direct detection of the cosmic neutrino background

Today was an all-day meeting at the Flatiron Institute on neutrinos in cosmology and large-scale structure, organized by Francisco Villaescusa-Navarro (Flatiron). I wasn't able to be at the whole meeting, but two important things I learned in the part I saw are the following:

Chris Tully (Princeton) astonished me by showing his real, funded attempt to actually directly detect the thermal neutrinos from the Big Bang. That is audacious. He has a very simple design, based on capture of electron neutrinos by tritium that has been very loosely bound to a graphene substrate. Details of the experiment include absolutely enormous surface areas of graphene, and also very clever focusing (in a phase-space sense) of the liberated electrons. I'm not worthy!

Raul Jimenez (Barcelona) spoke about (among other things) a statistical argument for a normal (rather than inverted) hierarchy for neutrino masses. His argument depends on putting priors over neutrino masses and then computing a Bayes factor. This argument made the audience suspicious, and he got some heat during and after his talk. Some comments: One is that he is not just doing simple Bayes factors; he is learning a hierarchical model and assessing within that. That is a good idea. Another is that this is actually the ideal place to use Bayes factors: Both models (normal and inverted) have exactly the same parameters, with exactly the same prior. That obviates many of my usual objections (yes, my loyal reader may be sighing) to computing the integrals I call FML. I Need to read and analyze his argument at some point soon.

One amusing note about the day: For technical reasons, Tully really needs the neutrino mass hierarchy to be inverted (not normal), while Jimenez is arguing that the smart money is on the normal (not inverted).


  1. It is difficult to setup meaningful priors for neutrinos: imposing flat or log flat priors on the masses, their squares, or on the differences, affects the hierarchies (normal hierarchy is typically favored). This is known, but no one really knows which prior is the most physically motivated. In addition, neutrino experiments don't provide likelihood functions per se (for many good reasons) and have complicated priors built-in. At present there is no analysis using all the available data correctly!

  2. It seems to me that they took a lot of heat for daring to suggest that priors could exist prior to an experiment! https://astrostatistics.wordpress.com/2017/03/16/intrigue-in-the-neutrino-kingdom/