November 27, 2023 to December 1, 2023
Dual node
Europe/Paris timezone

Field-Level Inference with Microcanonical Langevin Monte Carlo

Nov 27, 2023, 3:15 PM
Dual node

Dual node

IAP (Paris) & CCA/Flatiron (New York) IAP 98bis Boulevard Arago 75014 Paris FRANCE CCA/Flatiron 5th Avenue New York (NY) USA
Talk New York Contributed talks


Adrian Bayer (Princeton University / Simons Foundation)


Extracting optimal information from upcoming cosmological surveys is a pressing task, for which a promising path to success is performing field-level inference with differentiable forward modeling. A key computational challenge in this approach is that it requires sampling a high-dimensional parameter space. In this talk I will present a new promising method to sample such large parameter spaces, which improves upon the traditional Hamiltonian Monte Carlo, to both reconstruct the initial conditions of the Universe and obtain cosmological constraints.

Primary author

Adrian Bayer (Princeton University / Simons Foundation)

Presentation materials