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Commissioning studies of the CMS hadron calorimeter have identified sporadicuncharacteristic noise and a small number of malfunctioning calorimeterchannels. Algorithms have been developed to identify and address these problemsin the data. The methods have been tested on cosmic ray muon data, calorimeternoise data, and single beam data collected with CMS in 2008. The noiserejection algorithms can be applied to LHC collision data at the trigger levelor in the offline analysis. The application of the algorithms at the triggerlevel is shown to remove 90% of noise events with fake missing transverseenergy above 100 GeV, which is sufficient for the CMS physics triggeroperation.

Identification and Filtering of Uncharacteristic Noise in the CMS Hadron Calorimeter