Neutrino-induced hyperon final-state interactions as a probe of the in-medium hyperon potential
arXiv:2607.09273
Abstract
Hyperon single-particle potentials U_Y(rho) govern hyperon propagation in nuclei and the appearance of hyperons in dense matter, where they soften the neutron-star equation of state (EOS) and lower the maximum mass M_max, the hyperon puzzle. Charged-current (anti)neutrino interactions on argon-40 create Lambda and Sigma hyperons inside the nucleus. The reconstructed Lambda yield and momentum and a kaon-vetoed final-state-interaction (FSI) Sigma+ tag respond to U_Lambda and U_Sigma at SBND and DUNE energies. We write the potential at low density as U_Y = U_Y(rho_0) (rho/rho_0)^gamma, plus a correction that vanishes at saturation. A detector-level Fisher forecast, with production cross sections, fluxes and efficiencies as nuisance parameters and the muon kinematics calibrating the production model, determines U_Lambda best at rho* = 0.82 rho_0, independently of gamma. The statistical precision is 1.5 MeV; with the production model profiled and the remaining systematic uncertainties added in quadrature, the total is +-31 MeV, of which the largest item, 18 MeV, is the convention by which the cascade applies the potential. The measurement is a check, with different systematics, of the hypernuclear constraint, +-3.3 MeV at rho*. U_Sigma is not constrained. In relativistic mean-field EOSs anchored to hypernuclear and Sigma-atom depths, M_max for n p Lambda Sigma- matter is 1.94 M_sun for GM1 and 2.03 M_sun for FSU2H with the phi meson; it depends on a high-density Lambda NN term c_Lambda that the neutrino data do not constrain. The calculations use the StrangeMC Monte Carlo generator.
arXiv comment31 pages, 22 figures, 23 tables. v2: revised version resubmitted to Phys. Rev. D, new title; corrected the antineutrino quasi-elastic cross section (sign of the V-A interference term); forecast with production cross sections, fluxes, and efficiencies as nuisance parameters, plus a systematic budget from full simulation regenerations