From Raw Data to Physics Results: course

It would be helpful for students to know: a) How measurements are made in physical detectors, for example how a tracking chamber "sees" a charged particle or how a calorimeter measures energy. b) That physics processes result in photons, leptons, etc., which we then want to detect and analyze. These series of lectures describes the work that lies between the raw data taken by the detector elements and the physics variables used to study particular reactions. We start with an example analysis to show the kinds of information needed. We then describe the fitting process used to extract values from the observed patterns in typical detectors. This is followed by a discussion of the various problems of pattern recognition in tracking, calorimetry and particle identification detectors. The role of Monte Carlo simulation in understanding the quality of the obtained information is examined. We discuss how the use of "composite" observables is required due to what our instrumentation and reconstruction can achieve. The process of calibration and alignment is surveyed, with emphasis on getting "reasonable" results in the absence of formally complete information. Throughout, we emphasize the connection between the data we're collecting and the tests of theory that we want to do.