Abstract

Three-body nuclear forces play an important role in the structure of nuclei and hypernuclei and are also incorporated in models to describe the dynamics of dense baryonic matter, such as in neutron stars. So far, only indirect measurements anchored to the binding energies of nuclei can be used to constrain the three-nucleon force, and if hyperons are considered, the scarce data on hypernuclei impose only weak constraints on the three-body forces. In this work, we present the first direct measurement of the p$-$p$-$p and p$-$p$-\Lambda$ systems in terms of three-particle mixed moments carried out for pp collisions at $\sqrt{s}$ = 13 TeV. Three-particle cumulants are extracted from the normalised mixed moments by applying the Kubo formalism, where the three-particle interaction contribution to these moments can be isolated after subtracting the known two-body interaction terms. A negative cumulant is found for the p$-$p$-$p system, hinting to the presence of a residual three-body effect while for p$-$p$-\Lambda$ the cumulant is consistent with zero. This measurement demonstrates the accessibility of three-baryon correlations at the LHC.

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Figure 1 a)

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The (p-p)-p correlation function obtained using the data-driven approach
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Figure 1 b)

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The (p-p)-$\Lambda$ correlation function obtained using the data-driven approach
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Figure 1 c)

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The p-(p-$\Lambda$) correlation function obtained using the data-driven approach
Table 4

Figure 3 (left panel)

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Measured p-p-p three-particle correlation function
Table 5

Figure 3 (right panel)

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Measured p-p-$\Lambda$ three-particle correlation function
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Figure 4 (left panel)

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p-p-p cumulant
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Figure 4 (left panel)

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p-p-$\mathrm{\overline{p}}$ cumulant
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Figure 4 (right panel)

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p-p-$\Lambda$ cumulant
Table 9

Figure B.1 a)

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Measured p-p-$\mathrm{\overline{p}}$ three-particle correlation function
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Figure B.1 b)

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The (p-p)-$\mathrm{\overline{p}}$ correlation function obtained using the data-driven approach
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Figure B.1 c)

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The p-(p-$\mathrm{\overline{p}}$) correlation function obtained using the data-driven approach

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