Constraining electron number density in the Sun via Earth-based neutrino flavor data
Caroline Laber-Smith, Eve Armstrong, A. Baha Balantekin, Elizabeth K. Jones, Lily Newkirk, Amol V. Patwardhan, Sarah Ranginwala, M. Margarette Sanchez, Hansen Torres
arXiv:2404.06468v1 Announce Type: new
Abstract: Neutrino flavor transformation offers a window into the physics of various astrophysical environments, including our Sun and the more exotic environs of core-collapse supernovae and binary neutron-star mergers. Here, we apply an inference framework – specifically: statistical data assimilation (SDA) – to neutrino flavor evolution in the Sun. We take a model for solar neutrino flavor evolution, together with Earth-based neutrino measurements, to infer solar properties. Specifically, we ask what signature of the radially-varying solar electron number density $n_e(r)$ is contained within these Earth-based measurements. Currently, the best estimates of $n_e(r)$ come from the standard solar model. We seek to ascertain, through novel application of the SDA method, whether estimates of the same from neutrino data can serve as independent constraints.arXiv:2404.06468v1 Announce Type: new
Abstract: Neutrino flavor transformation offers a window into the physics of various astrophysical environments, including our Sun and the more exotic environs of core-collapse supernovae and binary neutron-star mergers. Here, we apply an inference framework – specifically: statistical data assimilation (SDA) – to neutrino flavor evolution in the Sun. We take a model for solar neutrino flavor evolution, together with Earth-based neutrino measurements, to infer solar properties. Specifically, we ask what signature of the radially-varying solar electron number density $n_e(r)$ is contained within these Earth-based measurements. Currently, the best estimates of $n_e(r)$ come from the standard solar model. We seek to ascertain, through novel application of the SDA method, whether estimates of the same from neutrino data can serve as independent constraints.
2024-04-10