Showing papers on "Adaptive optics published in 2020"

Adaptive optics with an infrared pyramid wavefront sensor at Keck

Abstract: The study of cold or obscured, red astrophysical sources can significantly benefit from adaptive optics (AO) systems employing infrared (IR) wavefront sensors. One particular area is the study of exoplanets around M-dwarf stars and planet formation within protoplanetary disks in star-forming regions. Such objects are faint at visible wavelengths but bright enough in the IR to be used as a natural guide star for the AO system. Doing the wavefront sensing at IR wavelengths enables high-resolution AO correction for such science cases, with the potential to reach the contrasts required for direct imaging of exoplanets. To this end, a new near-infrared pyramid wavefront sensor (PyWFS) has been added to the Keck II AO system, extending the performance of the facility AO system for the study of faint red objects. We present the Keck II PyWFS, which represents a number of firsts, including the first PyWFS installed on a segmented telescope and the first use of an IR PyWFS on a 10-m class telescope. We discuss the scientific and technological advantages offered by IR wavefront sensing and present the design and commissioning of the Keck PyWFS. In particular, we report on the performance of the Selex Avalanche Photodiode for HgCdTe InfraRed Array detector used for the PyWFS and highlight the novelty of this wavefront sensor in terms of the performance for faint red objects and the improvement in contrast. The system has been commissioned for science with the vortex coronagraph in the NIRC2 IR science instrument and is being commissioned alongside a new fiber injection unit for NIRSPEC. We present the first science verification of the system—to facilitate the study of exoplanets around M-type stars.

Adaptive optics two-photon microscopy enables near-diffraction-limited and functional retinal imaging in vivo

Abstract: In vivo fundus imaging offers non-invasive access to neuron structures and biochemical processes in the retina. However, optical aberrations of the eye degrade the imaging resolution and prevent visualization of subcellular retinal structures. We developed an adaptive optics two-photon excitation fluorescence microscopy (AO-TPEFM) system to correct ocular aberrations based on a nonlinear fluorescent guide star and achieved subcellular resolution for in vivo fluorescence imaging of the mouse retina. With accurate wavefront sensing and rapid aberration correction, AO-TPEFM permits structural and functional imaging of the mouse retina with submicron resolution. Specifically, simultaneous functional calcium imaging of neuronal somas and dendrites was demonstrated. Moreover, the time-lapse morphological alteration and dynamics of microglia were characterized in a mouse model of retinal disorder. In addition, precise laser axotomy was achieved, and degeneration of retinal nerve fibres was studied. This high-resolution AO-TPEFM is a promising tool for non-invasive retinal imaging and can facilitate the understanding of a variety of eye diseases as well as neurodegenerative disorders in the central nervous system.

High-speed adaptive optics line-scan OCT for cellular-resolution optoretinography

Abstract: Optoretinography–the non-invasive, optical imaging of light-induced functional activity in the retina–stands to provide a critical biomarker for testing the safety and efficacy of new therapies as well as their rapid translation to the clinic. Optical phase change in response to light, as readily accessible in phase-resolved OCT, offers a path towards all-optical imaging of retinal function. However, typical human eye motion adversely affects phase stability. In addition, recording fast light-induced retinal events necessitates high-speed acquisition. Here, we introduce a high-speed line-scan spectral domain OCT with adaptive optics (AO), aimed at volumetric imaging and phase-resolved acquisition of retinal responses to light. By virtue of parallel acquisition of an entire retinal cross-section (B-scan) in a single high-speed camera frame, depth-resolved tomograms at speeds up to 16 kHz were achieved with high sensitivity and phase stability. To optimize spectral and spatial resolution, an anamorphic detection paradigm was introduced, enabling improved light collection efficiency and signal roll-off compared to traditional methods. The benefits in speed, resolution and sensitivity were exemplified in imaging nanometer-millisecond scale light-induced optical path length changes in cone photoreceptor outer segments. With 660 nm stimuli, individual cone responses readily segregated into three clusters, corresponding to long, middle, and short-wavelength cones. Recording such optoretinograms on spatial scales ranging from individual cones, to 100 µm-wide retinal patches offers a robust and sensitive biomarker for cone function in health and disease.

