@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	ELV011304669
dewey-sort	3610
id	ELV056372167
language_de	englisch
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author	Hooker, J.
spellingShingle	Hooker, J. ddc 610 bkl 44.85 Elsevier Direct reaction Elsevier Transfer reaction Elsevier Geant4 simulation Elsevier Bayesian optimization Elsevier Low-energy reactions Elsevier Stable ion beam Elsevier Radioactive ion beam Use of Bayesian Optimization to understand the structure of nuclei
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title	Use of Bayesian Optimization to understand the structure of nuclei
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title_full	Use of Bayesian Optimization to understand the structure of nuclei
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title_sort	use of bayesian optimization to understand the structure of nuclei
title_auth	Use of Bayesian Optimization to understand the structure of nuclei
abstract	Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be.
abstractGer	Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be.
abstract_unstemmed	Monte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of simulating and fitting is often required to describe experimental data. We describe a Bayesian approach to fitting experimental data, designed for data from a 12Be(d,p) reaction measurement, using simulations made with GEANT4. Q-values from the 12C(d,p) reaction to well-known states in 13C are compared with simulations using BayesOpt. The energies of the states were not included in the simulation to reproduce the situation for 13Be where the states are poorly known. Both cases had low statistics and significant resolution broadening owing to large proton energy losses in the solid deuterium target. Excitation energies of the lowest three excited states in 13C were extracted to better than 90 keV, paving a way for extracting information on 13Be.
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title_short	Use of Bayesian Optimization to understand the structure of nuclei
url	https://doi.org/10.1016/j.nimb.2021.11.014
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author2	Kovoor, J. Jones, K.L. Kanungo, R. Alcorta, M. Allen, J. Andreoiu, C. Atar, L. Bardayan, D.W. Bhattacharjee, S.S. Blankstein, D. Burbadge, C. Burcher, S. Catford, W.N. Cha, S. Chae, K. Connolly, D. Davids, B. Esker, N. Garcia, F.H. Gillespie, S. Ghimire, R. Gula, A. Hackman, G. Hallam, S. Hellmich, M. Henderson, J. Holl, M. Jassal, P. King, S. Knight, T. Kruecken, R. Lepailleur, A. Liang, J. Morrison, L. O’Malley, P.D. Pain, S.D. Pereira-Lopez, X. Psaltis, A. Radich, A. Shotter, A.C. Vostinar, M. Williams, M. Workman, O.
author2Str	Kovoor, J. Jones, K.L. Kanungo, R. Alcorta, M. Allen, J. Andreoiu, C. Atar, L. Bardayan, D.W. Bhattacharjee, S.S. Blankstein, D. Burbadge, C. Burcher, S. Catford, W.N. Cha, S. Chae, K. Connolly, D. Davids, B. Esker, N. Garcia, F.H. Gillespie, S. Ghimire, R. Gula, A. Hackman, G. Hallam, S. Hellmich, M. Henderson, J. Holl, M. Jassal, P. King, S. Knight, T. Kruecken, R. Lepailleur, A. Liang, J. Morrison, L. O’Malley, P.D. Pain, S.D. Pereira-Lopez, X. Psaltis, A. Radich, A. Shotter, A.C. Vostinar, M. Williams, M. Workman, O.
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doi_str	10.1016/j.nimb.2021.11.014
up_date	2024-07-06T20:11:33.479Z
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