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Register a new userCASSIS: The Cornell Atlas of Spitzer/IRS Sources
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Added by
Vianney Lebouteiller
Publication date
2011
fields
Physics
and research's language is
English
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We present the spectral atlas of sources observed in low resolution with the Infrared Spectrograph on board the Spitzer Space Telescope. More than 11,000 distinct sources were extracted using a dedicated algorithm based on the SMART software with an optimal extraction (AdOpt package). These correspond to all 13,000 low resolution observations of fixed objects (both single source and cluster observations). The pipeline includes image cleaning, individual exposure combination, and background subtraction. A particular attention is given to bad pixel and outlier rejection at the image and spectra levels. Most sources are spatially unresolved so that optimal extraction reaches the highest possible signal-to-noise ratio. For all sources, an alternative extraction is also provided that accounts for all of the source flux within the aperture. CASSIS provides publishable quality spectra through an online database together with several important diagnostics, such as the source spatial extent and a quantitative measure of detection level. Ancillary data such as available spectroscopic redshifts are also provided. The database interface will eventually provide various ways to interact with the spectra, such as on-the-fly measurements of spectral features or comparisons among spectra.
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The Infrared Spectrograph (IRS) on board the Spitzer Space Telescope observed about 15,000 objects during the cryogenic mission lifetime. Observations provided low-resolution (R~60-127) spectra over ~5-38um and high-resolution (R~600) spectra over ~10-37um. The Cornell Atlas of Spitzer/IRS Sources (CASSIS) was created to provide publishable quality spectra to the community. Low-resolution spectra have been available in CASSIS since 2011, and we present here the addition of the high-resolution spectra. The high-resolution observations represent approximately one third of all staring observations performed with the IRS instrument. While low-resolution observations are adapted to faint objects and/or broad spectral features (e.g., dust continuum, molecular bands), high-resolution observations allow more accurate measurements of narrow features (e.g., ionic emission lines) as well as a better sampling of the spectral profile of various features. Given the narrow aperture of the two high-resolution modules, cosmic ray hits and spurious features usually plague the spectra. Our pipeline is designed to minimize these effects through various improvements. A super sampled point-spread function was created in order to enable the optimal extraction in addition to the full aperture extraction. The pipeline selects the best extraction method based on the spatial extent of the object. For unresolved sources, the optimal extraction provides a significant improvement in signal-to-noise ratio over a full aperture extraction. We have developed several techniques for optimal extraction, including a differential method that eliminates low-level rogue pixels (even when no dedicated background observation was performed). The updated CASSIS repository now includes all the spectra ever taken by the IRS, with the exception of mapping observations.
We present new advances in the spectral extraction of point-like sources adapted to the Infrared Spectrograph onboard the Spitzer Space Telescope. For the first time, we created a super-sampled point spread function of the low-resolution modules. We describe how to use the point spread function to perform optimal extraction of a single source and of multiple sources within the slit. We also examine the case of the optimal extraction of one or several sources with a complex background. The new algorithms are gathered in a plugin called Adopt which is part of the SMART data analysis software.
