arXiv subjects

Benoit Neichel

Publications and source records attributed to Benoit Neichel.

At least 19 recordsLinked to original sources

arXiv2026

Modelling Fourier filtering wavefront sensors for PSD-based methods: the AOPERA tool

Compensation of the atmospheric turbulence thanks to adaptive optics (AO) has now become commonly used for VLT or ELT class telescopes in order to retrieve a resolution close to their diffraction limit. Following the increasing trend of AO system, there is also a stronger necessity for simulations in order to understand and predict their performance facing different observing conditions, that are the evolution of the atmospheric turbulence or the diversity of AO guide source. The so-called PSD based methods are well adapted to the demand thanks to their simplicity and speed. Moreover, they provide a comprehensive breakdown error budget and impact on focal plane, that is of high interest especially in the case of extreme adaptive optics. Their drawback is the challenge to describe non-linear wavefront sensors (WFS) such as the pyramid WFS or the Zernike WFS. There is a necessity to develop fast yet accurate methods to describe the behaviour of AO systems including sensitive WFS. We thus develop a method to compute the AO system response (electromagnetic phase power spectral density, and point spread function) including the non-linear behaviour of the wavefront sensor within PSD-based numerical tools. Mathematical formalism to describe the FF-WFS sensitivity combined to non-linearity management greatly improve the accuracy of description of AO systems through numerical simulations. After a mathematical description of the method, its numerical implementation is compared with end-to-end simulations using the OOPAO tool. Indeed end-to-end simulations are reproducing the response of AO systems with high fidelity, especially regarding WFS sensitivity and non-linearity. Similarity of results for the fitting error, temporal error and noise error proves the validity of our method in managing Fourier filtering WFS sensitivity and non-linearity.

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arXiv2026

RISTRETTO: Assembly and Testing of the Seven-spaxel, High-resolution, Diffraction-limited Spectrograph

The RISTRETTO project aims at the direct detection of the reflected light of extra-solar planets to measure albedos and detect possible biosignatures, using the high-contrast / high-resolution method. We report on the assembly, lab-testing and on-sky testing of the seven-spaxel high-resolution single-mode spectrograph which was built ahead of the rest of the instrument. The spectrograph is a high resolution echelle spectrograph build for high spectral fidelity being uder vacuum and thermally controlled. Once the assembly has been completed we had the chance to test it on sky using OHP 1.52 m telescope using the PAPYRUS AO system for injection in our spectrograph.

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arXiv2026

Closing the loop on-sky with a vector-Zernike wavefront sensor using a convolutional neural network as phase reconstructor

Context: The new giant segmented mirror telescopes will use adaptive optics to reach the fundamental limits in resolving power. To accomplish this, new wavefront sensors (WFS) have been designed to fulfill the requirements, but they may require non-linear reconstruction techniques to operate given the nature of the signal of the WFSs Aims: In this article we show that it is possible to use non-linear reconstructors to extend the dynamic range of one of the most sensitive wavefront sensors far beyond the designed limits: the Zernike wavefront sensor (ZWFS). Methods: We trained a convolutional neural network (CNN) completely in simulation to perform the phase reconstruction of a vector-ZWFS (v-ZWFS), a higher dynamic-range variant of the ZWFS. Contrary to the linear method, the CNN uses the information across the full frame to reconstruct the phase at each point, enabling it to resolve the ambiguities introduced by the periodic response of the ZWFS and thereby extend its effective capture range. We developed a two-step training strategy that ensured closed-loop stability and used a physically informed loss function to maximize the performance of the CNN. Results: We successfully closed the loop on-sky with the v-ZWFS using the CNN in observing conditions that the linear reconstructor could not converge to a stable flat wavefront. In cases where both reconstruction methods were working, the CNN outperformed the linear method in almost all cases, and in favorable seeing conditions we were even able to close the loop with the ZWFS acting as a first stage WFS, highlighting the extended dynamic range brought by the use of a non-linear wavefront reconstructor. Conclusions: We conclude that the use of non-linear wavefront reconstructor can extend the use cases of adaptive optics systems, especially when the WFS used shows highly non-linear behaviors.

