Expertise

Topics:  High Energy Astrophysics, Cosmology, Space, Astrophysics, Black Holes

Industries: Research, Education/Learning

Tiziana Di Matteo's research focuses on the study of black holes, encompassing a wide range of topics in both high energy astrophysics and cosmology. They include theoretical studies of the interplay between black hole growth and galaxy formation and investigations of various aspects of the physics of accretion disks around black holes.

Media Experience

Simulation showing Milky Way-esque galaxy in early universe could prove cold dark matter theory  — IBTimes
Tiziana Di Matteo, professor of physics at Carnegie Mellon, said: "It's awe inspiring to think that galaxies much like our own existed when the universe was so young. The deepest Hubble Space Telescope observations have thus far only covered small volumes of space and have found very irregular, clumpy galaxies at these early epochs.

Milky Way-like galaxies may have existed in the early universe  — Phys.org
"It's awe inspiring to think that galaxies much like our own existed when the universe was so young," said Tiziana Di Matteo, professor of physics at Carnegie Mellon. "The deepest Hubble Space Telescope observations have thus only covered small volumes of space and have found very irregular, clumpy galaxies at these early epochs. It is not surprising that in these small volumes some of the small galaxies do not have regular morphologies like large disk galaxies. Similarly, numerical simulations have been limited in size so they have only made predictions for the smaller, clumpier galaxies at these early times."

A taste of James Webb’s potential  — Cosmos
To determine what Webb is expected to see, the team then used a state-of-the-art computer simulation called BlueTides, developed by a team led by Tiziana Di Matteo from Carnegie Mellon University (CMU) in Pittsburgh, US.

Machine learning accelerates cosmological simulations  — EurekAlert!
Carnegie Mellon University Physics Professors Tiziana Di Matteo and Rupert Croft, Flatiron Institute Research Fellow Yin Li, Carnegie Mellon Ph.D. candidate Yueying Ni, University of California Riverside Professor of Physics and Astronomy Simeon Bird and University of California Berkeley's Yu Feng surmounted this problem by teaching a machine learning algorithm based on neural networks to upgrade a simulation from low resolution to super resolution.

Hubble Finds Double Quasar in Early Universe  — Carnegie Mellon University News
“Understanding how black holes form, the first quasars emerge and how they grow along our cosmic histories is one of the greatest theoretical and observational challenges of modern astrophysics,” said Tiziana Di Matteo(opens in new window), professor of physics and director of Carnegie Mellon’s McWilliams Center for Cosmology(opens in new window).