Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userAnti-aliasing Wiener filtering for wave-front reconstruction in the spatial-frequency domain for high-order astronomical adaptive-optics systems
166
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Computationally-efficient wave-front reconstruction techniques for astronomical adaptive optics systems have seen a great development in the past decade. Algorithms developed in the spatial-frequency (Fourier) domain have gathered large attention specially for high-contrast imaging systems. In this paper we present the Wiener filter (resulting in the maximization of the Strehl-ratio) and further develop formulae for the anti-aliasing Wiener filter that optimally takes into account high-order wave-front terms folded in-band during the sensing (i.e. discrete sampling) process. We employ a continuous spatial-frequency representation for the forward measurement operators and derive the Wiener filter when aliasing is explicitly taken into account. We further investigate and compare to classical estimates using least-squares filters the reconstructed wave-front, measurement noise and aliasing propagation coefficients as a function of the system order. Regarding high-contrast systems, we provide achievable performance results as a function of an ensemble of for ward models for the Shack-Hartmann wave-front sensor (using sparse and non-sparse representations) and compute point-spread function raw intensities. We find that for a 32x32 single-conjugated adaptive optics system the aliasing propagation coefficient is roughly 60% of the least-squares filters whereas the noise propagation is around 80%. Contrast improvements of factors of up to 2 are achievable across the field in H-band. For current and next generation high-contrast imagers, despite better aliasing mitigation, anti-aliasing Wiener filtering cannot be used as a stand-alone method and must therefore be used in combination with optical spatial filters deployed before image formation takes actual place.
rate research
Read More
In tomographic adaptive-optics (AO) systems, errors due to tomographic wave-front reconstruction limit the performance and angular size of the scientific field of view (FoV), where AO correction is effective. We propose a multi time-step tomographic wave-front reconstruction method to reduce the tomographic error by using the measurements from both the current and the previous time-steps simultaneously. We further outline the method to feed the reconstructor with both wind speed and direction of each turbulence layer. An end-to-end numerical simulation, assuming a multi-object AO (MOAO) system on a 30 m aperture telescope, shows that the multi time-step reconstruction increases the Strehl ratio (SR) over a scientific FoV of 10 arcminutes in diameter by a factor of 1.5--1.8 when compared to the classical tomographic reconstructor, depending on the guide star asterism and with perfect knowledge of wind speeds and directions. We also evaluate the multi time-step reconstruction method and the wind estimation method on the RAVEN demonstrator under laboratory setting conditions. The wind speeds and directions at multiple atmospheric layers are measured successfully in the laboratory experiment by our wind estimation method with errors below 2 ms. With these wind estimates, the multi time-step reconstructor increases the SR value by a factor of 1.2--1.5, which is consistent with a prediction from end-to-end numerical simulation.
We build on a long-standing tradition in astronomical adaptive optics (AO) of specifying performance metrics and error budgets using linear systems modeling in the spatial-frequency domain. Our goal is to provide a comprehensive tool for the calculation of error budgets in terms of residual temporally filtered phase power spectral densities and variances. In addition, the fast simulation of AO-corrected point spread functions (PSFs) provided by this method can be used as inputs for simulations of science observations with next-generation instruments and telescopes, in particular to predict post-coronagraphic contrast improvements for planet finder systems. We extend the previous results and propose the synthesis of a distributed Kalman filter to mitigate both aniso-servo-lag and aliasing errors whilst minimizing the overall residual variance. We discuss applications to (i) analytic AO-corrected PSF modeling in the spatial-frequency domain, (ii) post-coronagraphic contrast enhancement, (iii) filter optimization for real-time wavefront reconstruction, and (iv) PSF reconstruction from system telemetry. Under perfect knowledge of wind velocities, we show that $sim$60 nm rms error reduction can be achieved with the distributed Kalman filter embodying anti- aliasing reconstructors on 10 m class high-order AO systems, leading to contrast improvement factors of up to three orders of magnitude at few ${lambda}/D$ separations ($sim1-5{lambda}/D$) for a 0 magnitude star and reaching close to one order of magnitude for a 12 magnitude star.
