Ground control to major time-lag: on-sky results of data-driven predictive wavefront control at Keck Observatory

Antonin Bouchez; Avinash Surendran; Charlotte Guthery; Charlotte Z. Bond; Eduardo Marin; Emiel Por; Jules Fowler; Maaike A. M. van Kooten; Mahawa Cisse; Maissa Salama

arxiv: 2606.20838 · v1 · pith:BH4ELGWEnew · submitted 2026-06-18 · 🌌 astro-ph.IM · astro-ph.EP

Ground control to major time-lag: on-sky results of data-driven predictive wavefront control at Keck Observatory

Jules Fowler , Rebeca Jensen-Clem , Sylvain Cetre , Maaike A. M. van Kooten , Maissa Salama , Antonin Bouchez , Avinash Surendran , Charlotte Guthery

show 7 more authors

Eduardo Marin Mahawa Cisse Max Service Charlotte Z. Bond Emiel Por Nour Skaf Will Gauvin

This is my paper

Pith reviewed 2026-06-26 15:13 UTC · model grok-4.3

classification 🌌 astro-ph.IM astro-ph.EP

keywords adaptive opticspredictive controlKeck Observatorywavefront sensingempirical orthogonal functionsexoplanet imagingtemporal error

0 comments

The pith

Predictive wavefront controller at Keck cuts sensor residuals by 20 percent versus integrator.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper presents on-sky engineering tests of an empirical orthogonal function predictive controller built into the Keck-II real-time adaptive optics system. It establishes that this approach, which forecasts the wavefront state from prior sensor measurements, reduces temporal lag errors. A reader would care because such lag errors dominate the budget for extreme adaptive optics required to image exoplanets. The tests directly compare the predictor against a standard integrator controller on the same nights.

Core claim

On-sky tests at Keck Observatory show the predictive controller achieves 20 percent lower wavefront residuals than a classic integrator according to Shack-Hartmann sensor data, while NIRC2 imaging through the Brackett Gamma filter yields comparable Strehl ratios and coronagraph-free contrast; parameter studies confirm the improvement holds across reasonable filter settings and principal-component power is modestly lower with the predictor.

What carries the argument

Empirical orthogonal functions that extract linear correlations from the recent history of wavefront sensor measurements to predict the wavefront at the moment of correction.

If this is right

Temporal errors that limit extreme adaptive optics can be reduced by learning from past sensor states.
The predictive filter improves residuals without degrading performance when its hyper-parameters are varied within tested ranges.
The method supplies a direct on-sky demonstration usable as a pathfinder for control systems on future extremely large telescopes.
Analysis of principal-component strength shows the predictor leaves modestly less residual power in higher-order modes.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

The benefit may appear only under specific turbulence conditions where temporal lag dominates over other error sources.
Integration of the same predictor with other real-time control layers could compound the residual reduction.
Repeating the test across a broader set of guide-star magnitudes and seeing values would map the regimes where the gain is largest.

Load-bearing premise

A 20 percent drop in Shack-Hartmann wavefront sensor residuals produces a meaningful advance in overall system performance even when final imaging metrics remain comparable.

What would settle it

A set of paired observations under identical conditions that show identical Strehl ratios and contrast curves between predictor and integrator runs would falsify the claim of system-level improvement.

Figures

Figures reproduced from arXiv: 2606.20838 by Antonin Bouchez, Avinash Surendran, Charlotte Guthery, Charlotte Z. Bond, Eduardo Marin, Emiel Por, Jules Fowler, Maaike A. M. van Kooten, Mahawa Cisse, Maissa Salama, Max Service, Nour Skaf, Rebeca Jensen-Clem, Sylvain Cetre, Will Gauvin.

**Figure 1.** Figure 1: Performance of the integrator and predictor as compared to the full state of injected turbulence on the Keck-II [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗

**Figure 2.** Figure 2: Histogram of RMS wavefront residuals during the initial predictor on/off experiment. Left: The mode of the [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗

**Figure 3.** Figure 3: NIRC2 Bracket γ images of the target HD 189337. We show a median combination of 5 0.2 ms frames. Left: Images while the integrator was running. Right: Images while the predictor was running. The performance in SR is comparable between the two median combined images. 4.2 Optimizing predictive filter hyper-parameters on-sky On the night of 12/03/2025, we conducted a half night of Keck observing to conduct pa… view at source ↗

**Figure 4.** Figure 4: Selecting optimal history vector (hv) and training data lengths for the predictive control filter. Using SHWFS [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗

**Figure 5.** Figure 5: Data from the night of 12/03/25 on the target BS 1191. Left: RMS residual wavefront error from the SHWFS [PITH_FULL_IMAGE:figures/full_fig_p007_5.png] view at source ↗

