GIGA-Lens: Fast Bayesian Inference for Strong Gravitational Lens Modeling

Understand

We present GIGA-Lens: a gradient-informed, GPU-accelerated Bayesian framework for modeling strong gravitational lensing systems, implemented in TensorFlow and JAX.

• The three components, optimization using multi-start gradient descent, posterior covariance estimation with variational inference, and sampling via Hamiltonian Monte Carlo, all take advantage of gradient information through automatic differentiation and massive parallelization on graphics processing units (GPUs).
• We test our pipeline on a large set of simulated systems and demonstrate in detail its high level of performance.
• The average time to model a single system on four Nvidia A100 GPUs is 105 seconds.