Exoplanet imaging uses coronagraphs to block out the bright light from a star, allowing astronomers to observe the much fainter light from planets orbiting the star. However, these instruments are heavily impacted by small aberrations in the wavefront and require the minimization of starlight residuals directly in the focal plane. Stateof-the art wavefront control methods suffer from errors in the underlying physical models, and often require several iterations to minimize the intensity in the dark hole, limiting performance and reducing effective observation time. This study aims at developing a data-driven method to create a dark hole in post-coronagraphic images. For this purpose, we leverage the model-free capabilities of reinforcement learning to train an agent to learn a control strategy directly from phase diversity images acquired around the focal plane. Initial findings demonstrate successful aberration correction in non-coronagraphic simulations and promising results for dark hole creation in post-coronagraphic scenarios. These results highlight the potential of model-free reinforcement learning for dark-hole creation, justifying further investigation and eventually experimental validation on a dedicated testbed.
To reduce the amount of stellar light for exoplanet detection, coronagraphs feature amplitude masks in pupils plane(s) and/or focal plane(s), where a large fraction of photons are stopped -- and generally not used. Here, we give an overview of where potentially useful stellar (and circumstellar) photons are lost. We review existing concepts that use these lost photons, and propose generic strategies to make use of them for various applications. We particularly focus on wavefront sensing applications, but also explore how these photons can be used for calibration measurements, or for additional scientific observations.
The detection and characterization of Earth-like exoplanets around Sun-like stars is a primary science motivation for the Habitable Worlds Observatory. However, the current best technology is not yet advanced enough to reach the 10−10 contrasts at close angular separations and at the same time remain insensitive to low-order aberrations, as would be required to achieve high-contrast imaging of exo-Earths. Photonic technologies could fill this gap, potentially doubling exo-Earth yield. We review current work on photonic coronagraphs and investigate the potential of hybridized designs which combine both classical coronagraph designs and photonic technologies into a single optical system. We present two possible systems. First, a hybrid solution which splits the field of view spatially such that the photonics handle light within the inner working angle and a conventional coronagraph that suppresses starlight outside it. Second, a hybrid solution where the conventional coronagraph and photonics operate in series, complementing each other and thereby loosening requirements on each subsystem. As photonic technologies continue to advance, a hybrid or fully photonic coronagraph holds great potential for future exoplanet imaging from space.
Looking to the future of exo-Earth imaging from the ground, core technology developments are required in visible Extreme Adaptive Optics (ExAO) to enable the observation of atmospheric features such as oxygen on rocky planets in visible light. UNDERGROUND (Ultra-fast AO techNology Determination for Exoplanet imageRs from the GROUND), a collaboration built in Feb. 2023 at the Optimal Exoplanet Imagers Lorentz Workshop, aims to (1) motivate oxygen detection in Proxima Centauri b and analogs as an informative science case for high-contrast imaging and direct spectroscopy, (2) overview the state of the field with respect to visible exoplanet imagers, and (3) set the instrumental requirements to achieve this goal and identify what key technologies require further development.
New space missions dedicated to exoplanet imaging will rely on coronagraphs to address the high contrast between the stars and their environments. In order to avoid the image of planets to be lost in post-coronagraphic starlight residuals, high precision wavefront sensing and control is a key element to these missions. We present recent results of simultaneous post-coronagraphic phase and amplitude sensing obtained on the THD bench using the coronagraphic phase diversity. We also present results of simulation studies on the non-linear dark hole technique to assess the main limitations of this technique. Finally, we present a first experimental validation of its principle and corroborate expectations on its speed of convergence. These results suggest that the non-linear dark hole is a good candidate for wave-front control for future space-based exoplanet imaging missions, where fast techniques to produce deep dark holes are of paramount importance.
The final performance of current and future instruments dedicated to exoplanet detection and characterization
is limited by intensity residuals in the scientific image plane, which originate in uncorrected optical aberrations.
In order to reach very high contrasts, these aberrations needs to be compensated for. We have proposed a focalplane
wave-font sensor called COFFEE (for COronagraphic Focal-plane wave-Front Estimation for Exoplanet
detection), which consists in an extension of conventional phase diversity to a coronagraphic system. In this
communication, we study the extension of COFFEE to the joint estimation of the phase and the amplitude in
the context of space-based coronagraphic instruments: we optimize the diversity phase in order to minimize the
reconstruction error; we also propose and optimize a novel low-amplitude high-frequency diversity that should
allow the phase-diverse images to still be used for science. Lastly, we perform a first experimental validation of
COFFEE in the very high, space-like contrast conditions of the THD bench and show that COFFEE is able to
distinguish between phase and amplitude aberrations.
The resolution of coronagraphic high contrast exoplanet imaging devices such as SPHERE is limited by quasistatic aberrations. These aberrations produce speckles that can be mistaken for planets in the image. In order to design instruments, correct quasi-static aberrations or analyze data, the expression of the point spread function of a coronagraphic telescope in the presence of residual turbulence is useful. We have derived an analytic formula for this point spread function. We explain physically its structure, we validate it by numerical simulations and we show that it is computationally efficient.
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