**Figure 6.** Figure 6: Keck/NIRC2 data through the Bracket γ filter from the night of 12/03/2025. These data consist of a median combination of 40 0.1 second frames on the target BS 1191 while (left) a classic integrator was running and (right) a predictor with optimal filter hyper-parameters was running [PITH_FULL_IMAGE:figures/full_fig_p008_6.png] view at source ↗

**Figure 7.** Figure 7: Strehl ratios of the Keck/NIRC2 images taken during the predictor on/off experiment. Each NIRC2 frame is [PITH_FULL_IMAGE:figures/full_fig_p008_7.png] view at source ↗

**Figure 8.** Figure 8: Left: Coronagraph-free contrast curves taken with Keck/NIRC2. By intentionally over-saturating the NIRC2 [PITH_FULL_IMAGE:figures/full_fig_p009_8.png] view at source ↗

**Figure 9.** Figure 9: In visible light, a few nm of wavefront has a larger impact. Using performance models of Keck/ORKID (the [PITH_FULL_IMAGE:figures/full_fig_p010_9.png] view at source ↗

**Figure 10.** Figure 10: Figure captions are used to describe the figure and help the reader understand it’s significance. The caption [PITH_FULL_IMAGE:figures/full_fig_p011_10.png] view at source ↗

read the original abstract

Directly imaging and characterizing exoplanets requires extreme adaptive optics (XAO), which achieves exquisite wavefront correction over a small (<5") field of view. Temporal errors, where the wavefront evolves faster than the lag between wavefront sensing and control, are often a leading term in the error budget for these XAO systems. Predictive control mitigates temporal errors by predicting where the wavefront will be by the time the system correction is applied. In particular, empirical orthogonal functions (EOF) learn linear correlations in a wavefront using previous states in the wavefront sensor history. We present on-sky results of a new implementation of EOF built directly into the Keck-II real time controller. On-sky engineering tests at Keck Observatory of the predictive controller show a 20% performance improvement over a classic integrator according to wavefront residuals from the Shack-Hartmann Wavefront Sensor (SHWFS). Parameter optimization studies show that there is a clear improvement based on varying predictive filter hyper-parameters, but that within a reasonable regime, varying filter parameters does not degrade performance to notably worse than an integrator. NIRC2 imaging through the Brackett Gamma=2190nm filter shows comparable performance between an integrator and predictor, both comparing Strehl Ratio (SR) and coronagraph-free contrast. We also explore power in principal components, and find a modest improvement (on the order of 3% less area under the curve of component strength) from the predictor over the integrator. This work not only improves current observing for the Keck community, but also acts as a pathfinder for predictive control methods with extremely large telescopes.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

The paper's on-sky Keck tests report 20% lower SHWFS residuals with the EOF predictor versus integrator, but NIRC2 Brackett-Gamma images show no gain in Strehl or contrast.

read the letter

The main thing to know is that the EOF predictor cut Shack-Hartmann residuals by about 20% during on-sky engineering runs at Keck-II, yet the NIRC2 science camera data in Brackett Gamma gave essentially identical Strehl ratios and coronagraph-free contrast for both controllers.

The work is a straightforward on-sky implementation of an established technique. They folded the predictor directly into the existing Keck real-time controller and collected parameter sweeps on the filter hyperparameters. That they kept performance from degrading below the integrator across a reasonable range of settings is useful practical information, and the modest 3% drop in principal-component power is at least consistent with the residual claim.

The clear soft spot is the disconnect between the wavefront-sensor metric and the focal-plane results. If the residual improvement does not show up in the images that actually matter for exoplanet work, either the SHWFS metric is missing the dominant error terms or other noise sources are limiting. The abstract does not give error bars, data-selection criteria, or a clear explanation for why the gain fails to propagate, which leaves the central performance claim only partially supported.

This is the sort of incremental engineering note that adaptive-optics groups at current 8-10 m telescopes and those planning ELT-scale systems will want to read. It is not a new theoretical framework, but the on-sky numbers and implementation details have value as a pathfinder.

I would send it to peer review. The experimental data are worth referee scrutiny even if the authors need to tighten the link between residuals and science metrics.

Referee Report

1 major / 2 minor

Summary. The manuscript presents on-sky engineering tests at Keck Observatory of an empirical orthogonal function (EOF) predictive wavefront controller integrated into the Keck-II real-time controller. It reports a 20% reduction in Shack-Hartmann wavefront sensor (SHWFS) residuals relative to a classic integrator, robustness to hyper-parameter variation, a modest (~3%) reduction in principal-component power, and comparable Strehl ratio plus coronagraph-free contrast in NIRC2 Brackett-Gamma imaging.

