September 24, 2021

Solar and Space Physics UNIToV

Gruppo di Fisica Solare e Spaziale Università di Roma Tor Vergata

Digital Data Analysis – M. D. Course in Physics of Complex Systems and Big Data

Digital Data Analysis [8CFU]
AA 2018-2019 – Dr. Dario Del Moro – Dr. Giancarlo De Gasperis

Tracks for a random walks simulation of magnetic points on the solar surface

The aim of the course is to provide to the student a broad overview of the various methods and techniques of data analysis, with a deeper insight on those used in modern-time astrophysics.
In particular, we will study the aspects of digital information access, handling, restoration, manipulation, compression and transformation into data. All these aspects will be also tackled in the laboratory sessions, where the students will have the opportunity to work on actual astrophysics data-sets to implement the algorithm introduced in the lessons.

Section I: The Transforms
Signal Processing I: Sampling of the Signal (The Sampling Theorem, The Convolution, The Correlation, Correlation is not Causation, Decomposition of the Signal on the Sphere)
Signal Processing II: The Fourier Transform (The DFT, The FFT, The Power Spectrum, The Phases, Discretization of the Signal on the Sphere)
The Information: Wavelets, PCA and EMD (Data compression, MP3, JPEG2000, JP3D)

Section II: The Signal and The Noise
The Noise: Noise Sources, Noise Types and Spectra, SNR maximization, Noise suppression 

Time-dependent PDF for pair separation of magnetic elements (a), b)), and the same rescaled to unity rms c), d) for initial separations in the range 7.42 <r0< 7.77 Mm a), c) and 10.21 <r0< 10.56 Mm b), d). The shaded areas in panels a) and b) cover the initial separation bins. All PDFs are normalized to unit area.

Data Restoring: Image reconstruction vs Scanning, Speckle Imaging, Blind Deconvolution
Data Analysis: Patterns in Data, Punctual Operatore and Filters, More Transforms, Morphological Operators and Descriptors

In the LAB:
Data Access: FITS + multiFITS
Datafication examples: H-R diagram, Kepler data and star periods
The Fourier Transform: Fourier spectrum, Digital Filters, Data manipulation (shifts, transform)
Data-cubes Analysis: Wavelet Spectra, EMD analysis
Data Compression: Image quality estimators, Image information estimators

DOWNLOAD LECTURES HERE