Distortion matrix concept for deep optical imaging in scattering media.

Abstract: In optical imaging, light propagation is affected by the inhomogeneities of the medium. Sample-induced aberrations and multiple scattering can strongly degrade the image resolution and contrast. On the basis of a dynamic correction of the incident and/or reflected wavefronts, adaptive optics has been used to compensate for those aberrations. However, it only applies to spatially invariant aberrations or to thin aberrating layers. Here, we propose a global and noninvasive approach based on the distortion matrix concept. This matrix basically connects any focusing point of the image with the distorted part of its wavefront in reflection. A singular value decomposition of the distortion matrix allows to correct for high-order aberrations and forward multiple scattering over multiple isoplanatic modes. Proof-of-concept experiments are performed through biological tissues including a turbid cornea. We demonstrate a Strehl ratio enhancement up to 2500 and recover a diffraction-limited resolution until a depth of 10 scattering mean free paths.

High-resolution in-vivo human retinal imaging using full-field OCT with optical stabilization of axial motion

Abstract: Time-domain full-field OCT (FF-OCT) represents an imaging modality capable of recording high-speed en-face sections of a sample at a given depth. One of the biggest challenges to transfer this technique to image in-vivo human retina is the presence of continuous involuntary head and eye axial motion during image acquisition. In this paper, we demonstrate a solution to this problem by implementing an optical stabilization in an FF-OCT system. This was made possible by combining an FF-OCT system, an SD-OCT system, and a high-speed voice-coil translation stage. B-scans generated by the SD-OCT were used to measure the retina axial position and to drive the position of the high-speed voice coil translation stage, where the FF-OCT reference arm is mounted. Closed-loop optical stabilization reduced the RMS error by a factor of 7, significantly increasing the FF-OCT image acquisition efficiency. By these means, we demonstrate the capacity of the FF-OCT to resolve cone mosaic as close as 1.5 o from the fovea center with high consistency and without using adaptive optics.

A Deep Learning Approach to Photoacoustic Wavefront Localization in Deep-Tissue Medium

Abstract: Optical photons undergo strong scattering when propagating beyond 1-mm deep inside biological tissue. Finding the origin of these diffused optical wavefronts is a challenging task. Breaking through the optical diffusion limit, photoacoustic (PA) imaging (PAI) provides high-resolution and label-free images of human vasculature with high contrast due to the optical absorption of hemoglobin. In real-time PAI, an ultrasound transducer array detects PA signals, and B-mode images are formed by delay-and-sum or frequency-domain beamforming. Fundamentally, the strength of a PA signal is proportional to the local optical fluence, which decreases with the increasing depth due to depth-dependent optical attenuation. This limits the visibility of deep-tissue vasculature or other light-absorbing PA targets. To address this practical challenge, an encoder–decoder convolutional neural network architecture was constructed with custom modules and trained to identify the origin of the PA wavefronts inside an optically scattering deep-tissue medium. A comprehensive ablation study provides strong evidence that each module improves the localization accuracy. The network was trained on model-based simulated PA signals produced by 16 240 blood-vessel targets subjected to both optical scattering and Gaussian noise. Test results on 4600 simulated and five experimental PA signals collected under various scattering conditions show that the network can localize the targets with a mean error less than 30 microns (standard deviation 20.9 microns) for targets below 40-mm imaging depth and 1.06 mm (standard deviation 2.68 mm) for targets at a depth between 40 and 60 mm. The proposed work has broad applications such as diffused optical wavefront shaping, circulating melanoma cell detection, and real-time vascular surgeries (e.g., deep-vein thrombosis).

