I am a cosmologist working at the interface between theoretical modelling and data analysis, experienced in Bayesian and machine learning inference, who also likes to meddle with biomedical imaging. My main scientific interest is primordial non-Gaussianity, which I try to measure using novel methods. To achieve this, I have been studying the spectral distortions of the cosmic microwave background and the large scale structures on non-linear scales.

Projects

The complete list of my publications is available here.

PNG inference on non-linear scales

Small non-linear scales carry a wealth of information we could use to constrain primordial non-Gaussianity. Simulations can be used to model these analytically-intractable scales, and simulation based inference can guide our hand in developing robust and interpretable summary statistics.

Spectral distortions anisotropies

Any energy release event in the universe has left an imprint on the CMB energy spectrum in the form of spectral distortions.
Many exotic processes might have generated peculiar signals that we could unveil studying distortion anisotropies and that we have constrained already.

Radiative processes

Early universe thermalization is driven by creation and destruction of photons. The Bremsstrahlung and double Compton processes allow the primeval plasma to do that.
Precise modelling of the emission rates allow us to predict the cosmological thermal history.

tSZ effect angular distribution

The Sunyaev-Zeldovich effect is a powerful probe of the most massive structures in our Universe.
Its higher order correlators might allow us to harvest the best part of the information it carries.

Curriculum vitae

Pdf version.

Research

Education

Contact

Dr Andrea Ravenni
DFA G. Galilei, Università degli Studi di Padova
Via Marzolo 8, 35131 Padova (PD), Italy