Development of New Technologies for Particle Detection and Application of Machine Learning Techniques to Search for New Physics Using the ATLAS Detector

A suite of linked research projects is undertaken, combining a search for phenomena beyond the Standard Model of particle physics, development of new instruments for greater precision in detecting fundamental particles, and tracking and understanding the effect upon the detectors of the radiation that is an indelible element of their operating environment. Data recorded by the ATLAS Detector at CERN are employed in a search for evidence of undiscovered particles contributing to the rate of decays of B_(s,d) mesons to dimuon final states. New applications of machine learning techniques are implemented to separate this signal from its many backgrounds. That analysis is combined with a highly sensitive evaluation of the effects of radiation damage already received by the Pixel detector and a comparison of these data to a detailed model of radiation. A complementary thrust of this effort involves development of new devices and techniques for monitoring radiation fluences and calibrating particle physics detectors in a high radiation field. Finally, a comprehensive program for quality assurance of the ATLAS upgrade inner tracker modules and staves is being developed and applied to components assembled at SLAC laboratory, including electrical and mechanical tests and an interactive data structure of these results.