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arXiv2026

Impact of microlens shape on the performance of Laser Guide Star wavefront sensors for ELT-class telescopes

Laser Guide Star (LGS) adaptive optics systems on extremely large telescopes (ELTs) rely on Shack-Hartmann wavefront sensors (SHWFS) equipped with large-format microlens arrays. Manufacturing imperfections in the microlens surface profile degrade spot quality and reduce centroiding accuracy, yet this effect is rarely quantified in the context of full AO system performance. This paper presents a comprehensive characterization of the impact of microlens shape on LGS wavefront sensing, using the MORFEO-HARMONI LGS wavefront sensor design as the primary test case, results are directly applicable to any ELT-class or future large-telescope LGS instrument, including systems on the GMT and TMT. Starting from interferometric surface profile measurements of prototype microlenses, we derive the induced phase errors and compute the degradation of center-of-gravity (CoG) spot detection accuracy as a function of LGS elongation and flux. A real microlens degrades CoG variance by a factor of 1.8 to 2.4 compared to an ideal lens, equivalent to requiring approximately twice the photon flux to maintain the same measurement accuracy. This effect is shown to decrease with increasing LGS elongation, and to improve with higher microlens sag. The per-subaperture flux-loss model is then propagated into tomographic AO end-to-end simulations, where measurement redundancy across multiple LGS and MMSE reconstructor weighting partially mitigate the penalty, reducing the effective Strehl ratio flux loss to factors of 1.25-1.4. Experimental validation is provided with the LGS wavefront sensor optical bench prototype at LAM, which also enables full-array characterization in a single measurement. The methodology is broadly applicable to any Shack-Hartmann system operating in a low-flux regime.

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arXiv2026

DD4AO control law for RISTRETTO: robustness, real-time performance, and on-sky validation with PAPYRUS

This study presents DD4AO progress towards its implementation in the RISTRETTO instrument. DD4AO is a novel frequency-domain, data-driven controller for adaptive optics that leverages power spectral density estimation for optimization while enforcing stability criteria. It addresses disturbance rejection, command amplitude constraints, and system transfer functions through convex optimization, yielding an optimal controller in Infinite Impulse Response (IIR) filter form. We present the on-sky validation of DD4AO conducted using the PAPYRUS instrument at the Observatoire de Haute-Provence (OHP). The observations were performed on two stars over the night of 24-25 March 2026: the bright star Arcturus, and the faint binary HD137909. DD4AO successfully maintained a closed and stable loop over hour-long exposures while continuously adapting to evolving atmospheric conditions. The pipeline enabled instantaneous switching between DD4AO and standard controllers, namely the Integrator and OMGI, allowing direct statistical comparisons throughout each observation. On Arcturus, DD4AO achieved a 5% Strehl ratio improvement over the integrator at lambda = 1310 nm, from 28.8% to 33.9%. On HD137909, performance differences were smaller due to the low-SNR regime, though DD4AO consistently used less deformable mirror stroke and suppressed vibration peaks present in the residuals of the standard controllers. These results validate DD4AO as a robust on-sky control solution and represent an important milestone towards its deployment in RISTRETTO and SAXO+ at the VLT.

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arXiv2026

Estimation of the laser guide star uplink tip-tilt using aperture size diversity

Laser guide star (LGS) adaptive optics cannot directly measure tip-tilt (TT), forcing reliance on natural guide stars and limiting sky coverage. We propose estimating the uplink TT from telemetry acquired at the laser launch telescope alone, operated in a monostatic configuration as both emitter and receiver. Extracting TT over concentric disks of different diameters within the receiving pupil yields signals mixing uplink and downlink contributions in different proportions; this aperture size diversity, combined with an LMMSE estimator, disentangles the uplink component. Simulations show a residual error of 24 mas for a single turbulent layer and 34 mas with two layers.

