Entering a new, data-driven era for precision cosmology: opportunities and challenges for machine learning

Event Date:
2024-12-09T16:00:00
2024-12-09T17:00:00
Event Location:
HENN 318
Speaker:
Laurence Perreault-Levasseur, Université de Montréal
Related Upcoming Events:
Astronomy Colloquia
Intended Audience:
Everyone
Local Contact:

Allison Man (aman@phas.ubc.ca) and Brett Gladman (gladman@astro.ubc.ca)

All are welcome to this event!

Event Information:

Abstract:

Despite the remarkable success of the standard model of cosmology, the inflationary lambda CDM model, at predicting the observed structure of the universe over many scales, very little is known about the fundamental nature of its principal constituents: the inflationary field(s), dark matter, and dark energy. In this talk, I will give a brief overview of the successes of the inflationary lambda CDM model and discuss how, in the coming years, new surveys and telescopes will provide an opportunity to probe these unknown components. These surveys will produce unprecedented volumes of data, the analysis of which can shed light on the equation of state of dark energy, the particle nature of dark matter, and the nature of the inflaton field. The analysis of this data using traditional methods, however, is entirely impractical. I will share my recent work focused on developing machine learning tools for cosmological data analysis and discuss how these tools can help us overcome some of the most important computational challenges of analyzing data from the next generation of sky surveys.

Bio:

Laurence Perreault-Levasseur is the Canada Research Chair in Computational Cosmology and Artificial Intelligence. She is an assistant professor at Université de Montréal and an associate academic member of Mila – Quebec Artificial Intelligence Institute. Perreault-Levasseur’s research focuses on the development and application of machine learning methods to cosmology.

She is also a Visiting Scholar at the Flatiron Institute in New York City. Prior to that, she was a research fellow at their Center for Computational Astrophysics, and a KIPAC postdoctoral fellow at Stanford University.

For her PhD degree at the University of Cambridge, she worked on applications of open effective field theory methods to the formalism of inflation. She completed her BSc and MSc degrees at McGill University.

Learn More:

Add to Calendar 2024-12-09T16:00:00 2024-12-09T17:00:00 Entering a new, data-driven era for precision cosmology: opportunities and challenges for machine learning Event Information: Abstract: Despite the remarkable success of the standard model of cosmology, the inflationary lambda CDM model, at predicting the observed structure of the universe over many scales, very little is known about the fundamental nature of its principal constituents: the inflationary field(s), dark matter, and dark energy. In this talk, I will give a brief overview of the successes of the inflationary lambda CDM model and discuss how, in the coming years, new surveys and telescopes will provide an opportunity to probe these unknown components. These surveys will produce unprecedented volumes of data, the analysis of which can shed light on the equation of state of dark energy, the particle nature of dark matter, and the nature of the inflaton field. The analysis of this data using traditional methods, however, is entirely impractical. I will share my recent work focused on developing machine learning tools for cosmological data analysis and discuss how these tools can help us overcome some of the most important computational challenges of analyzing data from the next generation of sky surveys. Bio: Laurence Perreault-Levasseur is the Canada Research Chair in Computational Cosmology and Artificial Intelligence. She is an assistant professor at Université de Montréal and an associate academic member of Mila – Quebec Artificial Intelligence Institute. Perreault-Levasseur’s research focuses on the development and application of machine learning methods to cosmology. She is also a Visiting Scholar at the Flatiron Institute in New York City. Prior to that, she was a research fellow at their Center for Computational Astrophysics, and a KIPAC postdoctoral fellow at Stanford University. For her PhD degree at the University of Cambridge, she worked on applications of open effective field theory methods to the formalism of inflation. She completed her BSc and MSc degrees at McGill University. Learn More: See her faculty webpage here: Laurence PERREAULT-LEVASSEUR - Département de physique - Université de Montréal Read more about her research here: Laurence Perreault Levasseur – Interaction Event Location: HENN 318