Python in Science Conference (SciPy)
Published July 10, 2024 | Version v1
Poster Open

gravitational lensing simulations made user friendly with Caustics' three interface levels

Authors/Creators

  • 1. University of Montreal

Contributors

  • 1. GDI
  • 2. SLB
  • 3. University of North Carolina
  • 4. Curvenote
  • 5. Deloitte
  • 6. Aptos
  • 7. Arm

Description

We present Caustics, a tool to accelerate the analysis of gravitational lensing systems for the next generation of astronomical data. Caustics will enable precision measurements of dark matter properties, the expansion rate of the Universe, lensed black holes, the first stars, and more. In this talk I will the benefits and challenges of how we used PyTorch (a differentiable and GPU accelerated scientific python package) to allow for fast development without sacrificing numerical performance. I will detail our development process as well as how we encourage users of all skill levels to engage with our documentation/tools.

Files

Stone_Caustics_SciPy2024.pdf

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