Study of cosmic nuclei fluxes with AMS-02: implication for dark matter search

L’Alpha Magnetic Spectrometer (AMS-02) é un rivelatore per raggi cosmici (CR) progettato e costruito da una collaborazione internazionale di 56 istituti e 16 paesi ed installato il 19 Maggio del 2011 sulla Stazione Spaziale Internazionale (ISS). Orbitando intorno alla Terra, AMS-02 sará in grado di studiare con un livello di accuratezza mai raggiunto prima la composizione dei raggi cosmici, esplorando nuove frontiere nella fisica delle particelle, ricercando antimateria primordiale ed evidenze indirette di materia oscura. Durante il mio lavoro di tesi, ho utilizzato il software GALPROP per studiare la propagazione dei CR nella nostra Galassia attraverso il mezzo interstellare (ISM), cercando di individuare un set di parametri in grado di fornire un buon accordo con i dati preliminari di AMS-02. In particolare, mi sono dedicata all’analisi del processo di propagazione di nuclei, studiando i loro flussi e i relativi rapporti. Il set di propagazione ottenuto dall’analisi é stato poi utilizzato per studiare ipotetici flussi da materia oscura e le possibili implicazioni per la ricerca indiretta attraverso AMS-02.

Antarctic cloud spectral emission from ground-based measurements, a focus on far infrared signatures

The present work belongs to the PRANA project, the first extensive field campaign of observation of atmospheric emission spectra covering the Far InfraRed spectral region, for more than two years. The principal deployed instrument is REFIR-PAD, a Fourier transform spectrometer used by us to study Antarctic cloud properties. A dataset covering the whole 2013 has been analyzed and, firstly, a selection of good quality spectra is performed, using, as thresholds, radiance values in few chosen spectral regions. These spectra are described in a synthetic way averaging radiances in selected intervals, converting them into BTs and finally considering the differences between each pair of them. A supervised feature selection algorithm is implemented with the purpose to select the features really informative about the presence, the phase and the type of cloud. Hence, training and test sets are collected, by means of Lidar quick-looks. The supervised classification step of the overall monthly datasets is performed using a SVM. On the base of this classification and with the help of Lidar observations, 29 non-precipitating ice cloud case studies are selected. A single spectrum, or at most an average over two or three spectra, is processed by means of the retrieval algorithm RT-RET, exploiting some main IR window channels, in order to extract cloud properties. Retrieved effective radii and optical depths are analyzed, to compare them with literature studies and to evaluate possible seasonal trends. Finally, retrieval output atmospheric profiles are used as inputs for simulations, assuming two different crystal habits, with the aim to examine our ability to reproduce radiances in the FIR. Substantial mis-estimations are found for FIR micro-windows: a high variability is observed in the spectral pattern of simulation deviations from measured spectra and an effort to link these deviations to cloud parameters has been performed.