Significance. An on-sky demonstration of data-driven predictive control on an 8-10 m telescope is a practical contribution to extreme AO instrumentation. The direct RTC integration and hyper-parameter study are useful engineering results. However, the absence of corresponding gains in the focal-plane metrics that matter for exoplanet imaging limits the immediate system-level significance.

major comments (1)

[Abstract] Abstract: the headline claim of a 20% SHWFS-residual improvement is load-bearing for the paper's performance assertion, yet the same abstract states that NIRC2 Brackett-Gamma imaging yields comparable Strehl ratio and coronagraph-free contrast for predictor versus integrator. Because science metrics are the quantities that ultimately matter for XAO, this discrepancy must be reconciled (e.g., via error-budget breakdown or additional data) before the residual gain can be taken as evidence of a meaningful advance.

minor comments (2)

The manuscript notes that full methods, error bars, and data-selection criteria are not visible in the provided text; ensure these are explicitly documented so readers can assess the statistical significance of the reported 20% residual reduction.
Clarify whether the ~3% reduction in area under the principal-component curve is statistically significant and whether it correlates with the SHWFS residual metric.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their constructive feedback. We address the single major comment below.

read point-by-point responses

Referee: [Abstract] Abstract: the headline claim of a 20% SHWFS-residual improvement is load-bearing for the paper's performance assertion, yet the same abstract states that NIRC2 Brackett-Gamma imaging yields comparable Strehl ratio and coronagraph-free contrast for predictor versus integrator. Because science metrics are the quantities that ultimately matter for XAO, this discrepancy must be reconciled (e.g., via error-budget breakdown or additional data) before the residual gain can be taken as evidence of a meaningful advance.

Authors: The abstract accurately reports both results without contradiction. The 20% SHWFS residual reduction is the direct, high-SNR metric of the controller's success at mitigating temporal error, which is the quantity the EOF predictor is engineered to improve. Comparable NIRC2 Strehl and contrast is the expected and desired outcome for an engineering test: it confirms the predictor introduces no new errors that degrade science performance. Under the short on-sky sequences and conditions used, other error terms (non-common-path aberrations, fitting error, vibration) dominate the focal-plane budget, so a residual gain need not produce an immediate measurable contrast gain. We will add one clarifying sentence to the abstract and a short paragraph in the discussion to make this distinction explicit. revision: partial

Circularity Check

0 steps flagged

No circularity: purely empirical on-sky comparison

full rationale

The manuscript reports direct on-sky measurements at Keck comparing an EOF predictive controller against a classic integrator. All performance numbers (20% SHWFS residual reduction, comparable NIRC2 Strehl/contrast, 3% PCA power difference) are obtained from hardware telemetry and imaging data. No derivation chain, fitted-parameter prediction, or self-citation is invoked to obtain the reported results; the claims rest on measured observables rather than any equation that reduces to its own inputs.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The claim rests on the domain assumption that linear correlations learned from past wavefront states remain predictive on-sky and that SHWFS residuals are a sufficient proxy for end-to-end performance. Hyper-parameters of the predictive filter are optimized but not enumerated.

free parameters (1)

predictive filter hyper-parameters
The abstract states that parameter optimization studies were performed and that performance varies with these choices.

axioms (1)

domain assumption Past wavefront sensor states contain linear correlations that can be used to predict future states via empirical orthogonal functions.
This is the foundational premise of the EOF predictive controller described in the abstract.

pith-pipeline@v0.9.1-grok · 5893 in / 1255 out tokens · 36571 ms · 2026-06-26T15:13:31.800016+00:00 · methodology

discussion (0)

Reference graph

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2026

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Theoretical Limits on Extrasolar Terrestrial Planet Detection with Coronagraphs,

Guyon, O., Pluzhnik, E. A., Kuchner, M. J., Collins, B., and Ridgway, S. T., “Theoretical Limits on Extrasolar Terrestrial Planet Detection with Coronagraphs,”Astrophysics Journal Supplement Series167, 81–99 (Nov. 2006)

2006

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Closed-Loop Until Further Notice: Comparing Predictive Control Methods in Closed-Loop,

Fowler, J., van Kooten, M., and Jensen-Clem, R., “Closed-Loop Until Further Notice: Comparing Predictive Control Methods in Closed-Loop,” in [Adaptive Optics for Extremely Large Telescopes (AO4ELT7)], 49 (June 2023)

2023

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Upgrading SPHERE with the second stage AO system SAXO+: RTC preliminary design,

Ferreira, F., Sevin, A., Gratadour, D., Chauvin, G., Diolaiti, E., Gratton, R., Loupias, M., Milli, J., Wildi, F., and Boccaletti, A., “Upgrading SPHERE with the second stage AO system SAXO+: RTC preliminary design,” in [Adaptive Optics Systems IX], Jackson, K. J., Schmidt, D., and Vernet, E., eds.,Society of Photo-Optical Instrumentation Engineers (SPIE)...

2024