Optimal merging of point sources extracted from Spitzer Space Telescope data in multiple infrared passbands versus simple general source association

For collating point-source flux measurements derived from multiple infrared passbands of Spitzer-Space-Telescope data – e.g., channels 1-4 of the Infrared Array Camera (IRAC) and channels 1-3 of the Multiband Imaging Pho- tometer for Spitzer (MIPS) – it is best to use the ‘bandmerge’ software developed at the Spitzer Science Center rather than the relatively simple method of general source association (GSA). The former method uses both source positions and positional uncertainties to form a chi-squared statistic that can be thresholded for optimal matching, while the latter method finds nearest neighbors across bands that fall within a user-specified radius of the primary source. Our assertion is supported by our study of completeness (C) vs. reliability (R) for the two methods, which involved MIPS-24/IRAC-1 matches in the SWIRE Chandra Deep Field South. Both methods can achieve C = 98%, but with R = 92.7% for GSA vs. R = 97.4% for bandmerge. With almost a factor of three lower in unreliability (1 − R), bandmerge is the clear winner of this comparison

Optimal Point-Source Extraction for Spitzer IRS Spectra

A new optimal-extraction technique has been developed for deriving point-source spectra from data taken by the Infrared Spectrograph (IRS) on-board the Spitzer Space Telescope. The new technique gives improvements of up to a factor of two in the signal-to-noise ratio (S/N) for faint (< 10 mJy) sources, corresponding to an effective quadrupling of the exposure time. Regular extraction consists of an even-weighted summing of pixel values at the same wavelength. Optimal extraction weights each pixel by its S/N, estimated using the spatial profile of a bright calibration star and data uncertainties. Additionally, the optimal-extraction calculations are performed in “rectified” space, and so a natural by-product of the processing is a useful output file containing the rectified image. The optimal-extraction technique is unsuitable for extended sources and best only for point sources

Franck-Condon factors and observed band strength distribution in the vibrational structure of the Ag_2 D-X band system

Potential curves for the X_1Σ_g^+ and D_1Σ_u^+ states of three diatomic silver isotopomers, ^(107)Ag_2, ^(107)Ag^(109)Ag and ^(109)Ag_2, were determined from the best available molecular constants by the Rydberg-Klein-Rees method. From these potentials, Franck-Condon factors and band-origin wave numbers were computed, and the reliability of the obtained values was verified by comparison with the observed band strength distribution and the measured band origin positions in a previously recorded D-X spectrum. The ratios of the Franck-Condon factors to those of corresponding isotopic bands were found to be very close to unity, revealing only a very small isotopic effect on the Franck Condon factors of Ag_2 D-X bands. The isotopic shifts of the calculated band origins agree well with previously measured displacements of band heads

Spitzer IRS Pipelines for General Users

An effort is underway to make the Spitzer InfraRed Spectrograph (IRS) data-processing pipelines available for use by astronomers worldwide. This will allow users to reprocess raw data downloaded from the Spitzer archive with customized calibration files, updated operational parameters, and/or a modified list of processing steps. The pipelines will create all standard BCD (basic calibrated data) and post-BCD products, plus additional intermediate products. The pipelines will be made up of newly developed Perl and C-shell ``executive'' scripts, plus the binary-executable modules currently used in operations (the modules' source code will not be distributed, however). The scripts are being designed for ease of use and will facilitate user-customization. The operating systems targeted for support are Mac OS X, Linux, Solaris, and possibly Windows

The Outer Halo of the Milky Way as Probed by RR Lyr Variables from the Palomar Transient Facility

RR Lyr stars are ideal massless tracers that can be used to study the total mass and dark matter content of the outer halo of the Milky Way. This is because they are easy to find in the light curve databases of large stellar surveys and their distances can be determined with only knowledge of the light curve. We present here a sample of 112 RR Lyr beyond 50 kpc in the outer halo of the Milky Way, excluding the Sgr streams, for which we have obtained moderate resolution spectra with Deimos on the Keck 2 Telescope. Four of these have distances exceeding 100 kpc. These were selected from a much larger set of 447 candidate RR Lyr which were datamined using machine learning techniques applied to the light curves of variable stars in the Palomar Transient Facility database. The observed radial velocities taken at the phase of the variable corresponding to the time of observation were converted to systemic radial velocities in the Galactic standard of rest. From our sample of 112 RR Lyr we determine the radial velocity dispersion in the outer halo of the Milky Way to be ~90 km/s at 50 kpc falling to about 65 km/s near 100 kpc once a small number of major outliers are removed. With reasonable estimates of the completeness of our sample of 447 candidates and assuming a spherical halo, we find that the stellar density in the outer halo declines as the -4 power of r.Comment: Accepted for publication in the Ap

LSST Science Data Quality Analysis Subsystem Design

The Large Synoptic Survey Telescope (LSST) will have a Science Data Quality Analysis (SDQA) subsystem for vetting its unprecedented volume of astronomical image data. The SDQA subsystem inhabits three basic realms: image processing, graphical-user-interface (GUI) tools, and alarms/reporting. During pipeline image processing, SDQA data are computed for the images and astronomical sources extracted from the images, and utilized to grade the images and sources. Alarms are automatically sent, if necessary, to initiate swift response to problems found. Both SDQA data and machine-determined grades are stored in a database. At the end of a data-processing interval, e.g., nightly processing or data-release reprocessing, automatic SDQA reports are generated from SDQA data and grades queried from the database. The SDQA reports summarize the science data quality and provide feedback to telescope, camera, facility, observation-scheduling and data-processing personnel. During operations, GUI tools facilitate visualization of image and SDQA data in a variety of ways that allow a small SDQA-operations team of humans to quickly and easily perform manual SDQA on a substantial fraction of LSST data products, and possibly reassign SDQA grades as a result of the visual inspection

Franck–Condon factors and observed band strength distribution in the vibrational structure of the Ag2 D-X band system

TPotential curves for the X1Sg+ and D1Su+ states of three diatomic silver isotopomers, 107Ag2, 107Ag109Ag and 109Ag2, were determined from the best available molecular constants by the Rydberg–Klein–Rees method. From these potentials, Franck–Condon factors and band-origin wavenumbers were computed, and the reliability of the obtained values was verified by comparison with the observed band strength distribution and the measured band origin po¬sitions in a previously recorded D-X spectrum. The ratios of the Franck–Con¬don factors to those of corresponding isotopic bands were found to be very close to unity, revealing only a very small isotopic effect on the Franck–Condon factors of Ag2 D-X bands. The isotopic shifts of the calculated band origins agree well with previously measured displacements of band heads

Science data quality assessment for the Large Synoptic Survey Telescope

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