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arXiv2026

On-sky demonstration of reinforcement learning for adaptive optics control

Reinforcement learning (RL)-based algorithms have recently emerged as a promising approach for adaptive optics (AO) control. In simulations and laboratory experiments, they have demonstrated robustness to real-world effects such as photon and detector noise, misregistration, vibrations, and rapid variations in seeing conditions. However, their performance has not yet been validated on sky. We report the first on-sky demonstration of a reinforcement learning controller for adaptive optics, named Policy Optimization for AO (PO4AO). We further analyze its on-sky behavior and identify directions for improving the algorithm and its implementation.PO4AO was implemented and deployed on the Papyrus adaptive optics system installed at the Coud\'e focus of the 1.52 m telescope (T152) at the OHP. A Python-based implementation was interfaced with the existing real-time controller (DAO RTC) via shared-memory buffers. The performance of PO4AO was compared to that of a standard integrator controller over several nights, covering a range of flux levels and atmospheric conditions. PO4AO consistently outperformed the standard integrator in all tested configurations. The controller successfully learned and compensated for vibration patterns and demonstrated strong robustness to measurement noise. Once tuned for Papyrus, PO4AO operated in a turnkey fashion, using a single set of hyperparameters across varying observing conditions and science targets. These performance gains were achieved despite a non-optimized Python implementation introducing approximately $750\,\mu\text{s}$ of additional latency, along with control jitter and occasional frame drops. When properly implemented and optimized, PO4AO constitutes a robust and high-performance turnkey controller for single-conjugate adaptive optics systems, paving the way for broader adoption of reinforcement learning strategies in on-sky AO operations.

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arXiv2026

A self-adjoint Fourier-type model for the iQuad wavefront sensor

Advanced adaptive optics (AO) systems can use Fourier-type wavefront sensing to correct optical distortions encountered in ground-based telescopes, AO-assisted retinal imaging, and free-space optical communications (FSOC). Recently, a novel Fourier-type wavefront sensor (WFS) known as the iQuad WFS has been introduced. Its design features a focal plane tessellation with a four-quadrant phase mask (FQPM) that incorporates a $\pm \pi/2$ phase shift between adjacent quadrants. In this work, we establish a comprehensive mathematical framework for the iQuad WFS, including its forward models and linearizations based on the Fr\'echet derivative. We reveal a connection between the iQuad WFS and the 2d finite Hilbert transform and demonstrate that the linear iQuad WFS operator is self-adjoint - a unique property among Fourier-type WFSs. Additionally, we introduce the double iQuad WFS, a two-path configuration that combines two rotated iQuad WFSs. This design addresses the limitations of the single iQuad WFS by suppressing poorly-seen phase components. Moreover, the double setup simplifies the mathematical modeling. We also highlight iQuad similarities to the widely used pyramid wavefront sensor (PWFS). Finally, we extend the concept of modulation to the iQuad WFS, further enhancing its versatility. The theoretical analysis presented here lays the groundwork for the development of fast and robust model-based wavefront reconstruction algorithms for the iQuad WFS, paving the way for future applications in AO instruments.

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arXiv2026

Data-calibrated point spread function prediction: General description of the method and demonstration on MUSE-NFM

Precise knowledge of the point spread function (PSF) underpins many data analysis steps in astronomy, from photometry and astrometry to source de-blending and deconvolution. In adaptive optics (AO) observations, however, the PSF is highly variable with wavelength, field position, and observing conditions, making it difficult to model. Traditional PSF reconstruction (PSF-R) requires full AO telemetry and complex infrastructures, limiting its routine use, especially for tomographic systems. We present a practical framework for fast, accurate, and data-calibrated PSF modeling that captures the spatial and spectral variability of AO-corrected PSFs without relying on complete AO telemetry. Our approach builds on a Fourier-based PSF model inspired by astro-TIPTOP. As inputs, our model uses only a compact set of physically meaningful parameters retrievable from the ESO archive. A lightweight neural network corrects these inputs to achieve the best match with real data. It is trained end to end with the PSF model, allowing it to learn any miscalibrations directly from on-sky data. The framework achieves high accuracy on on-sky data. On a test set of MUSE-NFM standard stars, it yields median errors of 13.5% in the Strehl ratio and 10.9% in the core full width at half maximum (FWHM). In crowded MUSE-NFM observations of $\omega$ Centauri, the method predicts dozens of off-axis, wavelength-dependent PSFs with a Strehl error of <5% and a FWHM error of 4.6%, enabling source separation without per-star PSF extraction. Our compact, physics-informed, and data-calibrated model delivers accurate, polychromatic, and field-varying PSFs without relying on full AO telemetry. While demonstrated on MUSE-NFM, the method is still transferable to other AO-assisted instruments.

