Strong Gravitational Lensing in the Era of Data-Driven Algorithms
APA
Hezaveh, Y. (2022). Strong Gravitational Lensing in the Era of Data-Driven Algorithms. Perimeter Institute. https://pirsa.org/22100091
MLA
Hezaveh, Yashar. Strong Gravitational Lensing in the Era of Data-Driven Algorithms. Perimeter Institute, Oct. 04, 2022, https://pirsa.org/22100091
BibTex
@misc{ pirsa_PIRSA:22100091, doi = {10.48660/22100091}, url = {https://pirsa.org/22100091}, author = {Hezaveh, Yashar}, keywords = {Cosmology}, language = {en}, title = {Strong Gravitational Lensing in the Era of Data-Driven Algorithms}, publisher = {Perimeter Institute}, year = {2022}, month = {oct}, note = {PIRSA:22100091 see, \url{https://pirsa.org}} }
In this talk I will share our recent work in developing statistical models based on machine learning methods. In particular, I will discuss posterior sampling in low- and high-dimensional spaces and connect this to two ongoing projects: measuring the small-scale distribution of dark matter and estimating the expansion rate of the Universe. I will discuss how the speed and the accuracy gained by these models are essential for the large volumes of data from the next generation sky surveys. I will finish by mentioning a few other projects and a new initiative for interdisciplinary collaboration in astrophysics and data sciences.
Zoom link: https://pitp.zoom.us/j/98316228305?pwd=UWwrZkIwUG1QZFBkYzc1eVdNSW1Ldz09