Digital Signal Processing applied to Physical Signals

It is well known that many of the scientific and technological discoveries of the XXI century will depend on the capability of processing and understanding a huge quantity of data. With the advent of the digital era, a fully digital and automated treatment can be designed and performed. From data mining to data compression, from signal elaboration to noise reduction, a processing is essential to manage and enhance features of interest after every data acquisition (DAQ) session. In the near future, science will go towards interdisciplinary research. In this work there will be given an example of the application of signal processing to different fields of Physics from nuclear particle detectors to biomedical examinations. In Chapter 1 a brief description of the collaborations that allowed this thesis is given, together with a list of the publications co-produced by the author in these three years. The most important notations, definitions and acronyms used in the work are also provided. In Chapter 2, the last results on the filter designs to be implemented in the trigger-less DAQ of the PANDA experiment are presented. Results obtained from simulation are used as basis for some FPGA-oriented filter projects able to process in real time data from nuclear particle detectors. For all studied filter structures, particular attention has been paid to the board inner-components consumption and to the maximum working frequency, since our aim is an on-line treatment. In Chapter 3, from a collaboration with the INRiM institute of research, the results of signal processing of data coming from TES single photon detectors are reported. Because of their high sensitivity and fast response, the application of these detectors is mandatory to all fields that deal with weak sources. It ranges from astrophysics to structure of matter, from X-rays to infra-red wavelengths. However, the electronic DAQ system and the environmental conditions of every acquisition require a digital treatment to extract the most important features of interest as the energy resolution or the capability to really count single photons of every DAQ session. The author had the possibility to spend a three months period as a PhD visiting student at CERN, Geneva. During this experience he was involved in the ALICE experiment of the LHC project. The goal was the development of an algorithm able to process on-line data from all detectors to be implemented on FPGA. The results of this study are reported in Chapter 4, subdivided in a simulation part, used to understand and write the algorithm, and in a real data analysis. The last application of signal processing presented, comes from a collaboration with the Ottica e Optometria course of studies of the University of Turin, it is introduced in Chapter 5. The analyses conduced on human corneas aiming at distinguishing all corneal sub-layers and estimating their thicknesses are reported. Every acquired image represents a signal to be processed. The impact of this development on medical applications is very high since, for the first time, all these clinical tests can be made in-vivo with no adverse effect for patients and with a precision never reached before. The work is concluded, in Chapter 6, with some considerations on the usefulness, and surely the necessity, of signal processing in science experiments.