Focal-plane Wavefront Sensing Research Articles

Research on Optical Metrology for Complex Optical Surfaces with Focal Plane Wavefront Sensing.

Complex optical elements have the advantages of improving image quality and optical performance and expanding the field of view. Therefore, it is widely used in X-ray scientific devices, adaptive optical elements, high-energy laser systems, and other fields and is a hot research direction in precision optics. Especially for precision machining, there is a greater need for high-precision testing technology. However, how to measure complex surfaces efficiently and accurately is still an important research topic in optical metrology technology. In order to verify the ability of optical metrology for complex optical surfaces with wavefront sensing based on image information of the focal plane, some experiment platforms in different types of optical surfaces were set up. In order to validate the feasibility and validity of wavefront-sensing technology based on image information of focal planes, a large number of repetitive experiments were carried out. The measurement results with wavefront sensing based on image information of the focal plane were compared with the measurement results with the ZYGO interferometer. The experimental results demonstrate that good agreement is obtained among the error distribution, PV value, and RMS value of the ZYGO interferometer, which shows the feasibility and validity of wavefront sensing based on image information of focal plane technology in optical metrology for the complex optical surface.

A deep learning approach for focal-plane wavefront sensing using vortex phase diversity

Context. The performance of high-contrast imaging instruments is limited by wavefront errors, in particular by non-common path aberrations (NCPAs). Focal-plane wavefront sensing (FPWFS) is appropriate to handle NCPAs because it measures the aberration where it matters the most, that is to say at the science focal plane. Phase retrieval from focal-plane images results, nonetheless, in a sign ambiguity for even modes of the pupil-plane phase. Aims. The phase diversity methods currently used to solve the sign ambiguity tend to reduce the science duty cycle, that is, the fraction of observing time dedicated to science. In this work, we explore how we can combine the phase diversity provided by a vortex coronagraph with modern deep learning techniques to perform efficient FPWFS without losing observing time. Methods. We applied the state-of-the-art convolutional neural network EfficientNet-B4 to infer phase aberrations from simulated focal-plane images. The two cases of scalar and vector vortex coronagraphs (SVC and VVC) were considered using a single post-coronagraphic point spread function (PSF) or two PSFs obtained by splitting the circular polarization states, respectively. Results. The sign ambiguity has been properly lifted in both cases even at low signal-to-noise ratios (S/Ns). Using either the SVC or the VVC, we have reached a very similar performance compared to using phase diversity with a defocused PSF, except for high levels of aberrations where the SVC slightly underperforms compared to the other approaches. The models finally show great robustness when trained on data with a wide range of wavefront errors and noise levels. Conclusions. The proposed FPWFS technique provides a 100% science duty cycle for instruments using a vortex coronagraph and does not require any additional hardware in the case of the SVC.

On-sky verification of Fast and Furious focal-plane wavefront sensing: Moving forward toward controlling the island effect at Subaru/SCExAO

Context. High-contrast imaging (HCI) observations of exoplanets can be limited by the island effect (IE). The IE occurs when the main wavefront sensor (WFS) cannot measure sharp phase discontinuities across the telescope’s secondary mirror support structures (also known as spiders). On the current generation of telescopes, the IE becomes a severe problem when the ground wind speed is below a few meters per second. During these conditions, the air that is in close contact with the spiders cools down and is not blown away. This can create a sharp optical path length difference between light passing on opposite sides of the spiders. Such an IE aberration is not measured by the WFS and is therefore left uncorrected. 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. Aims. 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. The F&F algorithm is a sequential phase diversity algorithm and a software-only solution to FPWFS that only requires access to images of non-coronagraphic PSFs and control of the deformable mirror. Methods. We deployed the algorithm on the SCExAO HCI instrument at the Subaru Telescope using the internal near-infrared camera in H-band. We tested with the internal source to verify that F&F can correct a wide variety of LWE phase screens. Subsequently, F&F 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). The VAR measures the distortion of the first Airy ring, and is used to quantify PSF improvements that do not or barely affect the PSF core (e.g., during challenging atmospheric conditions). Results. The internal source results show that F&F can correct a wide range of LWE phase screens. Random LWE phase screens with a peak-to-valley wavefront error between 0.4 μm and 2 μm were all corrected to a SRA > 90% and an VAR ⪅ 0.05. 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 0.27–0.03 and therefore significantly improve the symmetry of the PSF. Simultaneous observations of the PSF in the optical (λ = 750 nm, Δλ = 50 nm) show that during these tests we were correcting aberrations common to the optical and NIR paths within SCExAO. We could not conclusively determine if we were correcting the LWE and/or (quasi-)static aberrations upstream of SCExAO. Conclusions. The F&F algorithm is a promising focal-plane wavefront sensing technique that has now been successfully tested on-sky. Going forward, the algorithm is suitable for incorporation into observing modes, which will enable PSFs of higher quality and stability during science observations.

