Differentiable optics with a Lux: I - deep calibration of flat field and phase retrieval with automatic differentiation
Article
Desdoigts, Louis, Pope, Benjamin J. S., Dennis, Jordan and Tuthill, Peter G.. 2023. "Differentiable optics with a Lux: I - deep calibration of flat field and phase retrieval with automatic differentiation." Journal of Astronomical Telescopes, Instruments, and Systems. 9 (2). https://doi.org/10.1117/1.JATIS.9.2.028007
| Article Title | Differentiable optics with a Lux: I - deep calibration of flat field and phase retrieval with automatic differentiation |
|---|---|
| ERA Journal ID | 210799 |
| Article Category | Article |
| Authors | Desdoigts, Louis, Pope, Benjamin J. S., Dennis, Jordan and Tuthill, Peter G. |
| Journal Title | Journal of Astronomical Telescopes, Instruments, and Systems |
| Journal Citation | 9 (2) |
| Article Number | 028007 |
| Number of Pages | 13 |
| Year | 2023 |
| Publisher | SPIE - International Society for Optical Engineering |
| Place of Publication | United States |
| ISSN | 2329-4124 |
| 2329-4221 | |
| Digital Object Identifier (DOI) | https://doi.org/10.1117/1.JATIS.9.2.028007 |
| Web Address (URL) | https://www.spiedigitallibrary.org/journals/Journal-of-Astronomical-Telescopes-Instruments-and-Systems/volume-9/issue-2/028007/Differentiable-optics-with-Lux--Ideep-calibration-of-flat-field/10.1117/1.JATIS.9.2.028007.short |
| Abstract | The sensitivity limits of space telescopes are imposed by uncalibrated errors in the point spread function, photon-noise, background light, and detector sensitivity. These are typically calibrated with specialized wavefront sensor hardware and with flat fields obtained on the ground or with calibration sources, but these leave vulnerabilities to residual time-varying or non-common path aberrations and variations in the detector conditions. It is, therefore, desirable to infer these from science data alone, facing the prohibitively high dimensional problems of phase retrieval and pixel-level calibration. We introduce a new Python package for physical optics simulation, ∂ Lux, which uses the machine learning framework Jax to achieve graphics processing unit acceleration and automatic differentiation (autodiff), and apply this to simulating astronomical imaging. In this first of a series of papers, we show that gradient descent enabled by autodiff can be used to simultaneously perform phase retrieval and calibration of detector sensitivity, scaling efficiently to inferring millions of parameters. This new framework enables high dimensional optimization and inference in data analysis and hardware design in astronomy and beyond, which we explore in subsequent papers in this series. |
| Keywords | detectors; phase retrieval; simulations; diffractiveoptics |
| ANZSRC Field of Research 2020 | 5101. Astronomical sciences |
| Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
| Byline Affiliations | University of Sydney |
| University of Queensland | |
| University of Southern Queensland |
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