Introducing the Differentiable Universe Initiative

What's the idea

  • Vast amounts of data produced by upcoming surveys
     
  • Controlling systematics is paramount
     
  • All observe the same Universe under various modalities

How do we make the most of the available data ?

What if we could jointly forward simulate these surveys, and use the simulator for inference?

One example:
Weak Lensing

This is a Hierarchical Bayesian Model

aka

a stochastic simulator with some unknown tuning parameters

Advantages and Difficulties

  • Provides a full model for the observations, beyond 2 or 3pt statistics, multiprobe
     
  • Many systematics can now be explicitly modeled as part of  the simulation
     
  • We need to perform inference in a very large number of dimensions

=> We need more  information out of the simulator  to make the inference tractable

Let's build a full end-to-end differentiable model of the Universe

Why now?

  • We are at the dawn of Stage IV surveys, it's a good time to work on novel methodologies
     
  • Significant technological advances, with autodiff framework (like TensorFlow) and hardware acceleration
     
  • Significant methodological advances in machine learning, and inference  methodologies which make these problems tractable
     
  • This is not a new idea,  BCCP members have worked on differentiable simulations and optimization-based inference for years

Why an Initiative?

  • This is a large interdisciplinary task, requires coordination and can use  all the person-power it can get.

     
  • Goals of the Initiative:
    • Develop open source and high-quality software tools
       
    • Foster an open, collaborative, and welcoming environment where people will want to contribute to the effort
       
    • Help coordinate our interdisciplinary efforts towards making tools that can actually be used to analyse surveys.
       

Where we are right now

Introducing the Differentiable Universe Initiative

By eiffl

Introducing the Differentiable Universe Initiative

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