Communicating results between experimentalists and theorists in particle physics has been long and varied. From efficiency maps to selection cut flows - the collaboration between the two communities has continued to grow and evolve. Now, particularly more than ever, a stronger effort has been led within the ATLAS Collaboration taking advantage of the existing technologies used, such as containerization and plain-text data formats, to make analyses fully reproducible. One such data product from an experimental analysis relies on the statistical model used to derive the results published in papers, and these statistical models are essential information for analysis preservation and reuse. The ATLAS Collaboration is starting to publicly provide likelihoods associated with statistical fits used in searches for new physics. These likelihoods adhere to a specification first defined by the HistFactory p.d.f template [CERN-OPEN-2012-016].
This talk is future-focused and will describe my efforts in improving the communication of the field along different avenues. For communicating results of experimental particle physics, I will describe how these statistical models came about, the technical developments to make this possible, and illustrate how detailed information on the statistical modeling can enhance the short- and long-term impact of experimental results. For communicating physics with for Deaf and Hard-of-Hearing members, I will show how I have worked with American Sign Language interpreters and linguistic experts developing words and concepts to ensure accurate, complete communication. These developed signs can also benefit non-signers by changing how particle physicists communicate and collaborate in a large international experiment among colleagues of diverse backgrounds, cultures, and languages. And finally, for the Early Career members of the community, I will describe where we will and can go next with the ATLAS detector.
personal website: https://giordonstark.com
zoom connection: https://cern.zoom.us/j/68399739111?pwd=SGErcHBQYmVLWFZTVE9jdm5xSmdEdz09
indico : https://indico.in2p3.fr/event/32552/