Indoor Mixed Dual-Hop VLC/RF Systems Through Reconfigurable Intelligent Surfaces

Abstract: In this letter, a reconfigurable intelligent surface (RIS)-assisted dual-hop visible light communication (VLC)/radio frequency (RF) system in indoor scenarios is proposed, in which the first link is a VLC link while an RIS is deployed in the second RF link. More specifically, a relay first converts the received optical signal into the RF signal blue using either decode-and-forward or amplify-and-forward protocols and then forwards it to the RIS. The RIS alters the electromagnetic response of the impinging waves to provide connectivity between the RF destination and optical source. Based on this model, closed-form expressions for the outage probability and bit error rate (BER) are derived. Also, an asymptotic analysis for the outage probability is presented. Finally, simulation results are provided to verify our analytical results.

Fast widefield imaging of neuronal structure and function with optical sectioning in vivo

Abstract: Optical microscopy, owing to its noninvasiveness and subcellular resolution, enables in vivo visualization of neuronal structure and function in the physiological context. Optical-sectioning structured illumination microscopy (OS-SIM) is a widefield fluorescence imaging technique that uses structured illumination patterns to encode in-focus structures and optically sections 3D samples. However, its application to in vivo imaging has been limited. In this study, we optimized OS-SIM for in vivo neural imaging. We modified OS-SIM reconstruction algorithms to improve signal-to-noise ratio and correct motion-induced artifacts in live samples. Incorporating an adaptive optics (AO) module to OS-SIM, we found that correcting sample-induced optical aberrations was essential for achieving accurate structural and functional characterizations in vivo. With AO OS-SIM, we demonstrated fast, high-resolution in vivo imaging with optical sectioning for structural imaging of mouse cortical neurons and zebrafish larval motor neurons, and functional imaging of quantal synaptic transmission at Drosophila larval neuromuscular junctions.

Turbulence aberration correction for vector vortex beams using deep neural networks on experimental data.

Abstract: The vector vortex beams (VVB) possessing non-separable states of light, in which polarization and orbital angular momentum (OAM) are coupled, have attracted more and more attentions in science and technology, due to the unique nature of the light field. However, atmospheric transmission distortion is a recurring challenge hampering the practical application, such as communication and imaging. In this work, we built a deep learning based adaptive optics system to compensate the turbulence aberrations of the vector vortex mode in terms of phase distribution and mode purity. A turbulence aberration correction convolutional neural network (TACCNN) model, which can learn the mapping relationship of intensity profile of the distorted vector vortex modes and the turbulence phase generated by first 20 Zernike modes, is well designed. After supervised learning plentiful experimental samples, the TACCNN model compensates turbulence aberration for VVB quickly and accurately. For the first time, experimental results show that through correction, the mode purity of the distorted VVB improves from 19% to 70% under the turbulence strength of D/r0 = 5.28 with correction time 100 ms. Furthermore, both spatial modes and the light intensity distribution can be well compensated in different atmospheric turbulence.

MAORY: the adaptive optics module for the Extremely Large Telescope (ELT)

Abstract: MAORY is a post-focal adaptive optics module that forms part of the first light instrument suite for the ELT. The main function of MAORY is to relay the light beam from the ELT focal plane to the client instrument while compensating the effects of the atmospheric turbulence and other disturbances affecting the wavefront from the scientific sources of interest.

Cellular-Scale Imaging of Transparent Retinal Structures and Processes Using Adaptive Optics Optical Coherence Tomography.

Abstract: High-resolution retinal imaging is revolutionizing how scientists and clinicians study the retina on the cellular scale. Its exquisite sensitivity enables time-lapse optical biopsies that capture minute changes in the structure and physiological processes of cells in the living eye. This information is increasingly used to detect disease onset and monitor disease progression during early stages, raising the possibility of personalized eye care. Powerful high-resolution imaging tools have been in development for more than two decades; one that has garnered considerable interest in recent years is optical coherence tomography enhanced with adaptive optics. State-of-the-art adaptive optics optical coherence tomography (AO-OCT) makes it possible to visualize even highly transparent cells and measure some of their internal processes at all depths within the retina, permitting reconstruction of a 3D view of the living microscopic retina. In this review, we report current AO-OCT performance and its success in visualizing and quantifying these once-invisible cells in human eyes.

