Which is the flavor of cosmic neutrinos seen by IceCube?

We analyze the high-energy neutrino events observed by IceCube, aiming to probe the initial flavor of cosmic neutrinos. We study the track-to-shower ratio of the subset with energy above 60 TeV, where the signal is expected to dominate and show that different production mechanisms give rise to different predictions even accounting for the uncertainties due to neutrino oscillations. We include for the first time the passing muons observed by IceCube in the analysis. They corroborate the hypotheses that cosmic neutrinos have been seen and their flavor matches expectations.

ecCNO Solar Neutrinos: A Challenge for Gigantic Ultra-Pure Liquid Scintillator Detectors

Neutrinos produced in the Sun by electron capture reactions on $^{13}{rm N}$, $^{15}{rm O}$ and $^{17}{rm F}$, to which we refer as ecCNO neutrinos, are not usually considered in solar neutrino analysis since the expected fluxes are extremely low. The experimental determination of this sub-dominant component of the solar neutrino flux is very difficult but could be rewarding since it provides a determination of the metallic content of the solar core and, moreover, probes the solar neutrino survival probability in the transition region at $E_ usim 2.5,{rm MeV}$. In this letter, we suggest that this difficult measure could be at reach for future gigantic ultra-pure liquid scintillator detectors, such as LENA.

The chemical composition of the Sun from helioseismic and solar neutrino data

We perform a quantitative analysis of the solar composition problem by using a statistical approach that allows us to combine the information provided by helioseimic and solar neutrino data in an effective way. We include in our analysis the helioseismic determinations of the surface helium abundance and of the depth of the convective envelope, the measurements of the $^7{rm Be}$ and $^8{rm B}$ neutrino fluxes, the sound speed profile inferred from helioseismic frequencies. We provide all the ingredients to describe how these quantities depend on the solar surface composition and to evaluate the (correlated) uncertainties in solar model predictions. We include errors sources that are not traditionally considered such as those from inversion of helioseismic data. We, then, apply the proposed approach to infer the chemical composition of the Sun. We show that the opacity profile of the Sun is well constrained by the solar observational properties. In the context of a two parameter analysis in which elements are grouped as volatiles (i.e. C, N, O and Ne) and refractories (i.e Mg, Si, S, Fe), the optimal composition is found by increasing the the abundance of volatiles by $left( 45pm 4right)%$ and that of refractories by $left( 19pm 3right)%$ with respect to the values provided by AGSS09. This corresponds to the abundances $varepsilon_{rm O}=8.85pm 0.01$ and $varepsilon_{rm Fe}=7.52pm0.01$. As an additional result of our analysis, we show that the observational data prefer values for the input parameters of the standard solar models (radiative opacities, gravitational settling rate, the astrophysical factors $S_{34}$ and $S_{17}$) that differ at the $sim 1sigma$ level from those presently adopted.