AliITSPreprocessorSPD: Identifying Noisy Channels in SPD

1. Status of SPD Preprocessor Class Paul Nilsson

2. AliITSPreprocessorSPD Status Noisy channel finder implemented in new AliITSPreprocessorSPD class • Two versions of the algorithm • Optimized for data (noisy channels mixed with real hits) • Optimized for calibration data (i.e. data taken without beam) • Both versions scan the 2D histograms containing the digits (one histogram per SPD module) • Algorithm 1 compares each bin with the surrounding channels (if the bin content > n times the average neighborhood, it is considered “noisy”) • Algorithm 2 assumes only noisy channels present (everything above a threshold is per definition “noisy”) • Identified noisy channels are so far only stored in a tree (work in progress) P. Nilsson

3. AliITSPreprocessorSPD Status // Example of how to run the preprocessor for the SPD { // Instantiate the preprocessor AliITSPreprocessorSPD prepSPD("run_its_189_5k.root"); // Select a geometry (either kALICEGeometry or kTestBeamGeometry) prepSPD.SetGeometryMode(AliITSPreprocessorSPD::kTestBeamGeometry); // Select the noisy channel finder algorithm (either kOptimizedForRealData or // kOptimizedForCalibrationData, real data is default) prepSPD.SelectAlgorithm(AliITSPreprocessorSPD::kOptimizedForRealData); // Set the minimum number of times a channel must have fired to be called noisy (default is 10.) prepSPD.SetThreshold(20.); // Set the current bin content to average neighborhood ratio (default is 5.) prepSPD.SetThresholdRatio(5.); // Set the number of events (default is all available events) prepSPD.SetMaximumNumberOfEvents(5000); // Find the noisy channels prepSPD.FindNoisyChannels(); // Print out the found noisy channels (dump to standard output) prepSPD.PrintNoisyChannels(); // Remove the found noisy channels prepSPD.RemoveNoisyChannels(); } A noisy channel has to fire at least 20 times, 5 times the average of the neighbors P. Nilsson

4. AliITSPreprocessorSPD Status Data taken last week Test Beam 2004 data – Hits in SPD module 1 Not real maximum Row Row Column Column Raw data before noisy channel removal After noisy channel removal P. Nilsson