KEYWORDS: Planets, Stars, Exoplanets, Coronagraphy, Telescopes, James Webb Space Telescope, Atmospheric sciences, Atmospheric modeling, Large telescopes, Thirty Meter Telescope
The Pathways to Discovery in Astronomy and Astrophysics for the 2020s decadal survey highlighted the ability of the coming generation of 30-meter-class telescopes “to detect, image, and characterize temperate rocky planets around low-mass stars, measure their atmospheric compositions including searches for oxygen.” However, many of the technologies required to reach the challenging contrast ratios associated with this science case are not yet available, and targeted preparatory science must be carried out well in advance of these observations. In this paper, we draw from the example of NASA’s Exoplanet Exploration Program and propose a preliminary version of a “Technology Gap List” and “Science Gap List” for the ground-based imaging of rocky planets around the nearest stars with extremely large ground-based telescopes. These lists can be used to prioritize precursor technical demonstrations and observations with current and near-term high contrast instrumentation, so that the community is ready to exploit the collecting area of extremely large telescopes.
High contrast imaging (HCI) systems rely on active wavefront control (WFC) to deliver deep raw contrast in the focal plane, and on calibration techniques to further enhance contrast by identifying planet light within the residual speckle halo. Both functions can be combined in an HCI system and we discuss a path toward designing HCI systems capable of calibrating residual starlight at the fundamental contrast limit imposed by photon noise. We highlight the value of deploying multiple high-efficiency wavefront sensors (WFSs) covering a wide spectral range and spanning multiple optical locations. We show how their combined information can be leveraged to simultaneously improve WFS sensitivity and residual starlight calibration, ideally making it impossible for an image plane speckle to hide from WFS telemetry. We demonstrate residual starlight calibration in the laboratory and on-sky, using both a coronagraphic setup, and a nulling spectro-interferometer. In both case, we show that bright starlight can calibrate residual starlight.
To directly detect exoplanets and protoplanetary disks, the development of high accuracy wavefront sensing and control (WFS&C) technologies is essential, especially for ground-based Extremely Large Telescopes (ELTs). The Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) instrument is a high-contrast imaging platform to discover and characterize exoplanets and protoplanetary disks. It also serves as a testbed to validate and deploy new concepts or algorithms for high-contrast imaging approaches for ELTs, using the latest hardware and software technologies on an 8-meter class telescope. SCExAO is a multi-band instrument, using light from 600 to 2500 nm, and delivering a high Strehl ratio (>80% in median seeing in H-band) downstream of a low-order correction provided by the facility AO188. Science observations are performed with coronagraphs, an integral field spectrograph, or single aperture interferometers. The SCExAO project continuously reaches out to the community for development and upgrades. Existing operating testbeds such as the SCExAO are also unique opportunities to test and deploy the new technologies for future ELTs. We present and show a live demonstration of the SCExAO capabilities (Real-time predictive AO control, Focal plane WFS&C, etc) as a host testbed for the remote collaborators to test and deploy the new WFS&C concepts or algorithms. We also present several high-contrast imaging technologies that are under development or that have already been demonstrated on-sky.
In 2013, Frazin introduced a statistical inference algorithm that uses simultaneous millisecond exposures in the science camera (SC) and wavefront sensor (WFS) to jointly estimate this NCPA, as well as the exoplanetary image. Here, we provide an update on the advancement of the method, with a focus on the ability to compensate NCPA in real time, and an evaluation of the effect of readout noise on the contrast. Finally, we make conclusions about the practicality of implementing the algorithm on modern and future telescopes, discussing factors such as real time computational requirements and high fidelity model calibrations.