Spatial linear dark field control and holographic modal wavefront sensing with a vAPP coronagraph on MagAO-X

The Magellan Extreme Adaptive Optics (MagAO-X) Instrument is an extreme AO system coming online at the end of 2019 that will be operating within the visible and near-IR. With state-of-the-art wavefront sensing and coronagraphy, MagAO-X will be optimized for high-contrast direct exoplanet imaging at challenging visible wavelengths, particularly Hα. To enable high-contrast imaging, the instrument hosts a vector apodizing phase plate (vAPP) coronagraph. The vAPP creates a static region of high contrast next to the star that is referred to as a dark hole; on MagAO-X, the expected dark hole raw contrast is ∼4 × 10 − 6. The ability to maintain this contrast during observations, however, is limited by the presence of non-common path aberrations (NCPA) and the resulting quasi-static speckles that remain unsensed and uncorrected by the primary AO system. These quasi-static speckles within the dark hole degrade the high contrast achieved by the vAPP and dominate the light from an exoplanet. The aim of our efforts here is to demonstrate two focal plane wavefront sensing (FPWFS) techniques for sensing NCPA and suppressing quasi-static speckles in the final focal plane. To sense NCPA to which the primary AO system is blind, the science image is used as a secondary wavefront sensor. With the vAPP, a static high-contrast dark hole is created on one side of the PSF, leaving the opposite side of the PSF unocculted. In this unobscured region, referred to as the bright field, the relationship between modulations in intensity and low-amplitude pupil plane phase aberrations can be approximated as linear. The bright field can therefore be used as a linear wavefront sensor to detect small NCPA and suppress quasi-static speckles. This technique, known as spatial linear dark field control (LDFC), can monitor the bright field for aberrations that will degrade the high-contrast dark hole. A second form of FPWFS, known as holographic modal wavefront sensing (hMWFS), is also employed with the vAPP. This technique uses hologram-generated PSFs in the science image to monitor the presence of low-order aberrations. With LDFC and the hMWFS, high contrast across the dark hole can be maintained over long observations, thereby allowing planet light to remain visible above the stellar noise over the course of observations on MagAO-X. Here, we present simulations and laboratory demonstrations of both spatial LDFC and the hMWFS with a vAPP coronagraph at the University of Arizona Extreme Wavefront Control Laboratory. We show both in simulation and in the lab that the hMWFS can be used to sense low-order aberrations and reduce the wavefront error (WFE) by a factor of 3 − 4 × . We also show in simulation that, in the presence of a temporally evolving pupil plane phase aberration with 27-nm root-mean-square (RMS) WFE, LDFC can reduce the WFE to 18-nm RMS, resulting in factor of 6 to 10 gain in contrast that is kept stable over time. This performance is also verified in the lab, showing that LDFC is capable of returning the dark hole to the average contrast expected under ideal lab conditions. These results demonstrate the power of the hMWFS and spatial LDFC to improve MagAO-X’s high-contrast imaging capabilities for direct exoplanet imaging.

Focal-plane wavefront sensing with the vector-Apodizing Phase Plate

Context.One of the key limitations of the direct imaging of exoplanets at small angular separations are quasi-static speckles that originate from evolving non-common path aberrations (NCPA) in the optical train downstream of the instrument’s main wavefront sensor split-off.Aims.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 wavefront sensors to measure and correct the (quasi-)static aberrations without dedicated wavefront sensing holograms or modulation by the deformable mirror. The absolute wavefront retrieval is performed with a non-linear algorithm.Methods.The focal-plane wavefront sensing (FPWFS) performance of the vAPP and the algorithm are evaluated via 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.Results.In idealized simulations we show that for 107photons the root mean square (rms) WFE can be reduced to ∼λ/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 ∼λ/8 rms or ∼200 nm rms (SCExAO). Furthermore, we demonstrate the SCExAO vAPP capabilities by measuring and controlling the 30 lowest Zernike modes with the internal source and on-sky. On-sky, we report a raw contrast improvement of a factor ∼2 between 2 and 4λ/Dafter five iterations of closed-loop correction. When artificially introducing 150 nm rms WFE, the algorithm corrects it within five iterations of closed-loop operation.Conclusions.FPWFS with the vAPP 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.