Model Of The Response Function Of Cuore Bolometers 2011 Edition

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Springer Model Of The Response Function Of Cuore Bolometers 2011 Edition by Marco Vignati

Large mass bolometers are used in particle physics experiments to search for rare processes like neutrinoless double beta decay and dark matter interactions.In the next years the CUORE experiment (a 1 Ton detector composed by 1000 crystals of TeO2 operated as bolometers in a large cryostat at 10mK) will be the particle physics experiment with the highest chance of discovering the Majorana neutrino a long standing and yet fundamental question of particle physics. The study presented in this book was performed on the bolometers of the CUORE experiment. The response function of these detectors is not linear in the energy range of interest and it changes with the operating temperature worsening the performances. The nonlinearity appeared to be dominated by the thermistor and the biasing circuit used to read the bolometer and was modeled using few measurable parameters.A method to obtain a linear response is the result of this work. It allows a great improvement of the detector operation and data analysis. With a foreword by Fernando Ferroni. Table of contents : ForewordAcknowledgements1 Neutrino masses and double beta decay1.1 Oscillations 1.2 Masses 1.3 Double beta decay 1.3.1 Nuclear matrix elements 1.4 Experimental searches for neutrinoless double beta decay 1.4.1 Past and present experiments 1.4.2 Future experiments2 TeO2 bolometric detectors for 0_DBD search2.1 Bolometric detectors 2.1.1 The energy absorber 2.1.2 The choice of TeO2 2.1.3 The sensor 2.1.4 NTD-Ge thermistors 2.2 Bolometer operation 2.3 Arrays of TeO2 bolometers 2.4 Cryogenic setups 2.5 Signal readout 2.5.1 Measurement of the static resistance 2.6 Detector noise 2.7 CUORICINO and CUORE3 Model of the response function of CUORE bolometers3.1 The CCVR run 3.2 The Model 3.2.1 Thermistor model 3.2.2 Biasing circuit 3.2.3 Bessel filter 3.2.4 Thermal model 3.2.5 Simplified model without temperature dependences 3.2.6 Fit to data 3.2.7 Response function simulation 3.2.8 Amplitude dependence on the working temperature 3.2.9 Extraction of RS from the relationship between amplitude and baseline 4 Thermal response analysis4.1 Data analysis procedure 4.2 The Thermal Response algorithm 4.3 Check of the TR algorithm on MonteCarlo data 4.4 Data analysis 4.4.1 Calibration 4.5 Residual drift in time 4.6 Sources of systematic errors 4.6.1 Choice of the derivative algorithm 4.6.2 Error on the biasing and read-out circuits parameters5 Thermal response analysis on the Three Towers detector5.1 The Three Towers detector 5.2 Measurements of model parameters 5.2.1 Measurement of V G RS and VS 5.2.2 Measurement of G/GS 5.2.3 Measurement of RL 5.2.4 Measurement of VBGS 5.2.5 Measurement of cp 5.3 Results on calibration data 5.4 Results on background data 5.5 Future developments6. ConclusionsAppendix A Thermal response analysis on the CCVR detectorAppendix B Precision measurements on the Three Towers detector