Direct determination of aberration functions in microscopy by an artificial neural network

Abstract: Adaptive optics relies on the fast and accurate determination of aberrations but is often hindered by wavefront sensor limitations or lengthy optimization algorithms. Deep learning by artificial neural networks has recently been shown to provide determination of aberration coefficients from various microscope metrics. Here we numerically investigate the direct determination of aberration functions in the pupil plane of a high numerical aperture microscope using an artificial neural network. We show that an aberration function can be determined from fluorescent guide stars and used to improve the Strehl ratio without the need for reconstruction from Zernike polynomial coefficients.

VIPR: vectorial implementation of phase retrieval for fast and accurate microscopic pixel-wise pupil estimation.

Abstract: In microscopy, proper modeling of the image formation has a substantial effect on the precision and accuracy in localization experiments and facilitates the correction of aberrations in adaptive optics experiments. The observed images are subject to polarization effects, refractive index variations, and system specific constraints. Previously reported techniques have addressed these challenges by using complicated calibration samples, computationally heavy numerical algorithms, and various mathematical simplifications. In this work, we present a phase retrieval approach based on an analytical derivation of the vectorial diffraction model. Our method produces an accurate estimate of the system’s phase information, without any prior knowledge about the aberrations, in under a minute.

MagAO-X first light

Abstract: MagAO-X is a new “extreme” adaptive optics system for the Magellan Clay 6.5 m telescope which began commissioning in December, 2019. MagAO-X is based around a 2040 actuator deformable mirror, controlled by a pyramid wavefront sensor operating at up to 3.6 kHz. When fully optimized, MagAO-X will deliver high Strehls (< 70%), high resolution (19 mas), and high contrast (< 1 × 10−4) at Hα (656 nm). We present a brief review of the instrument design and operations, and then report on the results of the first-light run.

Practical sensorless aberration estimation for 3D microscopy with deep learning.

Abstract: Estimation of optical aberrations from volumetric intensity images is a key step in sensorless adaptive optics for 3D microscopy. Recent approaches based on deep learning promise accurate results at fast processing speeds. However, collecting ground truth microscopy data for training the network is typically very difficult or even impossible thereby limiting this approach in practice. Here, we demonstrate that neural networks trained only on simulated data yield accurate predictions for real experimental images. We validate our approach on simulated and experimental datasets acquired with two different microscopy modalities and also compare the results to non-learned methods. Additionally, we study the predictability of individual aberrations with respect to their data requirements and find that the symmetry of the wavefront plays a crucial role. Finally, we make our implementation freely available as open source software in Python.

Origin of cell contrast in offset aperture adaptive optics ophthalmoscopy.

Abstract: Offset aperture and split detector imaging are variants of adaptive optics scanning ophthalmoscopy recently introduced to improve the image contrast of retinal cells. Unlike conventional confocal scanning ophthalmoscopy, these approaches collect light laterally decentered from the optical axis. A complete explanation of how these methods enhance contrast has not been described. Here, we provide an optical model with supporting in vivo data that show contrast is generated from spatial variations in the refractive index as it is in phase contrast microscopy. A prediction of this model is supported by experimental data that show contrast is optimized when the detector is placed conjugate with a deeper backscattering screen such as the retinal pigment epithelium and choroid, rather than with the layer being imaged as in conventional confocal imaging. This detection strategy provides a substantial improvement in the contrast these new methods can produce.

Improving system performance by using adaptive optics and aperture averaging for laser communications in oceanic turbulence.

Abstract: We theoretically investigate the effectiveness of adaptive optics correction for Gaussian beams affected by oceanic turbulence. Action of an idealized adaptive optics system is modeled as a perfect removal of a certain number of Zernike modes from the aberrated wavefront. We focused on direct detection systems and we used the aperture-averaged scintillation as the main metric to evaluate optical system performances. We found that, similar to laser beam propagation in atmospheric turbulence, adaptive optics is very effective in improving the performance of laser communication links if an optimum aperture size is used. For the specific cases we analyzed in this study, scintillation was reduced by a factor of ∼7 when 15 modes were removed and when the aperture size of the transceiver was large enough to capture 4-5 speckles of the oceanic turbulence-affected beam.