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arXiv2026

Slow focus sensor for the Keck I laser guide star adaptive optics system using focal plane wavefront sensing

Laser guide stars (LGSs) have been deployed for the last 20-30 years in ground-based astronomical telescopes to overcome the limited sky coverage of classical adaptive optics (AO) systems. Unfortunately, slow altitude drifts of the sodium layer compromise focus measurements, generating the so-called slow focus error, and, consequently, a natural guide star (NGS) is needed to compensate for that error. Our goal is to develop and operationalize a focal plane wavefront sensing (FPWFS) technique for slow focus tracking for the Keck I telescope, which can significantly increase sky coverage and allow slow focus tracking at higher frequencies, reducing the lag error. We develop, characterize, and compare three different FPWFS algorithms, namely Gerchberg-Saxton (GS), linearized focal plane technique (LiFT), and Gaussian fit (Gf). These algorithms were studied for the specific purpose of slow focus sensing in the NIR (H and K bands) using numerical simulations and data collected at Keck in 2025 (bench and on-sky). The three algorithms were studied and characterized against different criteria such as linearity, computational costs, and resistance to low signal-to-noise ratio and/or residuals. From the results obtained, the main candidate for an on-sky deployment was GS. On-sky tests showed promising results, with GS successfully compensating for purposely introduced focus errors, even under the presence of high turbulence conditions. This work can also be extrapolated to other existing 8-10 m class telescopes, or even future 30-40 m class telescopes, where the use of FPWFS can significantly improve sky coverage and reduce the lag error.

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arXiv2024

MAVIS: Enabling High-Precision Ground-Based Astrometry in the Visible Spectrum

MAVIS (the MCAO-Assisted Visible Imager and Spectrograph), planned for the VLT Adaptive Optics Facility, represents an innovative step in Multi-Conjugate Adaptive Optics (MCAO) systems, particularly in its operation at visible wavelengths and anticipated contributions to the field of astronomical astrometry. Recognizing the crucial role of high-precision astrometry in realizing science goals such as studying the dynamics of dense starfields, this study focuses on the challenges of advancing astrometry with MAVIS to its limits, as well as paving the way for further enhancement by incorporating telemetry data as part of the astrometric analysis. We employ MAVISIM, Superstar, and DAOPHOT to simulate both MAVIS imaging performance and provide a pathway to incorporate telemetry data for precise astrometry with MAVIS. Photometry analyses are conducted using the Superstar and DAOPHOT platforms, integrated into a specifically designed pipeline for astrometric analysis in MCAO settings. Combining these platforms, our research aims to elucidate the impact of utilizing telemetry data on improving astrometric precision, potentially establishing new methods for ground-based AO-assisted astrometric analysis. This endeavor not only sheds light on the capabilities of MAVIS but also paves the way for advancing astrometry in the era of next-generation MCAO-enabled giant telescopes.

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arXiv2024

AI-Powered Low-Order Focal Plane Wavefront Sensing in Infrared

Adaptive optics (AO) systems are crucial for high-resolution astronomical observations by compensating for atmospheric turbulence. While laser guide stars (LGS) address high-order wavefront aberrations, natural guide stars (NGS) remain vital for low-order wavefront sensing (LOWFS). Conventional NGS-based methods like Shack-Hartmann sensors have limitations in field of view, sensitivity, and complexity. Focal plane wavefront sensing (FPWFS) offers advantages, including a wider field of view and enhanced signal-to-noise ratio, but accurately estimating low-order modes from distorted point spread functions (PSFs) remains challenging. We propose an AI-powered FPWFS method specifically for low-order mode estimation in infrared wavelengths. Our approach is trained on simulated data and validated on on-telescope data collected from the Keck I adaptive optic (K1AO) bench calibration source in K-band. By leveraging the enhanced signal-to-noise ratio in the infrared and the power of AI, our method overcomes the limitations of traditional LOWFS techniques. This study demonstrates the effectiveness of AI-based FPWFS for low-order wavefront sensing, paving the way for more compact, efficient, and high-performing AO systems for astronomical observations.

