The Keck Planet Finder (KPF) is a fiber-fed, high-resolution, echelle spectrometer that specializes in the discovery and characterization of exoplanets using Doppler spectroscopy. In designing KPF, the guiding principles were high throughput to promote survey speed and access to faint targets, and high stability to keep uncalibrated systematic Doppler measurement errors below 30 cm s−1. KPF achieves optical illumination stability with a tip-tilt injection system, octagonal cross-section optical fibers, a double scrambler, and active fiber agitation. The optical bench and optics with integral mounts are made of Zerodur to provide thermo-mechanical stability. The spectrometer includes a slicer to reformat the optical input, green and red channels (445–600 nm and 600–870 nm), and achieves a resolving power of ∼97,000. Additional subsystems include a separate, medium-resolution UV spectrometer (383–402 nm) to record the Ca II H & K lines, an exposure meter for real-time flux monitoring, a solar feed for sunlight injection, and a calibration system with a laser frequency comb and etalon for wavelength calibration. KPF was installed and commissioned at the W. M. Keck Observatory in late 2022 and early 2023 and is now in regular use for scientific observations. This paper presents an overview of the as-built KPF instrument and its subsystems, design considerations, and initial on-sky performance.
A number of popular software tools in the public domain are used by astronomers, professional and amateur
alike, but some of the tools that have similar purposes cannot be easily interchanged, owing to the lack of a
common standard. For the case of image distortion, SCAMP and SExtractor, available from Astromatic.net,
perform astrometric calibration and source-object extraction on image data, and image-data geometric distortion
is computed in celestial coordinates with polynomial coefficients stored in the FITS header with the PV i_j
keywords. Another widely-used astrometric-calibration service, Astrometry.net, solves for distortion in pixel
coordinates using the SIP convention that was introduced by the Spitzer Science Center. Up until now, due to
the complexity of these distortion representations, it was very difficult to use the output of one of these packages
as input to the other. New Python software, along with faster-computing C-language translations, have been
developed at the Infrared Processing and Analysis Center (IPAC) to convert FITS-image headers from PV to
SIP and vice versa. It is now possible to straightforwardly use Astrometry.net for astrometric calibration and
then SExtractor for source-object extraction. The new software also enables astrometric calibration by SCAMP
followed by image visualization with tools that support SIP distortion, but not PV . The software has been
incorporated into the image-processing pipelines of the Palomar Transient Factory (PTF), which generate FITS
images with headers containing both distortion representations. The software permits the conversion of archived
images, such as from the Spitzer Heritage Archive and NASA/IPAC Infrared Science Archive, from SIP to PV
or vice versa. This new capability renders unnecessary any new representation, such as the proposed TPV
distortion convention.
N. Law, R. Dekany, G. Rahmer, D. Hale, R. Smith, R. Quimby, E. Ofek, M. Kasliwal, J. Zolkower, V. Velur, J. Henning, K. Bui, D. McKenna, P. Nugent, J. Jacobsen, R. Walters, J. Bloom, J. Surace, C. Grillmair, R. Laher, S. Mattingly, S. Kulkarni
The Palomar Transient Factory (PTF) is a new fully-automated, wide-field survey conducting a systematic exploration
of the optical transient sky. The transient survey is performed using a new 8.1 square degree, 101 megapixel camera
installed on the 48-inch Samuel Oschin Telescope at Palomar Observatory. The PTF Camera achieved first light at the
end of 2008, completed commissioning in July 2009, and is now in routine science operations. The camera is based on
the CFH12K camera, and was extensively modified for use on the 48-inch telescope. A field-flattening curved window
was installed, the cooling system was re-engineered and upgraded to closed-cycle, custom shutter and filter exchanger
mechanisms were added, new custom control software was written, and many other modifications were made. We here
describe the performance of these new systems during the first year of Palomar Transient Factory operations, including
a detailed and long term on-sky performance characterization. We also describe lessons learned during the construction
and commissioning of the upgraded camera, the photometric and astrometric precision currently achieved with the PTF
camera, and briefly summarize the first supernova results from the PTF survey.
KEYWORDS: Large Synoptic Survey Telescope, Data modeling, Astronomy, Calibration, Observatories, Cameras, Data processing, Telescopes, Image quality, Point spread functions
LSST will have a Science Data Quality Assessment (SDQA) subsystem for the assessment of the data products that will
be produced during the course of a 10 yr survey. The LSST will produce unprecedented volumes of astronomical data as
it surveys the accessible sky every few nights. The SDQA subsystem will enable comparisons of the science data with
expectations from prior experience and models, and with established requirements for the survey. While analogous
systems have been built for previous large astronomical surveys, SDQA for LSST must meet a unique combination of
challenges. Chief among them will be the extraordinary data rate and volume, which restricts the bulk of the quality
computations to the automated processing stages, as revisiting the pixels for a post-facto evaluation is prohibitively
expensive. The identification of appropriate scientific metrics is driven by the breadth of the expected science, the scope
of the time-domain survey, the need to tap the widest possible pool of scientific expertise, and the historical tendency of
new quality metrics to be crafted and refined as experience grows. Prior experience suggests that contemplative, off-line
quality analyses are essential to distilling new automated quality metrics, so the SDQA architecture must support
integrability with a variety of custom and community-based tools, and be flexible to embrace evolving QA demands.
Finally, the time-domain nature of LSST means every exposure may be useful for some scientific purpose, so the model
of quality thresholds must be sufficiently rich to reflect the quality demands of diverse science aims.
KEYWORDS: Databases, Data archive systems, Data processing, Space operations, Data centers, Astronomy, Calibration, Space telescopes, Infrared astronomy, Image processing
Data Quality Analysis (DQA) for astronomical infrared maps and spectra acquired by NASA's Spitzer Space Telescope is one of the important functions performed in routine science operations at the Spitzer Science Center of the California Institute of Technology. A DQA software system has been implemented to display, analyze and grade Spitzer science data. This supports the project requirement that the science data be verified after calibration and before archiving and subsequent release to the astronomical community. The software has an interface for browsing the mission data and for visualizing images and spectra. It accesses supporting data in the operations database and updates the database with DQA grading information. The system has worked very well since the beginning of the Spitzer observatory's routine phase of operations, and can be regarded as a model for DQA operations in future space science missions.
KEYWORDS: Human-machine interfaces, Java, Statistical analysis, Data processing, Systems modeling, Error analysis, Space telescopes, Photometry, Diagnostics, Systems engineering
A graphical user interface (GUI) for bandmerging is presented. The purpose of the Bandmerge GUI is to provide an integrated graphical user interface for running the bandmerge module and its support modules to provide astronomers with an interactive tool for bandmerging. The bandmerge module identifies multi-band detections of an individual point source and merges the information in the different bands into a single record of the source. The developed Java Application provides an interface to downlink software, which is normally invoked on the command line. With the Bandmerge GUI, a SPITZER general user can select the data to be processed, specify processing parameters, and invoke the Bandmerge pipelines.
A new nonlinear diffusion filtering scheme based on a nonlinear diffusion equation with a variable scale parameter is developed to preserve faint point sources while smoothing images for segmentation purposes. Application of the proposed approach to simulated, as well as to real images obtained by the Spitzer Space Telescope and by the Chandra X-ray Observatory reduced the Gaussian and Poisson noise successfully, while preserving both point sources and diffuse structures.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.