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The Automated Planet Finder (APF) is a facility purpose-built for the discovery and characterization of extrasolar planets through high-cadence Doppler velocimetry of the reflex barycentric accelerations of their host stars. Located atop Mt. Hamilton, the APF facility consists of a 2.4-m telescope and its Levy spectrometer, an optical echelle spectrometer optimized for precision Doppler velocimetry. APF features a fixed format spectral range from 374 nm - 970 nm, and delivers a Throughput (resolution * slit width product) of 114,000 arc-seconds, with spectral resolutions up to 150,000. Overall system efficiency (fraction of photons incident on the primary mirror that are detected by the science CCD) on blaze at 560 nm in planet-hunting mode is 15%. First-light tests on the RV standard stars HD 185144 and HD 9407 demonstrate sub-meter per second precision (RMS per observation) held over a 3-month period. This paper reviews the basic features of the telescope, dome, and spectrometer, and gives a brief summary of first-light performance.
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We report initial performance results emerging from 600 hours of observations with the Automated Planet Finder (APF) telescope and Levy Spectrometer located at UCO/Lick Observatory. We have obtained multiple spectra of 80 G, K and M-type stars, which comprise 4,954 individual Doppler radial velocity (RV) measurements with a median internal uncertainty of 1.35 ms$^{-1}$. We find a strong, expected correlation between the number of photons accumulated in the 5000-6200$AA$ iodine region of the spectrum, and the resulting internal uncertainty estimates. Additionally, we find an offset between the population of G and K stars and the M stars within the data set when comparing these parameters. As a consequence of their increased spectral line densities, M-type stars permit the same level of internal uncertainty with 2x fewer photons than G-type and K-type stars. When observing M stars, we show that the APF/Levy has essentially the same speed-on-sky as Keck/HIRES for precision RVs. In the interest of using the APF for long-duration RV surveys, we have designed and implemented a dynamic scheduling algorithm. We discuss the operation of the scheduler, which monitors ambient conditions and combines on-sky information with a database of survey targets to make intelligent, real-time targeting decisions.
The productivity of Lick Observatory (LO) is reviewed over the years from 1965 to 2019, a 55 yr period which commences with the Shane 3 m telescope being the second-largest astronomical reflector in the world, but transitions into the era of 10 m ground-based optical telescopes. The metric of productivity used here is the annual number of refereed papers within which are presented results that are based at least in part on observations made with the telescopes of LO on Mount Hamilton. Criteria are set forth that have guided the counting of this metric. A bibliography of papers pertinent to observations from Lick Observatory has been compiled, and is made available through a NASA ADS library. The overall productivity of the observatory, counting all telescopes, went through a broad maximum between the years 1975 and 1982. This period also corresponds to a maximum in productivity of the Shane 3 m telescope. An author network shows that this period is attended by the introduction of digital detector systems at LO, particularly at the Shane telescope. Following 1983 the overall productivity of LO shows a net long-term decrease but with two other lesser peaks superimposed on that decrease. A slightly smaller peak occurs around 1996 and is associated with programs taking advantage of CCD spectrometers at both cassegrain and coud{e} foci of the Shane telescope. A third lesser peak around 2012 can be attributed to a rise in extragalactic supernova studies originating out of UC Berkeley. Author networks serve to document the UC astronomical communities that were using LO telescopes at these peak times. Institutional affiliations of first authors are documented.
A new high-order adaptive optics system is now being commissioned at the Lick Observatory Shane 3-meter telescope in California. This system uses a high return efficiency sodium beacon and a combination of low and high-order deformable mirrors to achieve diffraction-limited imaging over a wide spectrum of infrared science wavelengths covering 0.8 to 2.2 microns. We present the design performance goals and the first on-sky test results. We discuss several innovations that make this system a pathfinder for next generation AO systems. These include a unique woofer-tweeter control that provides full dynamic range correction from tip/tilt to 16 cycles, variable pupil sampling wavefront sensor, new enhanced silver coatings developed at UC Observatories that improve science and LGS throughput, and tight mechanical rigidity that enables a multi-hour diffraction- limited exposure in LGS mode for faint object spectroscopy science.
The Gemini Planet Imager (GPI) is currently in its final Acceptance & Testing stages. GPI is an XAO system based on a tweeter & woofer architecture (43 & 9 actuators respectively across the pupil), with the tweeter being a Boston Michromachines $64^2$ MEMS device. The XAO AO system is tightly integrated with a Lyot apodizing coronagraph. Acceptance testing started in February 2013 at the University of California, Santa Cruz. A conclusive acceptance review was held in July 2013 and the instrument was found ready for shipment to the Gemini South telescope on Cerro Pachon, Chile. Commissioning at the telescope will take place by the end of 2013, matching the summer window of the southern hemisphere. According to current estimates the 3 year planet finding campaign (890 allocated hours) might discover, image, and spectroscopically analyze 20 to 40 new exo-planets. Final acceptance testing of the integrated instrument can always bring up surprises when using cold chamber and flexure rig installations. The latest developments are reported. Also, we will give an overview of GPIs lab performance, the interplay between subsystems such as the calibration unit (CAL) with the AO bench. We report on-going optimizations on the AO controller loop to filter vibrations and last but not least achieved contrast performance applying speckle nulling. Furthermore, we will give an outlook of possible but challenging future upgrades as the implementation of a predictive controller or exchanging the conventional 48x48 SH WFS with a pyramid. With the ELT era arising, GPI will proof as a versatile and path-finding testbed for AO technologies on the next generation of ground-based telescopes.
We present an algorithm using Principal Component Analysis (PCA) to subtract galaxies from imaging data, and also two algorithms to find strong, galaxy-scale gravitational lenses in the resulting residual image. The combined method is optimized to find full or partial Einstein rings. Starting from a pre-selection of potential massive galaxies, we first perform a PCA to build a set of basis vectors. The galaxy images are reconstructed using the PCA basis and subtracted from the data. We then filter the residual image with two different methods. The first uses a curvelet (curved wavelets) filter of the residual images to enhance any curved/ring feature. The resulting image is transformed in polar coordinates, centered on the lens galaxy center. In these coordinates, a ring is turned into a line, allowing us to detect very faint rings by taking advantage of the integrated signal-to-noise in the ring (a line in polar coordinates). The second way of analysing the PCA-subtracted images identifies structures in the residual images and assesses whether they are lensed images according to their orientation, multiplicity and elongation. We apply the two methods to a sample of simulated Einstein rings, as they would be observed with the ESA Euclid satellite in the VIS band. The polar coordinates transform allows us to reach a completeness of 90% and a purity of 86%, as soon as the signal-to-noise integrated in the ring is higher than 30, and almost independent of the size of the Einstein ring. Finally, we show with real data that our PCA-based galaxy subtraction scheme performs better than traditional subtraction based on model fitting to the data. Our algorithm can be developed and improved further using machine learning and dictionary learning methods, which would extend the capabilities of the method to more complex and diverse galaxy shapes.
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