Image plane wavefront sensing and Kalman filtering for automated alignment of off-axis aspherics.

Automated alignment can significantly increase optical system precision and flexibility, and reduce time and labor costs in system setup and maintenance. We present an automated alignment technique on a double off-axis parabolic mirror system, which poses challenging alignment problems due to the mirrors' high sensitivity to aberrations, rotational asymmetry, and non-orthogonality in stage adjustments. In our methodology, we use focal plane wavefront sensing to eliminate the non-common path error, increase optical throughput, and reduce cost and system complexity. We incorporate model-based optimal estimation and control to better handle the nonlinearity, model uncertainty, and noise. Using either an iterated extended Kalman filter or a square-root unscented Kalman filter as the optimal nonlinear misalignment state estimator, we are able to consistently reduce the linear misalignment from around 1 mm to <5µm and the angular misalignment from around 500 to <6a r c s e c in simulation, achieving a final wavefront error of <5∗10-5 waves in the field of view when tested at wavelength 635 nm. We discover a multi-state coupling effect, which implies that different misalignment states have compensating effects on system measurements, thus interfering with the estimator's observation of misalignment state changes. We further investigate the coupling's effects on alignment quality through observability analysis.

Amplitude and phase retrieval with simultaneous diversity estimation using expectation maximization.

Iterative amplitude and phase retrieval algorithms have been proven to accurately reconstruct arbitrary wavefronts from multiple intensity measurements when system parameters are known exactly, given the ability to induce phase diversity between images. Such sets of intensity images with phase diversity can be generated by moving a lens in the optical system, but any position error on the lens will degenerate the reconstruction result. We demonstrate the use of an expectation-maximization algorithm with Kalman smoothing for recovering both the complex field and the lens position from a stack of intensity images. Our method successfully reduces the mean-squared-error of the estimated wavefront in comparison to an approach without position error estimation. We present and discuss the results of using a Kalman smoother and nonlinear least-squares optimization for the estimation of the moving lens position.

Automated alignment of a reconfigurable optical system using focal-plane sensing and Kalman filtering.

Automation of alignment tasks can provide improved efficiency and greatly increase the flexibility of an optical system. Current optical systems with automated alignment capabilities are typically designed to include a dedicated wavefront sensor. Here, we demonstrate a self-aligning method for a reconfigurable system using only focal plane images. We define a two lens optical system with 8 degrees of freedom. Images are simulated given misalignment parameters using ZEMAX software. We perform a principal component analysis on the simulated data set to obtain Karhunen-Loève modes, which form the basis set whose weights are the system measurements. A model function, which maps the state to the measurement, is learned using nonlinear least-squares fitting and serves as the measurement function for the nonlinear estimator (extended and unscented Kalman filters) used to calculate control inputs to align the system. We present and discuss simulated and experimental results of the full system in operation.

Performance of the Gemini Planet Imager's adaptive optics system.

The Gemini Planet Imager's adaptive optics (AO) subsystem was designed specifically to facilitate high-contrast imaging. A definitive description of the system's algorithms and technologies as built is given. 564 AO telemetry measurements from the Gemini Planet Imager Exoplanet Survey campaign are analyzed. The modal gain optimizer tracks changes in atmospheric conditions. Science observations show that image quality can be improved with the use of both the spatially filtered wavefront sensor and linear-quadratic-Gaussian control of vibration. The error budget indicates that for all targets and atmospheric conditions AO bandwidth error is the largest term.

First light of the Gemini Planet imager.

The Gemini Planet Imager is a dedicated facility for directly imaging and spectroscopically characterizing extrasolar planets. It combines a very high-order adaptive optics system, a diffraction-suppressing coronagraph, and an integral field spectrograph with low spectral resolution but high spatial resolution. Every aspect of the Gemini Planet Imager has been tuned for maximum sensitivity to faint planets near bright stars. During first-light observations, we achieved an estimated H band Strehl ratio of 0.89 and a 5-σ contrast of 10(6) at 0.75 arcseconds and 10(5) at 0.35 arcseconds. Observations of Beta Pictoris clearly detect the planet, Beta Pictoris b, in a single 60-s exposure with minimal postprocessing. Beta Pictoris b is observed at a separation of 434 ± 6 milliarcseconds (mas) and position angle 211.8 ± 0.5°. Fitting the Keplerian orbit of Beta Pic b using the new position together with previous astrometry gives a factor of 3 improvement in most parameters over previous solutions. The planet orbits at a semimajor axis of [Formula: see text] near the 3:2 resonance with the previously known 6-AU asteroidal belt and is aligned with the inner warped disk. The observations give a 4% probability of a transit of the planet in late 2017.

Computer vision applications for coronagraphic optical alignment and image processing.

Modern coronagraphic systems require very precise alignment between optical components and can benefit greatly from automated image processing. We discuss three techniques commonly employed in the fields of computer vision and image analysis as applied to the Gemini Planet Imager, a new facility instrument for the Gemini South Observatory. We describe how feature extraction and clustering methods can be used to aid in automated system alignment tasks, and also present a search algorithm for finding regular features in science images used for calibration and data processing. Along with discussions of each technique, we present our specific implementation and show results of each one in operation.

Chaotic exchange of solid material between planetary systems: implications for lithopanspermia.

We examined a low-energy mechanism for the transfer of meteoroids between two planetary systems embedded in a star cluster using quasi-parabolic orbits of minimal energy. Using Monte Carlo simulations, we found that the exchange of meteoroids could have been significantly more efficient than previously estimated. Our study is relevant to astrobiology, as it addresses whether life on Earth could have been transferred to other planetary systems in the Solar System's birth cluster and whether life on Earth could have been transferred from beyond the Solar System. In the Solar System, the timescale over which solid material was delivered to the region from where it could be transferred via this mechanism likely extended to several hundred million years (as indicated by the 3.8-4.0 Ga epoch of the Late Heavy Bombardment). This timescale could have overlapped with the lifetime of the Solar birth cluster (∼100-500 Myr). Therefore, we conclude that lithopanspermia is an open possibility if life had an early start. Adopting parameters from the minimum mass solar nebula, considering a range of planetesimal size distributions derived from observations of asteroids and Kuiper Belt objects and theoretical coagulation models, and taking into account Oort Cloud formation models, we discerned that the expected number of bodies with mass>10 kg that could have been transferred between the Sun and its nearest cluster neighbor could be of the order of 10(14) to 3·10(16), with transfer timescales of tens of millions of years. We estimate that of the order of 3·10(8)·l (km) could potentially be life-bearing, where l is the depth of Earth's crust in kilometers that was ejected as the result of the early bombardment.

On Advanced Estimation Techniques for Exoplanet Detection and Characterization Using Ground-based Coronagraphs.

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.