ATLAS (Astrophysics Telescope for Large Area Spectroscopy) is a concept for a NASA probe-class space mission. It is the spectroscopic follow-up mission to WFIRST, boosting its scientific return by obtaining deep NIR & MIR slit spectroscopy for most of the galaxies imaged by the WFIRST High Latitude Survey at z>0.5. ATLAS will measure accurate and precise redshifts for ~200M galaxies out to z=7 and beyond, and deliver spectra that enable a wide range of diagnostic studies of the physical properties of galaxies over most of cosmic history. ATLAS and WFIRST together will produce a definitive 3D map of the Universe over 2000 sq deg. ATLAS Science Goals are: (1) Discover how galaxies have evolved in the cosmic web of dark matter from cosmic dawn through the peak era of galaxy assembly. (2) Discover the nature of cosmic acceleration. (3) Probe the Milky Ways dust-enshrouded regions, reaching the far side of our Galaxy. (4) Discover the bulk compositional building blocks of planetesimals formed in the outer Solar System. These flow down to the ATLAS Scientific Objectives: (1A) Trace the relation between galaxies and dark matter with less than 10% shot noise on relevant scales at 1<z<7. (1B) Probe the physics of galaxy evolution at 1<z<7. (2) Obtain definitive measurements of dark energy and tests of General Relativity. (3) Measure the 3D structure and stellar content of the inner Milky Way to a distance of 25 kpc. (4) Detect and quantify the composition of 3,000 planetesimals in the outer Solar System. ATLAS is a 1.5m telescope with a FoV of 0.4 sq deg, and uses Digital Micro-mirror Devices (DMDs) as slit selectors. It has a spectroscopic resolution of R = 1000, and a wavelength range of 1-4 microns. ATLAS has an unprecedented spectroscopic capability based on DMDs, with a spectroscopic multiplex factor ~6,000. ATLAS is designed to fit within the NASA probe-class space mission cost envelope.
We use spitzer-IRAC data to identify near-infrared counterparts to submillimeter galaxies detected with Herschel-SPIRE at 250um in the Herschel Astrophysical Terahertz Large Area Survey (H-ATLAS). Using a likelihood ratio analysis we identify 146 reliable IRAC counterparts to 123 SPIRE sources out of the 159. We find that, compared to the field population, the SPIRE counterparts occupy a distinct region of 3.6 and 4.5um color-magnitude space, and we use this property to identify a further 23 counterparts to 13 SPIRE sources. The IRAC identification rate of 86% is significantly higher than those that have been demonstrated with wide-field ground-based optical and near-IR imaging of Herschel fields. We estimate a false identification rate of 3.6%, corresponding to 4 to 5 sources. Among the 73 counterparts that are undetected in SDSS, 57 have both 3.6 and 4.5um coverage. Of these 43 have [3.6] - [4.5]> 0 indicating that they are likely to be at z > 1.4. Thus, ~ 40% of identified SPIRE galaxies are likely to be high redshift (z > 1.4) sources. We discuss the statistical properties of the IRAC-identified SPIRE galaxy sample including far-IR luminosities, dust temperatures, star-formation rates, and stellar masses. The majority of our detected galaxies have 10^10 to 10^11 L_sun total IR luminosities and are not intense starbursting galaxies as those found at z ~ 2, but they have a factor of 2 to 3 above average specific star-formation rates compared to near-IR selected galaxy samples.
Detection of point sources in images is a fundamental operation in astrophysics, and is crucial for constraining population models of the underlying point sources or characterizing the background emission. Standard techniques fall short in the crowded-field limit, losing sensitivity to faint sources and failing to track their covariance with close neighbors. We construct a Bayesian framework to perform inference of faint or overlapping point sources. The method involves probabilistic cataloging, where samples are taken from the posterior probability distribution of catalogs consistent with an observed photon count map. In order to validate our method we sample random catalogs of the gamma-ray sky in the direction of the North Galactic Pole (NGP) by binning the data in energy and Point Spread Function (PSF) classes. Using three energy bins spanning $0.3 - 1$, $1 - 3$ and $3 - 10$ GeV, we identify $270substack{+30 -10}$ point sources inside a $40^circ times 40^circ$ region around the NGP above our point-source inclusion limit of $3 times 10^{-11}$/cm$^2$/s/sr/GeV at the $1-3$ GeV energy bin. Modeling the flux distribution as a power law, we infer the slope to be $-1.92substack{+0.07 -0.05}$ and estimate the contribution of point sources to the total emission as $18substack{+2 -2}$%. These uncertainties in the flux distribution are fully marginalized over the number as well as the spatial and spectral properties of the unresolved point sources. This marginalization allows a robust test of whether the apparently isotropic emission in an image is due to unresolved point sources or of truly diffuse origin.
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