Analysis Software

The 2 experiment has provided us with the opportunity to develop the basic framework for the analysis software to be used with the µLan detector. The principal stages of the data reduction process are the same in both cases:

• We decode the headers that UNIDAQ inserts to label the individual modules.
• We determine the boundaries between consecutive pulses in the data by finding the times at which the pulse rises above and then dips below a software threshold.
• We subtract the known pedestal value from each bin of the pulse. In the typical case, the pedestal can be determined from the first sample of each digitization interval, which is taken several nanoseconds before the rising edge of the pulse.
• We determine the time and energy of each pulse. We have various algorithms that perform this step. The simplest is to find the area by adding up the samples in a fixed number of bins centered about the maximum value of the pulse, and to find the time by taking an average of the times associated with these central bins of the pulse, weighted by the sample in each bin.
• We histogram the number of hits as a function of time in the fill, subject to appropriate cuts on the pulse area.

We have developed a versatile system to carry out these steps. It is based on the ROOT object-oriented analysis framework, described in [24]. In addition, we have begun to experiment with using Java Analysis Studio, described in [25], for this purpose. We believe that a significant amount of the code that we develop will be reusable for the µLan experiment.

One very significant difference is that, as described in the previous section, much of this analysis will take place in the online system. This means that we can expect a physics result relatively soon after the conclusion of the running time. It also means that we will have fast feedback to guide the process of running the experiment.