Measuring precise all-flavor neutrino information from a supernova is crucial for
understanding the core-collapse process as well as neutrino properties. We apply a chi …

Simulations of neutrino flavor evolution in compact merger environments have shown that
neutrino flavor, and hence nucleosynthesis, can be strongly affected by the presence of …

We demonstrate the ability of statistical data assimilation (SDA) to identify the measurements
required for accurate state and parameter estimation in an epidemiological model for the …

Inference is a term that encompasses many techniques including statistical data assimilation
(SDA). Unlike machine learning, which is designed to harness predictive power from …

We identify in the flavor transformation of astrophysical neutrinos a new class of
phenomena, a common outcome of which is the suppression of flavor conversion. Appealing …

We continue examining statistical data assimilation, an inference methodology, to infer
solutions to neutrino flavor evolution, for the first time using real—rather than simulated …

Understanding the physics of the deep solar interior, and the more exotic environs of core-
collapse supernovae (CCSN) and binary neutron-star (NS) mergers, is of keen interest in …

Understanding neutrino flavor transformation in dense environments such as core-collapse
supernovae (CCSN) is critical for inferring the physics of these events and interpreting a …

The evolution of neutrino flavor in dense environments such as core-collapse supernovae
and binary compact object mergers constitutes an important and unsolved problem. Its …

Neutrinos in compact-object environments, such as core-collapse supernovae, can
experience various kinds of collective effects in flavor space, engendered by neutrino …