Status and performance of the Gemini Planet Imager adaptive optics system

The Gemini Planet Imager is a high-contrast near-infrared instrument specifically designed to image exoplanets and circumstellar disks over a narrow field of view. We use science data and AO telemetry taken during the first 1.5 yr of the GPI Exoplanet Survey to quantify the performance of the AO system. In a typical 60 sec H-band exposure, GPI achieves a 5$\sigma$ raw contrast of 10$^{-4}$ at 0.4"; typical final 5$\sigma$ contrasts for full 1 hr sequences are more than 10 times better than raw contrasts. We find that contrast is limited by bandwidth wavefront error over much of the PSF. Preliminary exploratory factor analysis can explain 60-70% of the variance in raw contrasts with combinations of seeing and wavefront error metrics. We also examine the effect of higher loop gains on contrast by comparing wavefront error maps reconstructed from AO telemetry to concurrent IFS images. These results point to several ways that GPI performance could be improved in software or hardware.Comment: 15 pages, 11 figure

Adaptive Wavefront Calibration and Control for the Gemini Planet Imager

Quasi-static errors in the science leg and internal AO flexure will be corrected. Wavefront control will adapt to current atmospheric conditions through Fourier modal gain optimization, or the prediction of atmospheric layers with Kalman filtering

Fast minimum variance wavefront reconstruction for extremely large telescopes

We present a new algorithm, FRiM (FRactal Iterative Method), aiming at the reconstruction of the optical wavefront from measurements provided by a wavefront sensor. As our application is adaptive optics on extremely large telescopes, our algorithm was designed with speed and best quality in mind. The latter is achieved thanks to a regularization which enforces prior statistics. To solve the regularized problem, we use the conjugate gradient method which takes advantage of the sparsity of the wavefront sensor model matrix and avoids the storage and inversion of a huge matrix. The prior covariance matrix is however non-sparse and we derive a fractal approximation to the Karhunen-Loeve basis thanks to which the regularization by Kolmogorov statistics can be computed in O(N) operations, N being the number of phase samples to estimate. Finally, we propose an effective preconditioning which also scales as O(N) and yields the solution in 5-10 conjugate gradient iterations for any N. The resulting algorithm is therefore O(N). As an example, for a 128 x 128 Shack-Hartmann wavefront sensor, FRiM appears to be more than 100 times faster than the classical vector-matrix multiplication method.Comment: to appear in the Journal of the Optical Society of America

Science and Technology Review April/May 2012

This month's issue has the following articles: (1) Lawrence Livermore as the 'Go-To' National Security Laboratory - Commentary by Penrose (Parney) C. Albright; (2) Launching Traffic Cameras into Space - The Space-Based Telescopes for Actionable Refinement of Ephemeris project is designing nanosatellites to more accurately determine the trajectory of space objects orbiting Earth; (3)An Improved Tool for Nuclear Forensics - Resonance ionization mass spectrometry provides rapid isotopic analysis for studying materials derived from nuclear events; (4) A Simple Way to Better Protect Soldiers against Head Trauma - A modest increase in the foam padding used in Army helmets could significantly reduce brain injuries; and (5) Shocking Aluminum for Greater Understanding - Experiments using a laser beam to hit a thin film of aluminum provide an unprecedented look into the physics of shock waves traveling through a metal