Quantifying resonance behavior in the fusion of 
<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mmultiscripts><mml:mi mathvariant="normal">O</mml:mi><mml:mprescripts /><mml:none /><mml:mn>17</mml:mn></mml:mmultiscripts></mml:math>
 with 
<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mmultiscripts><mml:mi mathvariant="normal">C</mml:mi><mml:mprescripts /><mml:none /><mml:mn>12</mml:mn></mml:mmultiscripts></mml:math>
 at above-barrier energies

Hudan, S.; Johnstone, J. E.; Kumar, Rohit; deSouza, Romualdo; Allen, J.; Bardayan, D. W.; Blankstein, D.; Boomershine, C.; Carmichael, Stephen W.; Clark, Adam M.; Coil, S.; Henderson, S. L.; O’Malley, P. D.; Seeger, W. W. von

doi:10.1103/physrevc.107.064612

Phys. Rev. C

2023

DOI: 10.1103/physrevc.107.064612

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Quantifying resonance behavior in the fusion of O17 with C12 at above-barrier energies

S. Hudan

J. E. Johnstone

Rohit Kumar

et al.

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2024

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Cited by 3 publications

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Barrier distribution extraction via Gaussian process regression

Godbey

2024

EPJ Web Conf.

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This work presents a novel method for extracting potential barrier distributions from experimental fusion cross sections. We utilize a simple Gaussian process regression (GPR) framework to model the observed cross sections as a function of energy for three nuclear systems. The GPR approach offers a flexible way to represent the experimental data, accommodating potentially complex behavior without introducing strong prior assumptions. This method is applied directly to experimental data and is compared to the traditional direct extraction technique. We discuss the advantages of GPR-based barrier distribution extraction, including the capability to quantify uncertainties and robustness to noise in the experimental data.

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Barrier distribution extraction via Gaussian process regression

Godbey

2024

EPJ Web Conf.

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Influence of additional neutrons on the fusion cross section beyond the N=8 shell

Hudan,

Desilets,

Kumar

et al. 2024

Phys. Rev. C

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Search for beyond-mean-field signatures in heavy-ion fusion reactions

deSouza,

Godbey,

Hudan

et al. 2024

Phys. Rev. C

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Quantifying resonance behavior in the fusion of O17 with C12 at above-barrier energies

Cited by 3 publications

References 22 publications

Barrier distribution extraction via Gaussian process regression

Barrier distribution extraction via Gaussian process regression

Influence of additional neutrons on the fusion cross section beyond the N=8 shell

Search for beyond-mean-field signatures in heavy-ion fusion reactions

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