Millisecond Exoplanet Imaging, II: Regression Equations and Technical Discussion

The leading difficulty in achieving the contrast necessary to directly image exoplanets and associated structures (eg. protoplanetary disks) at wavelengths ranging from the visible to the infrared are quasi-static speckles, and they are hard to distinguish from planets at the necessary level of precision. The source of the quasi-static speckles is hardware aberrations that are not compensated by the adaptive optics system. These aberrations are called non-common path aberrations (NCPA). In 2013, Frazin showed how, in principle, simultaneous millisecond (ms) telemetry from the wavefront sensor (WFS) and the science camera behind a stellar coronagraph can be used as input into a regression scheme that simultaneously and self-consistently estimates the NCPA and the sought-after image of the planetary system (the exoplanet image). The physical principle underlying the regression method is rather simple: the wavefronts, which are measured by the WFS, modulate the speckles caused by the NCPA and therefore can be used as probes of the optical system. The most important departure from realism in the author's 2013 article was the assumption that the WFS made error-free measurements. The simulations in Part I provide results on the joint regression on the NCPA and the exoplanet image from three different methods, called the ideal, the naive, and the bias-corrected estimators. The ideal estimator is not physically realizable but is a useful as a benchmark for simulation studies, but the other two are, at least in principle. This article provides the regression equations for all three of these estimators as well as a supporting technical discussion. Briefly, the naive estimator simply uses the noisy WFS measurements without any attempt to account for the errors, and the bias-corrected estimator uses statistical knowledge of the wavefronts to treat errors in the WFS measurements.Comment: 13 pages, 2 figures, submitted to JOSA

Millisecond Exoplanet Imaging, I: Method and Simulation Results

One of the top remaining science challenges in astronomical optics is the direct imaging and characterization of extrasolar planets and planetary systems. Directly imaging exoplanets from ground-based observatories requires combining high-order adaptive optics with a stellar coronagraph observing at wavelengths ranging from the visible to the mid-IR. A limiting factor in achieving the required contrast (planet-to-star intensity ratio) is quasi-static speckles, caused largely by non-common path aberrations (NCPA) in the coronagraph. Starting with a realistic simulator of a telescope with an AO system and a coronagraph, this article provides simulations of several closely related millisecond regression models requiring inputs of the measured wavefronts and science camera images. The simplest regression model, called the naive estimator, does not treat the noise and other sources of information loss in the WFS. The naive estimator provided a useful estimate of the NCPA of $\sim$ 0.5 radian RMS, with an accuracy of $\sim$ 0.06 radian RMS in one minute of simulated sky time on a magnitude 8 star. The bias-corrected estimator generalizes the regression model to account for the noise and information loss in the WFS. A simulation of the bias-corrected estimator with four minutes of sky time included an NCPA of $\sim 0.05 \,$ radian RMS and an extended exoplanet scene. The joint regression of the bias-corrected estimator simultaneously achieved an NCPA estimate with an accuracy of $\sim 5\times10^{-3} \,$radian and contrast of $\sim 10^{-5}$ on the exoplanet scene. In addition, the estimate of the exoplanet image was completely free of the subtraction artifacts that always plague differential imaging. The estimate of the exoplanet image obtained by the joint regression was nearly identical to the image obtained by subtraction of a perfectly known point-spread function.Comment: 16 pages, 18 Figures, 4 Tables, submitted to JOSA

Student Composers\u27 Recital 2019

This special program features world-premiere performances of original works created by current student composers of the KSU School of Music under the supervision of KSU Composer-in-Residence, Dr. Laurence Sherr, and faculty composer Jennifer Mitchell. An exciting feature of the concert will be the premiere of a 30-minute, Broadway-style musical by Nicholas Felder. The musical, titled Rick and Josie, is a love story performed by students in the School of Music and Department of Theater and Performance Studies with accompaniment by faculty member Judith Cole. Also featured will be a woodwind quintet by Ben Champion plus several additional student works.https://digitalcommons.kennesaw.edu/musicprograms/2184/thumbnail.jp

Implicit electric field Conjugation: Data-driven focal plane control

Direct imaging of Earth-like planets is one of the main science cases for the next generation of extremely large telescopes. This is very challenging due to the star-planet contrast that must be overcome. Most current high-contrast imaging instruments are limited in sensitivity at small angular separations due to non-common path aberrations (NCPA). The NCPA leak through the coronagraph and create bright speckles that limit the on-sky contrast and therefore also the post-processed contrast. We aim to remove the NCPA by active focal plane wavefront control using a data-driven approach. We developed a new approach to dark hole creation and maintenance that does not require an instrument model. This new approach is called implicit Electric Field Conjugation (iEFC) and it can be empirically calibrated. This makes it robust for complex instruments where optical models might be difficult to realize. Numerical simulations have been used to explore the performance of iEFC for different coronagraphs. The method was validated on the internal source of the Magellan Adaptive Optics eXtreme (MagAO-X) instrument to demonstrate iEFC's performance on a real instrument. Numerical experiments demonstrate that iEFC can achieve deep contrast below $10^{-9}$ with several coronagraphs. The method is easily extended to broadband measurements and the simulations show that a bandwidth up to 40% can be handled without problems. Experiments with MagAO-X showed a contrast gain of a factor 10 in a broadband light and a factor 20 to 200 in narrowband light. A contrast of $5\cdot10^{-8}$ was achieved with the Phase Apodized Pupil Lyot Coronagraph at 7.5 $\lambda/D$. The new iEFC method has been demonstrated to work in numerical and lab experiments. It is a method that can be empirically calibrated and it can achieve deep contrast. This makes it a valuable approach for complex ground-based high-contrast imaging systems.Comment: 13 pages, 12 figures accepted by A&