Advanced AO systems will likely utilise Pyramid wave-front sensors (PWFS) over the traditional Shack-Hartmann sensor in the quest for increased sensitivity, peak performance and ultimate contrast. Here, we wish to bring knowledge and quantify the PWFS theoretical limits as a means to highlight its properties and use cases. We explore forward models for the PWFS in the spatial-frequency domain for they prove quite useful since a) they emanate directly from physical-optics (Fourier) diffraction theory; b) provide a straightforward path to meaningful error breakdowns, c) allow for reconstruction algorithms with $O (n,log(n))$ complexity for large-scale systems and d) tie in seamlessly with decoupled (distributed) optimal predictive dynamic control for performance and contrast optimisation. All these aspects are dealt with here. We focus on recent analytical PWFS developments and demonstrate the performance using both analytic and end-to-end simulations. We anchor our estimates with observed on-sky contrast on existing systems and then show very good agreement between analytical and Monte-Carlo estimates for the PWFS. For a potential upgrade of existing high-contrast imagers on 10,m-class telescopes with visible or near-infrared PWFS, we show under median conditions at Paranal a contrast improvement (limited by chromatic and scintillation effects) of 2x-5x by replacing the wave-front sensor alone at large separations close to the AO control radius where aliasing dominates, and factors in excess of 10x by coupling distributed control with the PWFS over most of the AO control region, from small separations starting with the Inner Working Angle of typically 1-2 $lambda/D$ to the AO correction edge (here 20 $lambda/D$).
The forthcoming Extremely Large Telescopes all require adaptive optics systems for their successful operation. The real-time control for these systems becomes computationally challenging, in part limited by the memory bandwidths required for wavefront reconstruction. We investigate new POWER8 processor technologies applied to the problem of real-time control for adaptive optics. These processors have a large memory bandwidth, and we show that they are suitable for operation of first-light ELT instrumentation, and propose some potential real-time control system designs. A CPU-based real-time control system significantly reduces complexity, improves maintainability, and leads to increased longevity for the real-time control system.
For ExAO instruments for the Giant Segmented Mirror Telescopes (GSMTs), alternative architectures of WFS are under consideration because there is a tradeoff between detector size, speed, and noise that reduces the performance of GSMT-ExAO wavefront control. One option under consideration for a GSMT-ExAO wavefront sensor is a three-sided PWFS (3PWFS). The 3PWFS creates three copies of the telescope pupil for wavefront sensing, compared to the conventional four-sided PWFS (4PWFS) which uses four pupils. The 3PWFS uses fewer detector pixels than the 4PWFS and should therefore be less sensitive to read noise. Here we develop a mathematical formalism based on the diffraction theory description of the Foucault knife edge test that predicts the intensity pattern after the PWFS. Our formalism allows us to calculate the intensity in the pupil images formed by the PWFS in the presence of phase errors corresponding to arbitrary Fourier modes. We then use the Object Oriented MATLAB Adaptive Optics toolbox (OOMAO) to simulate an end-to-end model of an adaptive optics system using a PWFS with modulation and compare the performance of the 3PWFS to the 4PWFS. In the case of a low read noise detector, the Strehl ratios of the 3PWFS and 4PWFS are within 0.01. When we included higher read noise in the simulation, we found a Strehl ratio gain of 0.036 for the 3PWFS using Raw Intensity over the 4PWFS using Slopes Maps at a stellar magnitude of 10. At the same magnitude, the 4PWFS RI also outperformed the 4PWFS SM, but the gain was only 0.012 Strehl. This is significant because 4PWFS using Slopes Maps is how the PWFS is conventionally used for AO wavefront sensing. We have found that the 3PWFS is a viable wavefront sensor that can fully reconstruct a wavefront and produce a stable closed-loop with correction comparable to that of a 4PWFS, with modestly better performance for high read-noise detectors.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