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arXiv2024

Performance comparison of the Shack-Hartmann and pyramid wavefront sensors with a laser guide star for 40 m telescopes

Context. The new giant segmented mirror telescopes will use laser guide stars (LGS) for their adaptive optics (AO) systems. Two options to use as wavefront sensors (WFS) are the Shack-Hartmann wavefront sensor (SHWFS) and the pyramid wavefront sensor (PWFS). Aims. In this paper, we compare the noise performance of the PWFS and the SHWFS. We aim to find which of the two WFS is the best to use in a single or tomographic configuration. Methods. To compute the noise performance we extended a noise model developed for the PWFS to be used with the SHWFS. To do this, we expressed the centroiding algorithm of the SHWFS as a matrix-vector multiplication, which allowed us to use the statistics of noise to compute its propagation through the AO loop. We validated the noise model with end-to-end simulations for telescopes of 8 and 16 m in diameter. Results. For an AO system with only one WFS, we found that, given the same number of subapertures, the PWFS outperforms the SHWFS. For a 40 m telescope, the limiting magnitude of the PWFS is around 1 magnitude higher than the SHWFS. When using multiple WFS and a Generalized least squares estimator to combine the signal, our model predicts that in a tomographic system, the SHWFS performs better than the PWFS having a limiting magnitude 0.3 magnitudes higher. If using sub-electron RON detectors for the PWFS, then the performances are almost identical between the two WFSs Conclusions. We conclude that when using a single WFS with LGS, the PWFS is a better alternative than the SH. However, for a tomographic system, either would have almost the same performance.

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arXiv2024

RISTRETTO: reflected-light exoplanet spectroscopy at the diffraction limit of the VLT

RISTRETTO is a visible high-resolution spectrograph fed by an extreme adaptive optics (AO) system, to be proposed as a visitor instrument on ESO VLT. The main science goal of RISTRETTO is to pioneer the detection and atmospheric characterisation of exoplanets in reflected light, in particular the temperate rocky planet Proxima b. RISTRETTO will be able to measure albedos and detect atmospheric features in a number of exoplanets orbiting nearby stars for the first time. It will do so by combining a high-contrast AO system working at the diffraction limit of the telescope to a high-resolution spectrograph, via a 7-spaxel integral-field unit (IFU) feeding single-mode fibers. Further science cases for RISTRETTO include the study of accreting protoplanets such as PDS70b/c through spectrally-resolved H-alpha emission, and spatially-resolved studies of Solar System objects such as icy moons and the ice giants Uranus and Neptune. The project is in the manufacturing phase for the spectrograph sub-system, and the preliminary design phase for the AO front-end. Specific developments for RISTRETTO include a novel coronagraphic IFU combining a phase-induced amplitude apodizer (PIAA) to a 3D-printed microlens array feeding a bundle of single-mode fibers. It also features an XAO system with a dual wavefront sensor aiming at high robustness and sensitivity, including to pupil fragmentation. RISTRETTO is a pathfinder instrument in view of similar developments at the ELT, in particular the SCAO-IFU mode of ELT-ANDES and the future ELT-PCS instrument.

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arXiv2024

Striving towards robust phase diversity on-sky: Implementing LIFT for VLT/MUSE-NFM

The recent IRLOS upgrade for VLT/MUSE narrow field mode (NFM) introduced a full-pupil mode to enhance sensitivity and sky coverage. This involved replacing the 2x2 Shack-Hartmann sensor with a single lens for full-aperture photon collection, which also enabled the engagement of the linearized focal-plane technique (LIFT) wavefront sensor instead. However, initial on-sky LIFT experiments have highlighted a complex point spread function (PSF) structure due to strong and polychromatic non-common path aberrations (NCPAs), complicating the accurate retrieval of tip-tilt and focus using LIFT. This study aims to conduct the first on-sky validation of LIFT on VLT/UT4, outline challenges encountered during the tests, and propose solutions for increasing the robustness of LIFT in on-sky operations. We developed a two-stage approach to focal-plane wavefront sensing, where tip-tilt and focus retrieval done with LIFT is preceded by the NCPA calibration step. The resulting NCPA estimate is subsequently used by LIFT. To perform the calibration, we proposed a method capable of retrieving the information about NCPAs directly from on-sky focal-plane PSFs. We verified the efficacy of this approach in simulated and on-sky tests. Our results demonstrate that adopting the two-stage approach has led to a significant improvement in the accuracy of the defocus estimation performed by LIFT, even under challenging low-flux conditions. The efficacy of LIFT as a slow and truth focus sensor in practical scenarios has been demonstrated. However, integrating NCPA calibration with LIFT is essential to verifying its practical application in the real system. Additionally, the proposed calibration step can serve as an independent and minimally invasive approach to evaluate NCPA on-sky.

