The minimum of the time-delay wavefront error in Adaptive Optics

Doelman, Niek

doi:10.1093/mnras/stz3237

Cited by 5 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The modest improvement is aligned with the results from Doelman (2019). 31 Operating at 1kHz, the turbulence moves less than 1 sub-aperture each frame. Hence, it is more relevant to think of each sub-aperture as a time series than to consider the spatial correlations between sub-apertures as done using Frozen Flow Hypothesis.…”

Section: Daytime Testingmentioning

confidence: 99%

Predictive wavefront control on Keck II adaptive optics bench: on-sky coronagraphic results

Kooten¹,

Cetre²,

Ragland³

et al. 2022

Preprint

View full text Add to dashboard Cite

The behavior of an adaptive optics (AO) system for ground-based high contrast imaging (HCI) dictates the achievable contrast of the instrument. In conditions where the coherence time of the atmosphere is short compared to the speed of the AO system, the servo-lag error can become the dominant error term of the AO system. While the AO system measures the wavefront error and subsequently applies a correction (typically taking a total of one or a few milliseconds), the atmospheric turbulence above the telescope has changed resulting in the servolag error. In addition to reducing the Strehl ratio, the servo-lag error causes a build-up of speckles along the direction of the dominant wind vector in the coronagraphic image, severely limiting the contrast at small angular separations. One strategy to mitigate this problem is to predict the evolution of the turbulence over the delay time. Our predictive wavefront control algorithm minimizes, in a mean square sense, the wavefront error over the delay and has been implemented on the Keck II AO bench. In this paper, we report on the latest results of our algorithm and discuss updates to the algorithm itself. We explore how to tune various filter parameters based on both daytime laboratory tests and on-sky tests. We show a reduction in residual-mean-square wavefront error for the predictor compared to the leaky integrator (the standard controller for Keck) implemented on Keck for three separate nights. Finally, we present contrast improvements for daytime and on-sky tests for the first time.Using the L-band vortex coronagraph for Keck's NIRC2 instrument, we find a contrast gain of up to 2 at a separation of 3 λ/D and up to 3 for larger separations (3-7λ/D).

show abstract

Section: Daytime Testingmentioning

confidence: 99%

Predictive wavefront control on Keck II adaptive optics bench: on-sky coronagraphic results

Kooten¹,

Cetre²,

Ragland³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…8. The contrast of an optimal predictive controller will also depend on the wind speed in the same way although with a lower constant of proportionality, 43 which is why the contrast starts to degrade at higher wind speeds. At lower wind speed (<15 ms −1 ), the DDSPC stays very close to the perfect controller.…”

Section: Stationary Turbulencementioning

confidence: 99%

Data-driven subspace predictive control of adaptive optics for high-contrast imaging

Haffert

Males

et al. 2021

J. Astron. Telesc. Instrum. Syst.

View full text Add to dashboard Cite

The search for exoplanets is pushing adaptive optics (AO) systems on ground-based telescopes to their limits. One of the major limitations at small angular separations, exactly where exoplanets are predicted to be, is the servo-lag of the AO systems. The servo-lag error can be reduced with predictive control where the control is based on the future state of the atmospheric disturbance. We propose to use a linear data-driven integral predictive controller based on subspace methods that are updated in real time. The new controller only uses the measured wavefront errors and the changes in the deformable mirror commands, which allows for closed-loop operation without requiring pseudo-open loop reconstruction. This enables operation with non-linear wavefront sensors such as the pyramid wavefront sensor. We show that the proposed controller performs nearoptimal control in simulations for both stationary and non-stationary disturbances and that we are able to gain several orders of magnitude in raw contrast. The algorithm has been demonstrated in the lab with MagAO-X, where we gain more than two orders of magnitude in contrast.

show abstract

“…The residual contrast of the integrator follows this proportionality, as can be seen in Figure 8. The contrast of an optimal predictive controller will also depend on the wind speed in the same way although with a lower constant of proportionality [43], which is why the contrast starts to degrade at higher wind speeds. At lower wind speed (< 15ms −1 ), the DDSPC stays very close to the perfect controller.…”

Section: Stationary Turbulencementioning

confidence: 99%

Data-driven subspace predictive control of adaptive optics for high-contrast imaging

Haffert¹,

Males²,

Close³

et al. 2021

Preprint

View full text Add to dashboard Cite

The search for exoplanets is pushing adaptive optics systems on ground-based telescopes to their limits. One of the major limitations at small angular separations, exactly where exoplanets are predicted to be, is the servo-lag of the adaptive optics systems. The servo-lag error can be reduced with predictive control where the control is based on the future state of the atmospheric disturbance. We propose to use a linear data-driven integral predictive controller based on subspace methods that is updated in real time. The new controller only uses the measured wavefront errors and the changes in the deformable mirror commands, which allows for closed-loop operation without requiring pseudoopen loop reconstruction. This enables operation with non-linear wavefront sensors such as the pyramid wavefront sensor. We show that the proposed controller performs near-optimal control in simulations for both stationary and non-stationary disturbances and that we are able to gain several orders of magnitude in raw contrast. The algorithm has been demonstrated in the lab with MagAO-X, where we gain more than two orders of magnitude in contrast.

show abstract

The minimum of the time-delay wavefront error in Adaptive Optics

Cited by 5 publications

References 13 publications

Predictive wavefront control on Keck II adaptive optics bench: on-sky coronagraphic results

Predictive wavefront control on Keck II adaptive optics bench: on-sky coronagraphic results

Data-driven subspace predictive control of adaptive optics for high-contrast imaging

Data-driven subspace predictive control of adaptive optics for high-contrast imaging

Contact Info

Product

Resources

About