15-19 February 2021
Europe/Paris timezone

ATLAS approach to releasing likelihoods for reinterpretation

15 Feb 2021, 16:00
virtual (online only) (CERN)

virtual (online only)



Eric Schanet (Ludwig Maximilians Universitat (DE))


Full likelihoods encode the entire statistical model of an analysis and thus range among the most invaluable analysis data products for a large range of analyses, ranging from SM measurements to BSM searches. ATLAS has recently started to release the first full analysis likelihoods using a python-based implementation of HistFactory. In this talk, the JSON specification used to release the likelihoods in serialisable format is discussed and details on how process them are given.
In addition, a tool to build simplified likelihoods targeted for CPU-intensive large-scale reinterpretations is presented.
Finally, the current collaboration policy and future plans are discussed.

Primary authors

Eric Schanet (Ludwig Maximilians Universitat (DE)) Jeanette Miriam Lorenz (Ludwig Maximilians Universitat (DE)) Giordon Holtsberg Stark (University of California,Santa Cruz (US)) Lukas Alexander Heinrich (CERN) Matthew Feickert (Univ. Illinois at Urbana Champaign (US))

Presentation Materials