Curvature wavefront sensing for the large synoptic survey telescope

Claver, C. F.; Liang, Ming; Chandrasekharan, Srinivasan; Angeli, George Z.; Shipsey, I. P. J.

doi:10.1364/ao.54.009045

Cited by 31 publications

(20 citation statements)

References 18 publications

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“…Optical and mechanical pathways with lenses and mirrors cause vignetting, which decreases brightness, especially at great distance from the optical axis of the system. Large focal planes and wide fields are especially prone to vignetting, even though specialized optical elements and optimized wide-field systems like LSST can reduce the effect significantly (Xin et al 2015). The LSST vignetting model depends only on the distance from the center of the field (Araujo-Hauck et al 2016).…”

Section: Vignettingmentioning

confidence: 99%

High-fidelity Simulations of the Near-Earth Object Search Performance of the Large Synoptic Survey Telescope

Vereš

Chesley

2017

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We perform high fidelity simulations of a wide-field telescopic survey searching for Near-Earth Objects (NEO) larger than 140 m, focusing on the observational and detection model, detection efficiency and accuracy. As a test survey we select the Large Synoptic Survey Telescope. We use its proposed pointings for a 10-year mission and model the detection of near-Earth objects in the fields. We discuss individual model parameters for magnitude losses, vignetting, fading, asteroid rotation and colors, fill factor, limiting magnitude, rate of motion, field shape and rotation and survey patterns and we assess results in terms of the cumulative completeness of the detected population as a function of size and time. Additionally, we examine the sources of modeling uncertainty and derive the overall NEO population completeness for the baseline LSST survey to be 55 ± 5% for NEOs with absolute magnitude brighter than 22. Including already discovered objects and ongoing surveys, the population completeness at the end of the LSST baseline survey should reach ∼ 77%.

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Section: Vignettingmentioning

confidence: 99%

High-fidelity Simulations of the Near-Earth Object Search Performance of the Large Synoptic Survey Telescope

Vereš

Chesley

2017

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“…Finally, LSST has a large central obstruction of 60 %. More information on the method used to compensate for these particular effects can be found in Xin et al 11,12 After being processed by the Wavefront Data Collector (WF Data Collector), the images are corrected from basic instrument signature using a procedure called the Instrumentation Signature Removal (ISR) 13,14 developed by the Data Management team. The ISR algorithm includes typical astronomical calibration (Flat fielding, bad pixels, darks, biases, gains).…”

Section: Wavefront Estimation Pipelinementioning

confidence: 99%

The LSST Real-Time Active Optics System

Thomas¹

2017

Proceedings of the Adaptive Optics for Extremely Large Telescopes 5

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The Large Synoptic Survey Telescope is an 8.4m telescope now under construction on Cerro Pachon in Chile. This ground-based telescope is designed to conduct a decade-long time domain survey of the optical sky. Achieving the fundamental science goals of the LSST requires high quality imaging that is consistent over its full 3.5 degree field of view. LSST will use an Active Optics System (AOS) to achieve this goal. Unlike most other systems, the LSST Active Optics correction will combine an open-loop model with a slow (30 s) closed loop feedback. Although it is not fast enough to correct for atmospheric distortions, the AOS will correct in real time the system aberrations mostly introduced by gravity, temperature gradients and other system distortions. The LSST AOS uses a combination of 4 curvature wavefront sensors (CWS) located on the edge of the LSST field of view. The information coming from the 4 CWSs are combined to calculate the appropriate corrections to be sent to LSST's three mirrors, all equipped with actuators. The AOS software is composed of a Wavefront Estimation Pipeline (WEP) to estimate the error at each of the wavefront sensors and an Active Optics Controller (AOC) to reconstruct the state of the 3-mirrors system and find the optimal correction. In this paper, we describe the design and implementation of the AOS as well as its calibration.

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“…The wavefront sensor algorithm used for LSST is curvature sensing and has been described in detail in Xin et al 18 Due to the location of the wavefront sensors in the focal plane (∼1.7 degrees off axis) there is a need for distortion and vignetting corrections, preventing analytical mapping from the telescope aperture to the defocused image. In addition, since LSST has a large central obstruction (60%) and fast beam (f-number of 1.23), the WEP uses a numerical solution, representing the mapping between the two sets of coordinates with 2D 10th-order polynomials.…”

Section: Wavefront Estimatormentioning

confidence: 99%

“…As our two baseline algorithms we have chosen the iterative fast Fourier transform (FFT) method by Roddier and Roddier,19 and the series expansion technique by Gureyev and Nugent. 20 More details are given in Xin et al 18 Figure 5 provides further details on the inputs and sub steps that happen in the wavefront estimator box shown in Figure 3. The output of the WEP is an annular Zernike decomposition of the wavefront.…”

Section: Wavefront Estimatormentioning

confidence: 99%

LSST active optics system software architecture

et al. 2016

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The Large Synoptic Survey Telescope (LSST) is an 8-meter class wide-field telescope now under construction on Cerro Pachón, near La Serena, Chile. This ground-based telescope is designed to conduct a decade-long time domain survey of the optical sky. In order to achieve the LSST scientific goals, the telescope requires delivering seeing limited image quality over the 3.5 degree field of view. Like many telescopes, LSST will use an Active Optics System (AOS) to correct in near real-time the system aberrations primarily introduced by gravity and temperature gradients. The LSST AOS uses a combination of 4 curvature wavefront sensors (CWS) located on the outside of the LSST field-of-view. The information coming from the 4 CWS is combined to calculate the appropriate corrections to be sent to the 3 different mirrors composing LSST. The AOS software incorporates a wavefront sensor estimation pipeline (WEP) and an active optics control system (AOCS). The WEP estimates the wavefront residual error from the CWS images. The AOCS determines the correction to be sent to the different degrees of freedom every 30 seconds. In this paper, we describe the design and implementation of the AOS. More particularly, we will focus on the software architecture as well as the AOS interactions with the various subsystems within LSST.

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Curvature wavefront sensing for the large synoptic survey telescope

Cited by 31 publications

References 18 publications

High-fidelity Simulations of the Near-Earth Object Search Performance of the Large Synoptic Survey Telescope

High-fidelity Simulations of the Near-Earth Object Search Performance of the Large Synoptic Survey Telescope

The LSST Real-Time Active Optics System

LSST active optics system software architecture

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