Data Reduction Techniques And Extraction Of Physics Parameters In The Icarus Detector

A liquid argon time projection chamber (LAr-TPC) working as an electronic bubblechamber, continually sensitive, self-triggering, able to provide 3-D imaging of any ionizing event together with a good calorimetric response was first proposed by Carlo Rubbia in 1977. In order to verify the feasibility of such a detector, the ICARUS collaboration started in 1985 an intensive R&D program aiming to solve the main technological problems. The satisfactory results obtained on small scale tests allowed us to start in 1989 the construction of a 3 ton prototype which is presently working at CERN under stable conditions without interruptions since May 1991, collecting events from cosmic rays and monochromatic gamma ray sources.The paper describes the working principles of such a detector, showing the results of the research program applied in the present prototype. Some emphasis is put into the description of the read-out apparatus, a custom designed VME-based multichannel waveform recorder. The huge number of channels and the high sampling rate essential to achieve the high resolution in the track detection make the data acquisition architecture a crucial point for event detection rate and self-triggering capabilities. At present a. complete signal analysis is performed to define those parameters needed to tune up algorithms and filtering methods that will become necessary in the future step of the ICARUS detector (hundred to thousands of tons of argon, i. e. tens of thousands of readout channels). A particular effort is made to optimize track localization algorithms, in order to achieve high efficiency data reduction by storing only those portions of signal which contain the track (thus lowering up to three orders of magnitude the event size) .From a human interface point of view, the data presentation relies on an event imaging very similar to the old fashioned bubble chambers. Besides from giving a direct feeling of what happens inside the detector, this kind of representations opens a way to the wide panorama of image processing applications: tasks as detail enhancement, pattern recognition or 3D reconstruction will helpfully inherit support from more general procedures.