| Speaker: |
Shivam Pandey (Johns Hopkins University) |
| Title: |
Building Accelerated Forward Models for the Large-Scale Structure of the Universe |
| Date (JST): |
Thu, Aug 28, 2025, 13:30 - 15:00 |
| Place: |
Seminar Room A |
| Abstract: |
Developing fast and efficient methods for simulating our observable Universe is a key challenge in maximizing information extraction from cosmological datasets. The current simulations are too slow to scale to the volume necessary to analyze even decade-old observations. I will discuss different machine-learning-based approaches (e.g., using a multi-modal, transformer-based architecture) to learn the mapping from approximate and cheap dark matter-only simulations to galaxies in high-resolution and expensive simulations, achieving an orders-of-magnitude acceleration and the ability to cheaply scale to a large volume. I will discuss how these approaches enable the first analysis of large-volume observations of approximately a million galaxies using simulation-based inference techniques to place precise constraints on cosmological models. Finally, I will discuss the potential of these approaches in the context of ongoing and next-generation large-scale cosmological surveys.
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