Toward on-sky adaptive optics control using reinforcement learning Model-based policy optimization for adaptive optics

Context. The direct imaging of potentially habitable exoplanets is one prime science case for the next generation of high contrast imaging instruments on ground-based, extremely large telescopes. To reach this demanding science goal, the instruments are equipped with eXtreme Adaptive Optics (XAO) systems which will control thousands of actuators at a framerate of kilohertz to several kilohertz. Most of the habitable exoplanets are located at small angular separations from their host stars, where the current control laws of XAO systems leave strong residuals. Aims. Current AO control strategies such as static matrix-based wavefront reconstruction and integrator control suffer from a temporal delay error and are sensitive to mis-registration, that is, to dynamic variations of the control system geometry. We aim to produce control methods that cope with these limitations, provide a significantly improved AO correction, and, therefore, reduce the residual flux in the coronagraphic point spread function (PSF). Methods. We extend previous work in reinforcement learning for AO. The improved method, called the Policy Optimization for Adaptive Optics (PO4AO), learns a dynamics model and optimizes a control neural network, called a policy. We introduce the method and study it through numerical simulations of XAO with Pyramid wavefront sensor (PWFS) for the 8-m and 40-m telescope aperture cases. We further implemented PO4AO and carried out experiments in a laboratory environment using Magellan Adaptive Optics eXtreme system (MagAO-X) at the Steward laboratory. Results. PO4AO provides the desired performance by improving the coronagraphic contrast in numerical simulations by factors of 3-5 within the control region of deformable mirror and PWFS, both in simulation and in the laboratory. The presented method is also quick to train, that is, on timescales of typically 5-10 s, and the inference time is sufficiently small (Peer reviewe

Toward on-sky adaptive optics control using reinforcement learning Model-based policy optimization for adaptive optics

Context. The direct imaging of potentially habitable exoplanets is one prime science case for the next generation of high contrast imaging instruments on ground-based, extremely large telescopes. To reach this demanding science goal, the instruments are equipped with eXtreme Adaptive Optics (XAO) systems which will control thousands of actuators at a framerate of kilohertz to several kilohertz. Most of the habitable exoplanets are located at small angular separations from their host stars, where the current control laws of XAO systems leave strong residuals. Aims. Current AO control strategies such as static matrix-based wavefront reconstruction and integrator control suffer from a temporal delay error and are sensitive to mis-registration, that is, to dynamic variations of the control system geometry. We aim to produce control methods that cope with these limitations, provide a significantly improved AO correction, and, therefore, reduce the residual flux in the coronagraphic point spread function (PSF). Methods. We extend previous work in reinforcement learning for AO. The improved method, called the Policy Optimization for Adaptive Optics (PO4AO), learns a dynamics model and optimizes a control neural network, called a policy. We introduce the method and study it through numerical simulations of XAO with Pyramid wavefront sensor (PWFS) for the 8-m and 40-m telescope aperture cases. We further implemented PO4AO and carried out experiments in a laboratory environment using Magellan Adaptive Optics eXtreme system (MagAO-X) at the Steward laboratory. Results. PO4AO provides the desired performance by improving the coronagraphic contrast in numerical simulations by factors of 3-5 within the control region of deformable mirror and PWFS, both in simulation and in the laboratory. The presented method is also quick to train, that is, on timescales of typically 5-10 s, and the inference time is sufficiently small (Peer reviewe

HIP 67506 C: MagAO-X Confirmation of a New Low-Mass Stellar Companion to HIP 67506 A

We report the confirmation of HIP 67506 C, a new stellar companion to HIP 67506 A. We previously reported a candidate signal at 2$\lambda$/D (240~mas) in L$^{\prime}$ in MagAO/Clio imaging using the binary differential imaging technique. Several additional indirect signals showed that the candidate signal merited follow-up: significant astrometric acceleration in Gaia DR3, Hipparcos-Gaia proper motion anomaly, and overluminosity compared to single main sequence stars. We confirmed the companion, HIP 67506 C, at 0.1" with MagAO-X in April, 2022. We characterized HIP 67506 C MagAO-X photometry and astrometry, and estimated spectral type K7-M2; we also re-evaluated HIP 67506 A in light of the close companion. Additionally we show that a previously identified 9" companion, HIP 67506 B, is a much further distant unassociated background star. We also discuss the utility of indirect signposts in identifying small inner working angle candidate companions.Comment: 10 pages, 9 figures, 4 tables, accepted to MNRA

Vector-apodizing phase plate coronagraph: design, current performance, and future development [Invited]

Instrumentatio

Countermeasures for side impact - final report.

National Highway Traffic Safety Administration, Washington, D.C.Mode of access: Internet.Author corporate affiliation: Dynamic Science, Inc., Phoenix, Ariz.Report covers the period June 1979 - Aug 1982. Released 1985Subject code: DGEOSSubject code: ENJJSubject code: JJSubject code: JLMSubject code: WNBFSubject code: WSM*NLSISubject code: WVIFKCSubject code: XMC

Countermeasures for side impact - final report: volume III, appendices E - I.

National Highway Traffic Safety Administration, Washington, D.C.Mode of access: Internet.Author corporate affiliation: Dynamic Science, Inc., Phoenix, Ariz.Report covers the period June 1979 - Aug 1982. Released 1985Subject code: DGEOSSubject code: ENJJSubject code: JJSubject code: JLMSubject code: WNBFSubject code: WSM*NLSISubject code: WVIFKCSubject code: XMC