The Multi-Mission Maximum Likelihood Framework (3ML): a Tool to Explore the High-Energy Universe in the Era of Multi Messenger Astrophysics

Stanford University, Stanford CA

Investigators

Abstract

Astrophysical sources are now observed by many instruments at wavelengths from radio to high-energy gamma-rays, and using different messengers, including light, light polarization, neutrinos, cosmic rays, and gravitational waves. Extracting insight from these data is currently very difficult because each instrument has its own data format, software, and analysis procedure, each requiring specialized knowledge and training. The Multi-Mission Maximum Likelihood framework (3ML) solves this issue, allowing easy modeling using all available data, independent of origin. Each instrument provides an interface from their data to 3ML, while 3ML optimizes model parameters to match all of the data as well as possible. This award supports the continued development of 3ML, focusing in particular on enabling new science for the High-Altitude Water Cerenkov telescope (HAWC) through the HAWC Accelerated Likelihood (HAL), a new 3ML component. The project includes tutorials to promote the use of 3ML for multi-wavelength study, targeting undergraduate and graduate students and exposing them to competitive research projects and fundamental questions in astrophysics. This work on 3ML and HAL is necessary to enable progress on several key scientific questions, such as: 1) cosmic ray acceleration, and in particular the open question of the source of ultra-high-energy Cosmic Rays; 2) dark matter annihilation cross sections through the modeling of the gamma-ray sky; 3) the origin of astrophysical neutrinos; 4) high-energy counterparts to gravitational wave signals and gamma-ray bursts; and 5) the extra-Galactic background light, by a stacking analysis of the spectra of many sources simultaneously. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.