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Register a new userOn-sky verification of Fast and Furious focal-plane wavefront sensing: Moving forward toward controlling the island effect at Subaru/SCExAO
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High-contrast imaging (HCI) observations of exoplanets can be limited by the island effect (IE). On the current generation of telescopes, the IE becomes a severe problem when the ground wind speed is below a few meters per second. This is referred to as the low-wind effect (LWE). The LWE severely distorts the point spread function (PSF), significantly lowering the Strehl ratio and degrading the contrast. In this article, we aim to show that the focal-plane wavefront sensing (FPWFS) algorithm, Fast and Furious (F&F), can be used to measure and correct the IE/LWE. We deployed the algorithm on the SCExAO HCI instrument at the Subaru Telescope using the internal near-infrared camera in H-band. We tested F&F with the internal source, and it was deployed on-sky to test its performance with the full end-to-end system and atmospheric turbulence. The performance of the algorithm was evaluated by two metrics based on the PSF quality: 1) the Strehl ratio approximation ($SRA$), and 2) variance of the normalized first Airy ring ($VAR$). Random LWE phase screens with a peak-to-valley wavefront error between 0.4 $mu$m and 2 $mu$m were all corrected to a $SRA$ $>$90% and an $VARlessapprox0.05$. Furthermore, the on-sky results show that F&F is able to improve the PSF quality during very challenging atmospheric conditions (1.3-1.4 seeing at 500 nm). Closed-loop tests show that F&F is able to improve the $VAR$ from 0.27 to 0.03 and therefore significantly improve the symmetry of the PSF. Simultaneous observations of the PSF in the {optical} ($lambda = $ 750 nm, $Delta lambda =$ 50 nm) show that during these tests we were correcting aberrations common to the optical and NIR paths within SCExAO. Going forward, the algorithm is suitable for incorporation into observing modes, which will enable PSFs of higher quality and stability during science observations.
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Focal plane wavefront sensing is an elegant solution for wavefront sensing since near-focal images of any source taken by a detector show distortions in the presence of aberrations. Non-Common Path Aberrations and the Low Wind Effect both have the ability to limit the achievable contrast of the finest coronagraphs coupled with the best extreme adaptive optics systems. To correct for these aberrations, the Subaru Coronagraphic Extreme Adaptive Optics instrument hosts many focal plane wavefront sensors using detectors as close to the science detector as possible. We present seven of them and compare their implementation and efficiency on SCExAO. This work will be critical for wavefront sensing on next generation of extremely large telescopes that might present similar limitations.
High quality, repeatable point-spread functions are important for science cases like direct exoplanet imaging, high-precision astrometry, and high-resolution spectroscopy of exoplanets. For such demanding applications, the initial on-sky point-spread function delivered by the adaptive optics system can require further optimization to correct unsensed static aberrations and calibration biases. We investigated using the Fast and Furious focal-plane wavefront sensing algorithm as a potential solution. This algorithm uses a simple model of the optical system and focal plane information to measure and correct the point-spread function phase, without using defocused images, meaning it can run concurrently with science. On-sky testing demonstrated significantly improved PSF quality in only a few iterations, with both narrow and broadband filters. These results suggest this algorithm is a useful path forward for creating and maintaining high-quality, repeatable on-sky adaptive optics point-spread functions.
The Low Wind Effect (LWE) refers to a phenomenon that occurs when the wind speed inside a telescope dome drops below $3$m/s creating a temperature gradient near the telescope spider. This produces phase discontinuities in the pupil plane that are not detected by traditional Adaptive Optics (AO) systems such as the pyramid wavefront sensor or the Shack-Hartmann. Considering the pupil as divided in 4 quadrants by regular spiders, the phase discontinuities correspond to piston, tip and tilt aberrations in each quadrant of the pupil. Uncorrected, it strongly decreases the ability of high contrast imaging instruments utilizing coronagraphy to detect exoplanets at small angular separations. Multiple focal plane wavefront sensors are currently being developed and tested on the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) instrument at Subaru Telescope: Among them, the Zernike Asymmetric Pupil (ZAP) wavefront sensor already showed on-sky that it could measure the LWE induced aberrations in focal plane images. The Fast and Furious algorithm, using previous deformable mirror commands as temporal phase diversity, showed in simulations its efficiency to improve the wavefront quality in the presence of LWE. A Neural Network algorithm trained with SCExAO telemetry showed promising PSF prediction on-sky. The Linearized Analytic Phase Diversity (LAPD) algorithm is a solution for multi-aperture cophasing and is studied to correct for the LWE aberrations by considering the Subaru Telescope as a 4 sub-aperture instrument. We present the different algorithms, show the latest results and compare their implementation on SCExAO/SUBARU as real-time wavefront sensors for the LWE compensation.
In this article we show that the vector-Apodizing Phase Plate (vAPP) coronagraph can be designed such that the coronagraphic point spread functions (PSFs) can act as a wavefront sensor to measure and correct the (quasi-)static aberrations, without dedicated wavefront sensing holograms nor modulation by the deformable mirror. The absolute wavefront retrieval is performed with a non-linear algorithm. The focal-plane wavefront sensing (FPWFS) performance of the vAPP and the algorithm are evaluated with numerical simulations, to test various photon and read noise levels, the sensitivity to the 100 lowest Zernike modes and the maximum wavefront error (WFE) that can be accurately estimated in one iteration. We apply these methods to the vAPP within SCExAO, first with the internal source and subsequently on-sky. In idealised simulations we show that for $10^7$ photons the root-mean-square (RMS) WFE can be reduced to $simlambda/1000$, which is 1 nm RMS in the context of the SCExAO system. We find that the maximum WFE that can be corrected in one iteration is $simlambda/8$ RMS or $sim$200 nm RMS (SCExAO). Furthermore, we demonstrate the SCExAO vAPP capabilities by measuring and controlling the lowest 30 Zernike modes with the internal source and on-sky. On-sky, we report a raw contrast improvement of a factor $sim$2 between 2 and 4 $lambda/D$ after 5 iterations of closed-loop correction. When artificially introducing 150 nm RMS WFE, the algorithm corrects it within 5 iterations of closed-loop operation. FPWFS with the vAPPs coronagraphic PSFs is a powerful technique since it integrates coronagraphy and wavefront sensing, eliminating the need for additional probes and thus resulting in a $100%$ science duty cycle and maximum throughput for the target.
The Magellan extreme adaptive optics (MagAO-X) instrument is a new extreme adaptive optics (ExAO) system designed for operation in the visible to near-IR which will deliver high contrast-imaging capabilities. The main AO system will be driven by a pyramid wavefront sensor (PyWFS); however, to mitigate the impact of quasi-static and non-common path (NCP) aberrations, focal plane wavefront sensing (FPWFS) in the form of low-order wavefront sensing (LOWFS) and spatial linear dark field control (LDFC) will be employed behind a vector apodizing phase plate (vAPP) coronagraph using rejected starlight at an intermediate focal plane. These techniques will allow for continuous high-contrast imaging performance at the raw contrast level delivered by the vAPP coronagraph 6 x 10^-5. We present simulation results for LOWFS and spatial LDFC with a vAPP coronagraph, as well as laboratory results for both algorithms implemented with a vAPP coronagraph at the University of Arizona Extreme Wavefront Control Lab.
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