A Seismic Solar Model Deduced from the Sound-Speed Distribution and an Estimate of the Neutrino Fluxes

Astronomy and Astrophysics – Astronomy

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Helioseismology, Neutrinos, Sun: Interior, Sun: Oscillations

Scientific paper

We have deduced the density, pressure, temperature, and hydrogen profiles in the solar interior by solving the basic equations governing the stellar structure with the imposition that the sound-speed profile is that determined by the helioseismic data of Libbrecht et al. (1990; AAA 52.080.103) and Jimenez et al. (1988; AAA 45.080.041). This approach is completely different from that of the standard solar model, and is based on more experimentally well-determined data. We solved the equations by requiring that the mass and mean molecular weight at the surface match the solar mass and a certain fixed value, respectively, as the outer boundary conditions. Together with these conditions and the appropriate inner boundary conditions, these equations were reduced to a boundary-value problem. We examined whether the luminosity at the surface matches the observed value. The error levels were estimated by a Monte-Carlo simulation with Gaussian noise on the sound-speed profile. The thus-constructed seismic model marginally satisfies the luminosity condition, L(Rsun)=Lsun, at the 3 sigma level. Using this seismic model, %satisfying L(R_{solar })=L_{solar }, we estimated the neutrino fluxes, and found that the (8) B neutrino flux is about 60% of that of the standard solar model. This model does not seem to contradict the Kamiokande neutrino detection experiment. The (7) Be neutrino flux of the model is about 20% smaller than the standard solar model, and the pp-neutrino flux of the model is almost the same as that of the standard solar model. We estimated the total neutrino capture rate of the chlorine experiment (Homestake) and that of the gallium experiments (GALLEX and SAGE), except for a contribution from the CNO cycle, by scaling the capture rates based on the standard solar model. The thus-estimated capture rates are 5.62 SNU and 117 SNU, respectively, and are higher than those observed at the 3sigma error level.

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