Giuseppe Cabras

Reducing wind noise in seismic data using Non-negative Matrix Factorization: an application to Villarrica volcano, Chile

Single channel source separation of seismic signals is an appealing but difficult problem. In this paper, we introduce a semi-blind single-channel seismic source separation method to enhance the components of volcanic origin. In this method, the source decomposition scheme is addressed as a Sparse Non-negative Matrix Factorization (NMF) of the time-frequency representation of the single vertical seismic channel. As a case study we present an application using seismic data recorded at Villarrica volcano, Chile, one of the most active in the southern Andes. The analysed dataset is strongly contaminated by wind noise and the procedure is used to separate a component of volcanic origin from another of meteorological origin.

A distributed, Grid-based analysis system for the MAGIC telescope

The observation of high-energetic γ-rays with ground based air cerenkov telescopes is one of the most exciting areas in modern astro particle physics giving insight into active galactic nuclei (AGN), pulsars, supernova remnants, unidentified EGRET sources, γ-ray bursts and cosmology. The MAGIC telescope started operation at the end of 2003. The low energy threshold for γ-rays together with different background sources leads to a considerable amount of data. The data analysis will be done in different institutes spread across Europe. The production of Monte Carlo events including the simulation of Cerenkov light in the atmosphere is very computing intensive and another challenge for a collaboration like MAGIC. The current Grid technology widely deployed over 80 sites by LCG has recently proven to be mature and well adapted to set up a distributed computational and data intensive analysis system meeting the requirements of experiments like MAGIC. The basic architecture of such a distributed, Europe wide Grid system will be presented. First implementation results will be shown. This Grid might be the starting point for a wider distributed astro particle Grid in Europe.

GRID SERVICES FOR THE MAGIC EXPERIMENT

Exploring signals from the outer space has become an observational science under fast expansion. On the basis of its advanced technology the MAGIC telescope is the natural building block for the first large scale ground based high energy gamma-ray observatory. The low energy threshold for gamma-rays together with different background sources leads to a considerable amount of data. The analysis will be done in different institutes spread over Europe. Therefore MAGIC offers the opportunity to use the Grid technology to setup a distributed computational and data intensive analysis system with the nowadays available technology. Benefits of Grid computing for the MAGIC telescope are presented.

A novel background reduction strategy for high level triggers and processing in gamma‐ray Cherenkov detectors

Gamma ray astronomy is now at the leading edge for studies related both to fundamental physics and astrophysics. The sensitivity of gamma detectors is limited by the huge amount of background, constituted by hadronic cosmic rays (typically two to three orders of magnitude more than the signal) and by the accidental background in the detectors. By using the information on the temporal evolution of the Cherenkov light, the background can be reduced. We will present here the results obtained within the MAGIC experiment using a new technique for the reduction of the background. Particle showers produced by gamma rays show a different temporal distribution with respect to showers produced by hadrons; the background due to accidental counts shows no dependence on time. Such novel strategy can increase the sensitivity of present instruments.

The restoration of low-quality audio recordings based on non-negative matrix factorization and perceptual assessment by means of the ebu mushra test method

In this paper, we focus on the signal-to-noise ratio (SNR) improvement in single channel audio recordings. Many approaches have been reported in the literature. The most popular method, with many variants, is Short Time Spectral Attenuation (STSA). Although this method reduces the noise and improves the SNR, it mostly tends to introduce signal distortion and a perceptually annoying residual noise usually called musical noise. In this paper we investigate the use of Non-negative Matrix Factorization (NMF) as an alternative to the STSA for the digital curation of musical heritage. NMF is an emerging new technique in the blind extraction of signals recorded in a variety of different fields. The application of NMF to the analysis of monaural recordings is relatively recent. We show that NMF is a suitable technique to extract the clean audio signal from undesired non stationary noise in a monaural recording of ethnic music. More specifically, we introduce a perceptual suppression rule to determine how the perceptual domain is competitive compared to the acoustic domain. Moreover, we carry out a listening test in order to compare NMF with the state of the art audio restoration framework using the EBU MUSHRA test method. The encouraging results obtained with this methodology in the presented case study support their wider applicability in audio separation.

A THIRD LEVEL TRIGGER PROGRAMMABLE ON FPGA FOR THE GAMMA/HADRON SEPARATION IN A CHERENKOV TELESCOPE USING PSEUDO-ZERNIKE MOMENTS AND THE SVM CLASSIFIER

We studied the application of the Pseudo-Zernike features as image parameters (instead of the Hillas parameters) for the discrimination between the images produced by atmospheric electromagnetic showers caused by gamma-rays and the ones produced by atmospheric electromagnetic showers caused by hadrons in the MAGIC Experiment. We used a Support Vector Machine as classification algorithm with the computed Pseudo-Zernike features as classification parameters. We implemented on a FPGA board a kernel function of the SVM and the Pseudo-Zernike features to build a third level trigger for the gamma-hadron separation task of the MAGIC Experiment.

Quality Product Controls of Silicon Pixel Sensors for a High Energy Particle Physics Experiment

This paper describes the quality control tests on the silicon pixel sensors for the ATLAS detector [1], performed at the Semiconductor Detectors Laboratory of the Physics Department of the Udine University. A silicon pixel detector system [1] for high multiplicity charged particle pattern recognition has been developed by the ATLAS collaboration to meet the CERN Large Hadron Collider [2] requirements. Every component is tested at each stage of the construction by the producers according to agreed standards, under the control of the collaborating institutes. Nevertheless, some of the quality controls must be performed in the institutes, since they require tools available only in specific laboratories of the collaboration. The Udine group of the Istituto Nazionale di Fisica Nucleare is among the groups which have the skills for such specialized controls.