| As indicated in Chapter 9: Physics, 
              the software for an experiment falls into three main categories: 
              physics simulation, experiment hardware simulation, and analysis. 
              (There can be, of course, various other utility software involved 
              such as that used for calibration of detectors and electronics but 
              we'll focus on these three primary tasks.) In fact, a large experiment 
              might split software assignments among three groups: one to produce 
              the basic physics simulators, one to simulate the detector hardware, 
              and a third to produce the analysis software.  Long before the experiment begins to run , the analysis group will 
              rely on the simulation software to produce realistic data on which 
              the analysis programs can "practice". The process will 
              require a bootstrap approach as the software of each team develops. 
              For example, the analysis software will only need crude simulator 
              data initially to debug the code. The detector software will become 
              more realistic once the detectors begin to undergo calibration tests 
              and produce data on which to tune the simulators. Feedback from 
              the analysis programming could correct possible errors in the detector 
              and physics programs. Ideally the simulated data would eventually reach such a degree 
              of realism that it would allow for "double-blind" tests 
              of the analyzes to reduce systematic biases. We will continue with our demonstration of experimental simulation 
              and data analysis with our mass drop example. Though it deals rather 
              trivial physics, it will help to illustrate the basic concepts and 
              techniques involved in developing the simulation and analysis programs 
              to support a actual experiment.   |