Intensity-enhanced deep network wavefront reconstruction in Shack-Hartmann sensors.

Abstract: The Shack–Hartmann wavefront sensor (SH-WFS) is known to produce incorrect measurements of the wavefront gradient in the presence of non-uniform illumination. Moreover, the most common least-squares phase reconstructors cannot accurately reconstruct the wavefront in the presence of branch points. We therefore developed the intensity/slopes network (ISNet), a deep convolutional-neural-network-based reconstructor that uses both the wavefront gradient information and the intensity of the SH-WFS’s subapertures to provide better wavefront reconstruction. We trained the network on simulated data with multiple levels of turbulence and compared the performance of our reconstructor to several other reconstruction techniques. ISNet produced the lowest wavefront error of the reconstructors we evaluated and operated at a speed suitable for real-time applications, enabling the use of the SH-WFS in stronger turbulence than was previously possible.

On-sky correction of non-common path aberration with the pyramid wavefront sensor

Abstract: The paper deals with with the on-sky performance of the pyramid wavefront sensor-based Adaptive Optics (AO) systems. These wavefront sensors are of great importance, being used in all first light AO systems of the ELTs (E-ELT, GMT, and TMT), currently in design phase. In particular, non-common path aberrations (NCPAs) are a critical issue encountered when using an AO system to produce corrected images in an associated astronomical instrument. The AO wavefront sensor (WFS) and the supported scientific instrument typically use a series of different optical elements, thus experiencing different aberrations. The usual way to correct for such NCPAs is to introduce a static offset in the WFS signals. In this way, when the AO loop is closed the sensor offsets are zeroed and the deformable mirror converges to the shape required to null the NCPA. The method assumes that the WFS operation is linear and completely described by some pre-calibrated interaction matrix. This is not the case for some frequently used wavefront sensors like the Pyramid sensor or a quad-cell Shack-Hartmann sensor. Here we present a method to work in closed-loop with a pyramid wavefront sensor, or more generally a non-linear WFS, introducing a wavefront offset that remains stable when AO correction quality changes due to variations in external conditions like star brightness, seeing, and wind speed. The paper details the methods with analytical and numerical considerations. Then we present results of tests executed at the LBT telescope, in daytime and on sky, using the FLAO system and LUCI2 facility instrument. The on-sky results clearly show the successful operation of the method that completely nulls NCPA, recovering diffraction-limited images with about 70% Strehl ratio in H band in variable seeing conditions. The proposed method is suitable for application to the above-mentioned ELT AO systems.

Fiber laser transceiving and wavefront aberration mitigation with adaptive distributed aperture array for free-space optical communications.

Abstract: In this Letter, we propose and demonstrate efficient adaptive optics correction of a distributed 19-element fiber laser array for both receiving and transmission for the first time, to our best knowledge. Active beam coupling from space into polarization-maintaining fibers and all-fiber active cophasing beam combining with multiple-level fiber couplers are performed. Phase distortions distributed throughout the optical path from the simulated target to the receiving port are eliminated, and nearly ideal coherent combining is achieved in the far-field. Comprehensive reception efficiency is raised up to 52 times with the whole equivalent aperture of 152 mm and the far-field power-in-the-bucket metric up to 8.27 times. The optimal array element parameters for a given whole array aperture and turbulence intensity are analyzed.