Due to its high sensitivity and minimal aliasing, the pyramid wavefront sensor (PyWFS) is becoming a popular choice for astronomical adaptive optics. To date, all implementations of the PyWFS modulate the input beam in order to operate the device the linear regime, however, this modulation reduces the sensitivity. Simulations in a recently published article show that model-based nonlinear estimation techniques can extend the range in which the PyWFS can be used without modulation, thus allowing modulation-free operation at lower Strehl values than previously thought possible. Further, the article shows that required calculations for the model-based nonlinear estimation do not require any real-time optical simulations and can be performed in massively parallel fashion, thus, (hopefully) allowing onsky implementation. The model-based estimation requires a realistic and phase-accurate, calibrated computational model (CCM) of the PyWFS. This article summarizes the potential benefits of modelbased nonlinear estimation and outlines a procedure to obtain the needed CCM.
Millisecond focal plane telemetry is now becoming practical due to a new generation of near-IR detector arrays with sub-electron noise that are capable of kHz readout rates. Combining these data with those simultaneously available from the wavefront sensing system allows the possibility of self-consistently determining the optical aberrations (the cause of quasi-static speckles) and the planetary image. This approach may be especially advantageous for finding planets within about 3λ/D of the star where differential imaging is ineffective. As shown in a recent article by the author (J. Opt. Soc. Am. A., 33, 712, 2016), one must account for unknown aberrations in several non-conjugate planes of the optical system, which, in turn, requires ability to computational propagate the field between these planes. These computations are likely to be difficult to implement and expensive. Here, a far more convenient alternative based on empirical Green's functions is provided. It is shown that the empirical Green's function (EGF), which accounts for all multi-planar, non-common path aberrations, and results in a much more tractable and highly parallel computational problem. It is also shown that the EGF can be generalized to treat polarization, resulting in the empirical Green's tensor (EGT).
Ground-based ultra-high contrast imaging, as required for direct imaging of exoplanets and other solar systems, is limited by difficulty of separating the planetary emission from the effects of optical aberrations that are not compensated by the adaptive optics (AO) system, so-called non-common path aberrations" (NCPAs). Simultaneous (~ millisecond) exposures by the science camera and the AO system enable the use of “phase diversity" to estimate both the NCPAs and the scene via a processing procedure first described by the author (R. Frazin 2013, ApJ, 767, article id. 21).This method is fully compatible with more standard concepts used in long-exposure high-contrast imaging, such as angular differential imaging and spectral deconvolution. Long-exposure methods find time-dependent NCPAs, such as those caused by vibrations, particularly challenging. Here, an NCPA of the form of α cos(k•r-ωt + ∂) is considered. It is shown that, when sampled at millisecond time-scales, the image plane data are sensitive to arg(α), ∂ and ω, and, therefore such NCPAs can be simultaneously estimated with the scene. Simulations of observations with ms exposure times are reported. These simulations include substantial detector noise and a sinusoidal NCPA that places a speckle exactly at the location of a planet. Simulations show that the effects of detector noise can be mitigated by mixing exposures of various lengths, allowing estimation of the planet's brightness.
The direct imaging of planets around nearby stars is exceedingly difficult. Only about 14 exoplanets have been
imaged to date that have masses less than 13 times that of Jupiter. The next generation of planet-finding
coronagraphs, including VLT-SPHERE, the Gemini Planet Imager, Palomar P1640, and Subaru HiCIAO have
predicted contrast performance of roughly a thousand times less than would be needed to detect Earth-like
planets. In this paper we review the state of the art in exoplanet imaging, most notably the method of Locally
Optimized Combination of Images (LOCI), and we investigate the potential of improving the detectability of
faint exoplanets through the use of advanced statistical methods based on the concepts of the ideal observer
and the Hotelling observer. We propose a formal comparison of techniques using a blind data challenge with an
evaluation of performance using the Receiver Operating Characteristic (ROC) and Localization ROC (LROC)
curves. We place particular emphasis on the understanding and modeling of realistic sources of measurement
noise in ground-based AO-corrected coronagraphs. The work reported in this paper is the result of interactions
between the co-authors during a week-long workshop on exoplanet imaging that was held in Squaw Valley,
California, in March of 2012.
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