# Data analysis with the Gravitational Wave LIGO/Virgo data (VIRGO_DA)

E-mail : pia.astone@roma1.infn.it
## Anno accademico 2019/2020

### Tutors: P. Astone, S. Frasca, Ornella Piccinni, Lorenzo Pierini

###
**Next lectures: **

** to be fixed** | 18-19.30 | ** Skype P. Astone ** |

### Official working hours in our lab: Tuesdays from 2/3 to 6/7 PM

**Presentation of the project (2020)**

### The program in short

Data analysis for gravitational wave detectors like
LIGO
and Virgo.

Lectures on general aspects of gw experiments and searches will be given at the beginning.
Students will learn signal processing methods (FFTs, spectral analysis, filtering, procedures to extract signals from noise). Programming language is Matlab. The analysis will be done using simulated data (signals added to noise).
###
Material for 2019-2020 :

###

The software
Examples
Evolving info document
Matched filtering applied to CBC signals

## Anno accademico 2018/2019

### First meeting with students: Friday 15 march 2019.

###
**Next meetings, lectures and tutorials: **

**Monday 18 march** | 18-19.30 | ** G23. P. Astone ** |

**Wednesday 20 march ** | 18-19.30 | ** G23. P. Astone** |

**Wednesday 27 march ** | 18.15-19.300 | ** G23. P. Astone ** |

** Tuesday 2 march ** | 18-19.30 | ** G23. P. Astone ** |

** Work on Tuesdays @ G23 ** | 18-19.30 | ** G23. ** |

### Official working hours in our lab: Tuesdays from 2/3 to 6/7 PM

**Presentation of the project (March, 5th 2019)**

### The program in short

Data analysis for gravitational wave detectors like
LIGO
and Virgo.

The signals analyzed will be those of the coalescence of two black holes of solar masses (CBC signalss), like
GW150914

Lectures on general aspects of gw experiments and searches will be given at the beginning.
Students will learn signal processing methods (FFTs, spectral analysis, filtering, procedures to extract signals from noise). They will construct and apply mathed filtering to CBC signals and then construct a grid of matched filters in order to evaluate the effect of a mismatch in the parameters of the filter vs the real signal. If there is interest, implementation and optimization of the code on GPUs will be included in the project. Programming language is Matlab. The analysis will be done using simulated data (chirp signals added to white noise), to begin, and then on real data LIGO or Virgo data (if there will be enough time and interest).
###
Material for 2018-2019:

###

The software
Examples
Evolving info document
Matched filtering applied to CBC signals
S. Frasca. Lab Segnali e sistemi

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Lectures:

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How the interferometer works and some basic aspects of the gw search. P. Astone
The search for compact binary coalescences in LIGO and Virgo data. P. Astone
Data analysis: signals. P. Astone/S. Frasca
Data analysis: filtering. P. Astone/S. Frasca

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Other important material:

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LIGO/Virgo open data center
CBC signals release
Science summaries of the LIGO/Virgo papers