Adaptive optics two-photon endomicroscopy enables deep-brain imaging at synaptic resolution over large volumes

Abstract: Optical deep-brain imaging in vivo at high resolution has remained a great challenge over the decades. Two-photon endomicroscopy provides a minimally invasive approach to image buried brain structures, once it is integrated with a gradient refractive index (GRIN) lens embedded in the brain. However, its imaging resolution and field of view are compromised by the intrinsic aberrations of the GRIN lens. Here, we develop a two-photon endomicroscopy by adding adaptive optics based on direct wavefront sensing, which enables recovery of diffraction-limited resolution in deep-brain imaging. A new precompensation strategy plays a critical role to correct aberrations over large volumes and achieve rapid random-access multiplane imaging. We investigate the neuronal plasticity in the hippocampus, a critical deep brain structure, and reveal the relationship between the somatic and dendritic activity of pyramidal neurons.

Filtering techniques to enhance optical turbulence forecast performances at short time-scales

Abstract: The efficiency of the management of top-class ground-based astronomical facilities supported by Adaptive Optics (AO) relies on our ability to forecast the optical turbulence (OT) and a set of relevant atmospheric parameters. Indeed, in spite of the fact that the AO is able to achieve, at present, excellent levels of wavefront corrections (a Strehl Ratio up to 90% in H band), its performances strongly depend on the atmospheric conditions. Knowing in advance the turbulence conditions allows an optimization of the AO use. It has already been proven that it is possible to provide reliable forecasts of the optical turbulence (CN2 profiles and integrated astroclimatic parameters such as seeing, isoplanantic angle, wavefront coherence time, ...) for the next night. In this paper we prove that it is possible to improve the forecast performances on shorter time scales (order of one or two hours) with consistent gains (order of 2 to 8) using filtering techniques. This has permitted us to achieve forecasts accuracies never obtained before and reach a fundamental milestone for the astronomical applications. The time scale of one or two hours is the most critical one for an efficient management of the ground-based telescopes supported by AO. Results shown here open, therefore, to an important revolution in the field. We implemented this method in the operational forecast system of the Large Binocular Telescope, named ALTA Center that is, at our knowledge, the first operational system providing forecasts of turbulence and atmospheric parameters at short time scales to support science operations.

An all-photonic focal-plane wavefront sensor.

Abstract: Adaptive optics (AO) is critical in astronomy, optical communications and remote sensing to deal with the rapid blurring caused by the Earth’s turbulent atmosphere. But current AO systems are limited by their wavefront sensors, which need to be in an optical plane non-common to the science image and are insensitive to certain wavefront-error modes. Here we present a wavefront sensor based on a photonic lantern fibre-mode-converter and deep learning, which can be placed at the same focal plane as the science image, and is optimal for single-mode fibre injection. By measuring the intensities of an array of single-mode outputs, both phase and amplitude information on the incident wavefront can be reconstructed. We demonstrate the concept with simulations and an experimental realisation wherein Zernike wavefront errors are recovered from focal-plane measurements to a precision of 5.1 × 10−3 π radians root-mean-squared-error. Adaptive optics wavefront sensors need to be in a pupil plane and are insensitive to certain wavefront-error modes. The authors present a wavefront sensor based on a photonic lantern fibre-mode-converter and deep learning, which can be placed at the same focal plane accessing nondegenerate wavefront information and reconstructing the wavefront.

Deep learning assisted Shack-Hartmann wavefront sensor for direct wavefront detection.

Abstract: The conventional Shack–Hartmann wavefront sensor (SHWS) requires wavefront slope measurements of every micro-lens for wavefront reconstruction. In this Letter, we applied deep learning on the SHWS to directly predict the wavefront distributions without wavefront slope measurements. The results show that our method could provide a lower root mean square wavefront error in high detection speed. The performance of the proposed method is also evaluated on challenging wavefronts, while the conventional approaches perform insufficiently. This Letter provides a new approach, to the best of our knowledge, to perform direct wavefront detection in SHWS-based applications.

Depth-resolved optimization of a real-time sensorless adaptive optics optical coherence tomography

Abstract: Sensorless adaptive optics optical coherence tomography (AO-OCT) is a technology to image retinal tissue with high resolution by compensating ocular aberrations without wavefront sensors. In this Letter, a fast and robust hill-climbing algorithm is developed to optimize five Zernike modes in AO-OCT with a numerical aperture between that of conventional AO and commercial OCT systems. The merit function is generated in real time using graphics processing unit while axially tracking the retinal layer of interest. A new method is proposed to estimate the largest achievable field of view for which aberrations are corrected uniformly in sensorless AO-OCT.

