A Data-Guided Coalescence Model for Light Nuclei and Hypernuclei: Validation and Predictions

TL;DR

This work develops a data-driven coalescence framework to predict light nuclei and hypernuclei production in relativistic heavy-ion collisions, using source radii extracted from $B_2$ (deuteron) data and measured $p$ and $\Lambda$ spectra. The approach consistently reproduces $A=3$ nuclei observables like $p_T$ spectra, yield ratios, and mean $p_T$, with Triton well described by realistic deuteron wave functions, while the hypertriton shows strong sensitivity to the assumed wave function, especially at low energies and small sources. The study highlights the potential of hypernuclear observables, particularly $^{3}_{\Lambda}\mathrm{H}$ and $S_3$, to constrain hyperon–nucleon interactions and possible three-body forces, and it emphasizes the value of low-energy, small-system data for probing hypernuclear structure. Overall, the data-guided coalescence method offers a robust link between measured spectra and the short-distance structure of light nuclei and hypernuclei, with implications for dense-matter physics and neutron-star modeling.

Abstract

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 $(t,{}^{3}\rm{He})$ and hypernuclei $({}^{3}_Λ\rm{H})$. For tritons, calculations with a Gaussian wave function reproduce experimental spectra and yield ratios across a broad collision-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.

Figures (22)

• Figure 1: Yield ratios $N_{n}/N_{p}$ (left) and $N_{\Sigma^{0}}/N_{\Lambda}$ (right) as a function of collision energy as predicted by Thermal-FIST Vovchenko:2019pjl.
• Figure 2: The RMS distance between the deuteron and the $\Lambda$ ($r_{d\Lambda}$) for the Congleton wave function using different paramterers $Q$ and $\alpha$. The white lines indicate the contours $r_{d\Lambda}$=8.2 and 10.7 fm. The red markers represent the wave functions employed in this paper.
• Figure 3: The different ${}^{3}_{\Lambda}\rm{H}$ wave functions employed in this study.
• Figure 4: Comparison of the nucleon source size extracted from deuteron $B_{2}$ data ALICE:2022veq (colored bands) and proton-proton correlation functions ALICE:2025wuy (dashed lines).
• Figure 5: Blast-wave parameters $T_{\rm{kin}}$ and $\beta$ for protons and deuterons obtained by fitting to $0-10\%$ their respective $p_{T}$ spectra from $\sqrt{s_{\rm NN}}$=3 to 200 GeV Au+Au collisions STAR:2017salSTAR:2023uxkSTAR:2019sjh. The flow profile $n$ is fixed to one in these fits.