We present a review of the ongoing research activity surrounding the adaptive optics system at the Shane telescope (ShaneAO) particularly the R&D efforts on the technology and algorithms for that will advance AO into wider application for astronomy. We are pursuing the AO challenges for whole sky coverage diffraction-limited correction down to visible science wavelengths. This demands high-order wavefront correction and bright artificial laser beacons. We present recent advancements in the development of MEMS based AO correction, woofer-tweeter architecture, wind-predictive wavefront control algorithms, atmospheric characterization, and a pulsed fiber amplifier guide star laser tuned for optical pumping of the sodium layer. We present the latest on-sky results from the new AO system and present status and experimental plans for the optical pumping guide star laser.
The advent of expensive, large-aperture telescopes and complex adaptive optics (AO) systems has strengthened the need for detailed simulation of such systems from the top of the atmosphere to control algorithms. The credibility of any simulation is underpinned by the quality of the atmosphere model used for introducing phase variations into the incident photons. Hitherto, simulations which incorporate wind layers have relied upon phase screen generation methods that tax the computation and memory capacities of the platforms on which they run. This places limits on parameters of a simulation, such as exposure time or resolution, thus compromising its utility. As aperture sizes and fields of view increase the problem will only get worse. We present an autoregressive method for evolving atmospheric phase that is efficient in its use of computation resources and allows for variability in the power contained in frozen flow or stochastic components of the atmosphere. Users have the flexibility of generating atmosphere datacubes in advance of runs where memory constraints allow to save on computation time or of computing the phase at each time step for long exposure times. Preliminary tests of model atmospheres generated using this method show power spectral density and rms phase in accordance with established metrics for Kolmogorov models.
We measure the long-term systematic component of the astrometric error in the GeMS MCAO system as a function of field radius and Ks magnitude. The experiment uses two epochs of observations of NGC 1851 separated by one month. The systematic component is estimated for each of three field of view cases (15'' radius, 30'' radius, and full field) and each of three distortion correction schemes: 8 DOF/chip + local distortion correction (LDC), 8 DOF/chip with no LDC, and 4 DOF/chip with no LDC. For bright, unsaturated stars with 13 < Ks < 16, the systematic component is < 0.2, 0.3, and 0.4 mas, respectively, for the 15'' radius, 30'' radius, and full field cases, provided that an 8 DOF/chip distortion correction with LDC (for the full-field case) is used to correct distortions. An 8 DOF/chip distortion-correction model always outperforms a 4 DOF/chip model, at all field positions and magnitudes and for all field-of-view cases, indicating the presence of high-order distortion changes. Given the order of the models needed to correct these distortions (~8 DOF/chip or 32 degrees of freedom total), it is expected that at least 25 stars per square arcminute would be needed to keep systematic errors at less than 0.3 milliarcseconds for multi-year programs. We also estimate the short-term astrometric precision of the newly upgraded Shane AO system with undithered M92 observations. Using a 6-parameter linear transformation to register images, the system delivers ~0.3 mas astrometric error over short-term observations of 2-3 minutes.
Scott Severson, Philip Choi, Katherine Badham, Dalton Bolger, Daniel Contreras, Blaine Gilbreth, Christian Guerrero, Erik Littleton, Joseph Long, Lorcan McGonigle, William Morrison, Fernando Ortega, Alex Rudy, Jonathan Wong, Erik Spjut, Christoph Baranec, Reed Riddle
We present the instrument design and first light observations of KAPAO, a natural guide star adaptive optics (AO) system for the Pomona College Table Mountain Observatory (TMO) 1-meter telescope. The KAPAO system has dual science channels with visible and near-infrared cameras, a Shack-Hartmann wavefront sensor, and a commercially available 140-actuator MEMS deformable mirror. The pupil relays are two pairs of custom off-axis parabolas and the control system is based on a version of the Robo-AO control software. The AO system and telescope are remotely operable, and KAPAO is designed to share the Cassegrain focus with the existing TMO polarimeter. We discuss the extensive integration of undergraduate students in the program including the multiple senior theses/capstones and summer assistantships amongst our partner institutions. This material is based upon work supported by the National Science Foundation under Grant No. 0960343.
The identification and prediction of time-varying wavefront errors in adaptive optics (AO) systems promises fainter limiting
guide star magnitudes and improved temporal bandwidth errors. In a new UCSC-LLNL collaboration, we aim to demonstrate
the power of predictive Fourier controllers for AO in the laboratory and on-sky. We have used the Fourier Wind
Identification technique to measure wind velocities at several telescopes, and now have demonstrated the identification of
frozen flow turbulence with a translating phase screen on a laboratory test bench.
Here, we present identification of the wind direction and velocity using telemetry data from a laboratory testbed simulating
the ShaneAO system geometry. Our wind identification system uses a Fourier decomposition technique to identify
the correlated movement of the atmosphere from WFS telemetry data, which are then used to construct a Kalman filter for
real-time operation. We demonstrate the use of an LQG controller with the ShaneAO system architecture, and show that
the effects of frozen flow turbulence can be easily identified in laboratory telemetry. We describe the adaptations made
to the LQG controller to integrate it into the dual-DM architecture of the ShaneAO system, and demonstrate that these
modifications produce stable and well-understood AO correction in the laboratory.
We describe KAPAO, our project to develop and deploy a low-cost, remote-access, natural guide star adaptive optics (AO) system for the Pomona College Table Mountain Observatory (TMO) 1-meter telescope. We use a commercially available 140-actuator BMC MEMS deformable mirror and a version of the Robo-AO control software developed by Caltech and IUCAA. We have structured our development around the rapid building and testing of a prototype system, KAPAO-Alpha, while simultaneously designing our more capable final system, KAPAO-Prime. The main differences between these systems are the prototype's reliance on off-the-shelf optics and a single visible-light science camera versus the final design's improved throughput and capabilities due to the use of custom optics and dual-band, visible and near-infrared imaging. In this paper, we present the instrument design and on-sky closed-loop testing of KAPAO-Alpha as well as our plans for KAPAO-Prime. The primarily undergraduate-education nature of our partner institutions, both public (Sonoma State University) and private (Pomona and Harvey Mudd Colleges), has enabled us to engage physics, astronomy, and engineering undergraduates in all phases of this project. This material is based upon work supported by the National Science Foundation under Grant No. 0960343.
The Spectral Energy Distribution (SED) Machine is an Integral Field Unit (IFU) spectrograph designed specifically to classify transients. It is comprised of two subsystems. A lenselet based IFU, with a 26" × 26" Field of View (FoV) and ∼ 0.75" spaxels feeds a constant resolution (R∼100) triple-prism. The dispersed rays are than imaged onto an off-the-shelf CCD detector. The second subsystem, the Rainbow Camera (RC), is a 4-band seeing-limited imager with a 12.5' × 12.5' FoV around the IFU that will allow real time spectrophotometric calibrations with a ∼ 5% accuracy. Data from both subsystems will be processed in real time using a dedicated reduction pipeline. The SED Machine will be mounted on the Palomar 60-inch robotic telescope (P60), covers a wavelength range of 370 − 920nm at high throughput and will classify transients from on-going and future surveys at a high rate. This will provide good statistics for common types of transients, and a better ability to discover and study rare and exotic ones. We present the science cases, optical design, and data reduction strategy of the SED Machine. The SED machine is currently being constructed at the Calofornia Institute of Technology, and will be comissioned on the spring of 2013.
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