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Data-guided coalescence model for production of light nuclei and hypernuclei in relativistic heavy-ion collisions at √𝑠𝑁⁢𝑁 = 3-200GeV

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The production of light hypernuclei in relativistic heavy-ion collisions provides a unique opportunity to probe hyperon-nucleon interactions and possible three-body forces, which are central to the resolution of the hyperon puzzle in neutron star matter. In this work, we develop a data-guided coales...

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Bibliographic Details
Main Authors: Leung, Yue (Author) , Zhou, Yingjie (Author) , Herrmann, Norbert (Author)
Format: Article (Journal)
Language:English
Published: 13 March, 2026
In: Physical review
Year: 2026, Volume: 113, Issue: 3, Pages: 1-19
ISSN:2469-9993
DOI:10.1103/9m2b-99x4
Online Access:Resolving-System, lizenzpflichtig, Volltext: https://doi.org/10.1103/9m2b-99x4
Verlag, lizenzpflichtig, Volltext: https://link.aps.org/doi/10.1103/9m2b-99x4
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Author Notes:Yue Hang Leung, Yingjie Zhou, and Norbert Herrmann
Description
Summary:The production of light hypernuclei in relativistic heavy-ion collisions provides a unique opportunity to probe hyperon-nucleon interactions and possible three-body forces, which are central to the resolution of the hyperon puzzle in neutron star matter. In this work, we develop a data-guided coalescence framework in which the source size is extracted from proton and deuteron yields and used, together with measured proton and Λ spectra, to predict the production of 𝐴=3 nuclei (𝑡,3He) and hypernuclei (3Λ⁢H) in √𝑠𝑁⁢𝑁=3-200GeV Au+Au collisions. For tritons, calculations with a Gaussian wave function reproduce experimental spectra and yield ratios across this energy range. For the hypertriton, the model predictions are highly sensitive to the assumed wave function. This sensitivity is strongest at low collision energies and in low-multiplicity environments, implying that such conditions are particularly valuable for probing hypernuclear structure.
Item Description:Im Titel steht sNN unter dem Wurzelsymbol, NN ist dabei tiefgestellt
Gesehen am 02.06.2026
Physical Description:Online Resource
ISSN:2469-9993
DOI:10.1103/9m2b-99x4

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