Assessing coincident neutrino detections using population models

• Several tentative associations between high-energy neutrinos and astrophysical sources have been recently reported, but a conclusive identification of these potential neutrino emitters remains challenging. We explore the use of Monte Carlo simulations of source populations to gain deeper insight into the physical implications of proposed individual source–neutrino associations. In particular, we focus on the IC170922A–TXS 0506+056 observation. Assuming a null model, we find a 7.6% chance of mistakenly identifying coincidences between γ-ray flares from blazars and neutrino alerts in 10-year surveys. We confirm that a blazar–neutrino connection based on the γ-ray flux is required to find a low chance coincidence probability and, therefore, a significant IC170922A–TXS 0506+056 association. We then assume this blazar–neutrino connection for the whole population and find that the ratio of neutrino to γ-ray fluxes must be ≲10−2 in order not to overproduce the total number of neutrino alerts seen by IceCube. For the IC170922A–TXS 0506+056 association to make sense, we must either accept this low flux ratio or suppose that only some rare sub-population of blazars is capable of high-energy neutrino production. For example, if we consider neutrino production only in blazar flares, we expect the flux ratio of between 10−3 and 10−1 to be consistent with a single coincident observation of a neutrino alert and flaring γ-ray blazar. These constraints should be interpreted in the context of the likelihood models used to find the IC170922A–TXS 0506+056 association, which assumes a fixed power-law neutrino spectrum of E−2.13 for all blazars. 

Subject headings

NATURVETENSKAP  -- Fysik -- Astronomi, astrofysik och kosmologi (hsv//swe)

NATURAL SCIENCES  -- Physical Sciences -- Astronomy, Astrophysics and Cosmology (hsv//eng)

NATURVETENSKAP  -- Fysik -- Subatomär fysik (hsv//swe)

NATURAL SCIENCES  -- Physical Sciences -- Subatomic Physics (hsv//eng)

Keyword

neutrinos

astroparticle physics

methods: data analysis

Publication and Content Type

ref (subject category)

art (subject category)