Draft of plan for study of DSO filter efficiency using simulated bursts AJW (1/15/02) Study DSO's response to (software) injected signals... - obtain tclsh scripts for running all 3 DSO's. - make sure we know what filterparams need changing - Obtain running time on an LDAS facility (preferably site). Obtain a test DB for storing triggers; make sure we can distinguish triggers generated using simulated data from triggers using real data. Run the DSOs exactly like they were run during E7. - OPTION: real E7 data (complete with glitches) or simulated Gaussian noise with E7 noise power spectra; in both cases, we have 3 IFOs to look at. Do we want to evaluate efficiency in presence of Gaussian noise or outlier glitches? Want to do both! Start with the former. For a pub, must have REAL efficiencies using E7 data; this requires high statistics, so we must work towards having high statistics simulation runs. - Have access to minutes or hours of frame data containing all the channels needed by the DSO, locked streches, with relevant calibration, and some measure of how glitchy. - use stand-alone tools to acquire data, inject signals, and deposit modified frame file on LDAS (via ftp) - OPTION: different waveforms. I think it's best to start with relatively narrow-band bursts (damped sinusoids). - Damped sinusoids have 3 parameters: h_peak, f_central, and bandwidth (1/tau). - Absolute normalization of waveform (eg, h_peak = 1e-19, etc). - Filter waveform through E7 transfer function, including whitening, etc. Inject on top of data or simulated noise with E7 noise power spectrum. (Using E7 as a specific example; can do it for any TF). - Then we want to inject many bursts, varying h_peak, f_central, and bandwidth. - Check DB to see if burst was found (eventually, within pre-defined windows in parameter space). - Represent efficiency vs h_peak, f_central, and bandwidth with suitable plots. - At the same time, evaluate efficiency vs filterparam thresholds. - Repeat, with different waveforms... - Repeat, with data sources - Repeat, optimizing DSO parameters, thresholds, etc As we change the DSO parameters significantly, we must be prepared to run the DSO(s) through the entire E7 dataset again. - We may also want to study correlations between IFOs using these simulation tools.