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In astronomy, upcoming space telescopes with wide-field optical instruments have a spatially varying point spread function (PSF). Specific scientific goals require a high-fidelity estimation of the PSF at target positions where no direct measurement of the PSF is provided. Even though observations of the PSF are available at some positions of the field of view (FOV), they are undersampled, noisy, and integrated into wavelength in the instrument's passband. PSF modeling represents a challenging ill-posed problem, as it requires building a model from degraded observations that can infer a super-resolved PSF at any wavelength and position in the FOV. Our model, coined WaveDiff, proposes a paradigm shift in the data-driven modeling of the point spread function field of telescopes. We change the data-driven modeling space from the pixels to the wavefront by adding a differentiable optical forward model into the modeling framework. This change allows the transfer of complexity from the instrumental response into the forward model. The proposed model relies on stochastic gradient descent to estimate its parameters. Our framework paves the way to building powerful, physically motivated models that do not require special calibration data. This paper demonstrates the WaveDiff model in a simplified setting of a space telescope. The proposed framework represents a performance breakthrough with respect to the existing state-of-the-art data-driven approach. The pixel reconstruction errors decrease 6-fold at observation resolution and 44-fold for a 3x super-resolution. The ellipticity errors are reduced at least 20 times, and the size error is reduced more than 250 times. By only using noisy broad-band in-focus observations, we successfully capture the PSF chromatic variations due to diffraction. Code available at https://github.com/tobias-liaudat/wf-psf., Comment: Submitted. Without appendix: 42 pages, 10 figures, 4 tables

We propose a paradigm shift in the data-driven modeling of the instrumental response field of telescopes. By adding a differentiable optical forward model into the modeling framework, we change the data-driven modeling space from the pixels to the wavefront. This allows to transfer a great deal of complexity from the instrumental response into the forward model while being able to adapt to the observations, remaining data-driven. Our framework allows a way forward to building powerful models that are physically motivated, interpretable, and that do not require special calibration data. We show that for a simplified setting of a space telescope, this framework represents a real performance breakthrough compared to existing data-driven approaches with reconstruction errors decreasing 5 fold at observation resolution and more than 10 fold for a 3x super-resolution. We successfully model chromatic variations of the instrument's response only using noisy broad-band in-focus observations., Comment: 10 pages. Accepted for the Fourth Workshop on Machine Learning and the Physical Sciences (NeurIPS 2021)

The Infra-Red Telescope (IRT) is part of the payload of the THESEUS mission, which is one of the two ESA M5 candidates within the Cosmic Vision program, planned for launch in 2032. The THESEUS payload, composed by two high energy wide field monitors (SXI and XGIS) and a near infra-red telescope (IRT), is optimized to detect, localize and characterize Gamma-Ray Bursts and other high-energy transients. The main goal of the IRT is to identify and precisely localize the NIR counterparts of the high-energy sources and to measure their distance. Here we present the design of the IRT and its expected performance., Comment: Proceedings of the SPIE 2020, paper 11444-305

We present the B-BOP instrument, a polarimetric camera on board the future ESA-JAXA SPICA far-infrared space observatory. B-BOP will allow the study of the magnetic field in various astrophysical environments thanks to its unprecedented ability to measure the linear polarization of the submillimeter light. The maps produced by B-BOP will contain not only information on total power, but also on the degree and the angle of polarization, simultaneously in three spectral bands (70, 200 and 350 microns). The B-BOP detectors are ultra-sensitive silicon bolometers that are intrinsically sensitive to polarization. Their NEP is close to 10E-18 W/sqrt(Hz). We will present the optical and thermal architectures of the instrument, we will detail the bolometer design and we will show the expected performances of the instrument based on preliminary lab work., Comment: 10 pages, 6 figures, SPIE proceeding: Astronomical Telescopes + Instrumentation 2020