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26.11.2025   at 10:30 - 11:30

QTC seminar: Gravitational-wave data analysis with machine learning and deep learning

Speaker: Costantino Pacilio from INFN, University La Sapienza
AbstractGravitational-wave astronomy enables precision studies of compact binary systems and provides powerful tests of General Relativity. Black-hole spectroscopy—the detection of gravitational-wave emission spectra from black-hole ringdowns—offers a particularly clean framework for testing gravity theories against well-defined predictions. However, accurate waveform modeling and efficient parameter estimation are essential to extract both astrophysical and fundamental physics insights from the data. In this talk, I will present my recent works in gravitational waveform modeling and inference, with a focus on black hole ringdowns, and highlighting the role of machine learning and deep learning techniques. In particular, I will discuss the promises and challenges of using Gaussian Process Regression for waveform modeling and hierarchical inference, and simulation-based inference for parameter estimation. 

Location: The DIAS Meetingroom Nord (V24-410-2)
You can also join via Zoom
Meeting ID: 278 903 9116
Passcode: 860183

The event is open to all.