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arXiv2024

Cassiop\'ee, towards technological development for XAO on ELT: the e-APD infrared detector

The Cassiop\'ee project aims to develop the key technologies that will be used to deploy very high-performance Adaptive Optics for future ELTs. The ultimate challenge is to detect earth-like planets and characterize the composition of their atmosphere. For this, imaging contrasts of the order of 109 are required, implying a leap forward in adaptive optics performance, with high density deformable mirrors (120x120 actuators), low-noise cameras and the control of the loop at few kHz. The project brings together 2 industrial partners: First Light Imaging and ALPAO, and 2 academic partners: ONERA and LAM, who will work together to develop a new camera for wavefront sensing, a new deformable mirror and their implementation in an adaptive optics loop. This paper will present the development of the fast large infrared e-APD camera which will be used in the wavefront sensor of the system. The camera will integrate the latest 512x512 Leonardo e-APD array and will benefit from the heritage of the first-light imaging's C-RED One camera. The most important challenges for the application are the autonomous operation, vibration control, background limitation, compactness, acquisition speed and latency.

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arXiv2024

Transformer neural networks for closed-loop adaptive optics using non-modulated pyramid wavefront sensors

The Pyramid Wavefront Sensor (PyWFS) is highly nonlinear and requires the use of beam modulation to successfully close an AO loop under varying atmospheric turbulence conditions, at the expense of a loss in sensitivity. In this work we train, analyse, and compare the use of deep neural networks (NNs) as non-linear estimators for the non-modulated PyWFS, identifying the most suitable NN architecture for reliable closed-loop AO. We develop a novel training strategy for NNs that seeks to accommodate for changes in residual statistics between open and closed-loop, plus the addition of noise for robustness purposes. Through simulations, we test and compare several deep NNs, from classical to new convolutional neural networks (CNNs), plus a state-of-the-art transformer neural network (TNN, Global Context Visual Transformer, GCViT), first in open-loop and then in closed-loop. Using open-loop simulated data, we observe that a TNN (GCViT) largely surpasses any CNN in estimation accuracy in a wide range of turbulence conditions. Also, the TNN performs better in simulated closed-loop than CNNs, avoiding estimation issues at the pupil borders. When closing the loop at strong turbulence and low noise, the TNN using non-modulated PyWFS data is able to close the loop similar to a PyWFS with $12\lambda/D$ of modulation. When raising the noise only the TNN is able to close the loop, while the standard linear reconstructor fails, even with modulation. Using the GCViT, we close a real AO loop in the optical bench achieving a Strehl ratio between 0.28 and 0.77 for turbulence conditions ranging from 6cm to 20cm, respectively. In conclusion, we demonstrate that a TNN is the most suitable architecture to extend the dynamic range without sacrificing sensitivity for a non-modulated PyWFS. It opens the path for using non-modulated Pyramid WFSs under an unprecedented range of atmospheric and noise conditions.

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arXiv2024

Expected performance of the Pyramid wavefront sensor with a laser guide star for 40 m class telescopes

The use of artificial Laser Guide Stars (LGS) is planned for the new generation of giant segmented mirror telescopes, to extend the sky coverage of their adaptive optics systems. The LGS, being a 3D object at a finite distance will have a large elongation that will affect its use with the Shack-Hartmann (SH) wavefront sensor. In this paper, we compute the expected performance for a Pyramid WaveFront Sensor (PWFS) using a LGS for a 40 m telescope affected by photon noise, and also extend the analysis to a flat 2D object as reference. We developed a new way to discretize the LGS, and a new, faster method of propagating the light for any Fourier Filtering wavefront sensors (FFWFS) when using extended objects. We present the use of a sensitivity model to predict the performance of a closed-loop adaptive optic system. We optimized a point source calibrated interaction matrix to accommodate the signal of an extended object, by means of computing optical gains using a convolutional model. We found that the sensitivity drop, given the size of the extended laser source, is large enough to make the system operate in a low-performance regime given the expected return flux of the LGS. The width of the laser beam, rather than the thickness of the sodium layer was identified as the limiting factor. Even an ideal, flat LGS will have a drop in performance due to the flux of the LGS, and small variations in the return flux will result in large variations in performance. We conclude that knife-edge-like wavefront sensors, such as the PWFS, are not recommended for their use with LGS for a 40 m telescope, as they will operate in a low-performance regime, given the size of the extended object.

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