Wide field-of-view, high-resolution Solar observation in combination with ground layer adaptive optics and speckle imaging

Abstract: Context. High angular resolution images at a wide field of view are required for investigating Solar physics and predicting space weather. Ground-based observations are often subject to adaptive optics (AO) correction and post-facto reconstruction techniques to improve the spatial resolution. The combination of ground layer adaptive optics (GLAO) and speckle imaging is appealing with regard to a simplification of the correction and the high resolution of the reconstruction. The speckle transfer functions (STFs) used in the speckle image reconstruction mainly determine the photometric accuracy of the recovered result. The STF model proposed by Friedrich Woger and Oskar von der Luhe in the classical AO condition is generic enough to accommodate the GLAO condition if correct inputs are given. Thus, the precisely calculated inputs to the model STF are essential for the final results. The necessary input for the model STF is the correction efficiency which can be calculated simply with the assumption of one layer turbulence. The method for calculating the correction efficiency for the classical AO condition should also be improved to suit the GLAO condition. The generic average height of the turbulence layer used by Friedrich Woger and Oskar von der Luhe in the classic AO correction may lead to reduced accuracy and should be revised to improve photometric accuracy.Aims. This study is aimed at obtaining quantitative photometric reconstructed images in the GLAO condition. We propose methods for extracting the appropriate inputs for the STF model.Methods. In this paper, the telemetry data of the GLAO system was used to extract the correction efficiency and the equivalent height of the turbulence. To analyze the photometric accuracy of the method, the influence resulting from the distribution of the atmospheric turbulence profile and the extension of the guide stars are investigated by simulations. At those simulations, we computed the STF from the wavefront phases and convolved it with the high-resolution numerical simulations of the solar photosphere. We then deconvolved them with the model STF calculated from the correction efficiency and the equivalent height to obtain a reconstructed image. To compute the resulting photometric precision, we compared the intensity of the original image with the reconstructed image. We reconstructed the solar images taken by the GLAO prototype system at the New Vacuum Solar Telescope of the Yunnan Astronomical Observatory using this method and analyzed the results.Results. These simulations and ensuing analysis demonstrate that high photometric precision can be obtained for speckle amplitude reconstruction using the inputs for the model STF derived from the telemetry data of the GLAO system.

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

Abstract: 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 $VAR\lessapprox0.05$. 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.

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

Abstract: 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 μ m and 2 μ m 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.

Multi-Node Optical Frequency Dissemination With Post Automatic Phase Correction

Abstract: We report a technique for coherence transfer of laser light through a fiber link, where the optical phase noise induced by environmental perturbations via the fiber link is compensated by remote users with passive phase noise correction, rather than at the local site as is conventional. Neither phase discrimination nor active phase tracking is required due to the open-loop design, mitigating some technical problems such as the limited compensation speed and the finite compensation precision as conventional active phase noise cancellation. We theoretically analyze and experimentally demonstrate that the delay-limited residual fiber phase noise after phase noise compensation is a factor of seven higher than the conventional techniques. Using this technique, we demonstrate the transfer laser light through a 145-km-long, lab-based spooled fiber. After being compensated, a relative frequency instability is $1.9\times 10^{-15}$ at the integration time of 1 s and scales down to the level of $10^{-18}$ -range at 10,000 s. The frequency uncertainty of the light after transferring through the fiber relative to that of the input light is $(-0.36\pm 2.6)\times 10^{-18}$ . As the transmitted optical signal remains unaltered until it reaches the remote sites, it can be transmitted simultaneously to multiple remote sites on an arbitrarily complex fiber network, paving a way to develop a multi-node optical frequency dissemination system with post automatic phase noise correction for a number of end-users.