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[ascl:2209.002] Herculens: Differentiable gravitational lensing

Herculens models imaging data of strong gravitational lenses. The package supports various degrees of model complexity, ranging from standard smooth analytical profiles to pixelated models and machine learning approaches. In particular, it implements multiscale pixelated models regularized with sparsity constraints and wavelet decomposition, for modeling both the source light distribution and the lens potential. The code is fully differentiable - based on JAX (ascl:2111.002) - which enables fast convergence to the solution, access to the parameters covariance matrix, efficient exploration of the parameter space including the sampling of posterior distributions using variational inference or Hamiltonian Monte-Carlo methods.

Code site:
https://github.com/Herculens/herculens
Described in:
https://ui.adsabs.harvard.edu/abs/2022arXiv220705763G
Bibcode:
2022ascl.soft09002G
Preferred citation method:

https://ui.adsabs.harvard.edu/abs/2022arXiv220705763G ; please see additional citation information here: https://github.com/austinpeel/herculens#citation


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ascl:2209.002
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