Improving the photometric precision of IRAC Channel 1

Planning is underway for a possible post-cryogenic mission with the Spitzer Space Telescope. Only Channels 1 and 2 (3.6 and 4.5 μm) of the Infrared Array Camera (IRAC) will be operational; they will have unmatched sensitivity from 3 to 5 microns until the James Webb Space Telescope is launched. At SPIE Orlando, Mighell described his NASA-funded MATPHOT algorithm for precision stellar photometry and astrometry and presented MATPHOT-based simulations that suggested Channel 1 stellar photometry may be significantly improved by modeling the nonuniform RQE within each pixel, which, when not taken into account in aperture photometry, causes the derived flux to vary according to where the centroid falls within a single pixel (the pixel-phase effect). We analyze archival observations of calibration stars and compare the precision of stellar aperture photometry, with the recommended 1-dimensional and a new 2-dimensional pixel-phase aperture-flux correction, and MATPHOT-based PSF-fitting photometry which accounts for the observed loss of stellar flux due to the nonuniform intrapixel quantum efficiency. We show how the precision of aperture photometry of bright isolated stars corrected with the new 2-dimensional aperture-flux correction function can yield photometry that is almost as precise as that produced by PSF-fitting procedures. This timely research effort is intended to enhance the science return not only of observations already in Spitzer data archive but also those that would be made during the Spitzer Warm Mission

Airborne 20-65 micron spectrophotometry of Comet Halley

Observations of Comet Halley with a grating spectrometer on board the Kuiper Airborne Observatory on four nights in Dec. 1985 to Apr. 1986 are reported. Low resolution 20 to 65 micrometer spectra of the nucleus with a 40 arcsec FWHM beam was obtained on 17 Dec. 1985, and on 15 and 17 Apr. 1986. On 20 Dec. 1985, only a 20 to 35 micrometer spectrum was obtained. Most of the data have been discussed in a paper where the continuum was dealt with. In that paper, models were fit to the continuum that showed that more micron sized particles of grain similar to amorphous carbon were needed to fit the spectrum than were allowed by the Vega SP-2 mass distribution, or that a fraction of the grains had to be made out of a material whose absorption efficiency fell steeper than lambda sup -1 for lambda greater than 20 micrometers. Spectra was also presented taken at several points on the coma on 15 Apr. which showed that the overall shape to the spectrum is the same in the coma. Tabulated values of the data and calibration curves are available. The spectral features are discussed

Improving the photometric precision of IRAC Channel 1

Planning is underway for a possible post-cryogenic mission with the Spitzer Space Telescope. Only Channels 1 and 2 (3.6 and 4.5 μm) of the Infrared Array Camera (IRAC) will be operational; they will have unmatched sensitivity from 3 to 5 microns until the James Webb Space Telescope is launched. At SPIE Orlando, Mighell described his NASA-funded MATPHOT algorithm for precision stellar photometry and astrometry and presented MATPHOT-based simulations that suggested Channel 1 stellar photometry may be significantly improved by modeling the nonuniform RQE within each pixel, which, when not taken into account in aperture photometry, causes the derived flux to vary according to where the centroid falls within a single pixel (the pixel-phase effect). We analyze archival observations of calibration stars and compare the precision of stellar aperture photometry, with the recommended 1-dimensional and a new 2-dimensional pixel-phase aperture-flux correction, and MATPHOT-based PSF-fitting photometry which accounts for the observed loss of stellar flux due to the nonuniform intrapixel quantum efficiency. We show how the precision of aperture photometry of bright isolated stars corrected with the new 2-dimensional aperture-flux correction function can yield photometry that is almost as precise as that produced by PSF-fitting procedures. This timely research effort is intended to enhance the science return not only of observations already in Spitzer data archive but also those that would be made during the Spitzer Warm Mission

Photometry using the Infrared Array Camera on the Spitzer Space Telescope

We present several corrections for point source photometry to be applied to data from the Infrared Array Camera (IRAC) on the Spitzer Space Telescope. These corrections are necessary because of characteristics of the IRAC arrays and optics and the way the instrument is calibrated in-flight. When these corrections are applied, it is possible to achieve a ~2% relative photometric accuracy for sources of adequate signal to noise in an IRAC image.Comment: 16 pages, 13 figures. Accepted for publication in the Publications of the Astronomical Society of the Pacifi

A Spitzer IRAC Measure of the Zodiacal Light

The dominant non-instrumental background source for space–based infrared observatories is the zodiacal light (ZL). We present Spitzer Infrared Array Camera (IRAC) measurements of the ZL at 3.6, 4.5, 5.8, and 8.0 μm, taken as part of the instrument calibrations. We measure the changing surface brightness levels in approximately weekly IRAC observations near the north ecliptic pole over the period of roughly 8.5 years. This long time baseline is crucial for measuring the annual sinusoidal variation in the signal levels due to the tilt of the dust disk with respect to the ecliptic, which is the true signal of the ZL. This is compared to both Cosmic Background Explorer Diffuse Infrared Background Experiment data and a ZL model based thereon. Our data show a few percent discrepancy from the Kelsall et al.(1998) model including a potential warping of the interplanetary dust disk and a previously detected overdensity in the dust cloud directly behind the Earth in its orbit. Accurate knowledge of the ZL is important for both extragalactic and Galactic astronomy including measurements of the cosmic infrared background, absolute measures of extended sources, and comparison to extrasolar interplanetary dust models. IRAC data can be used to further inform and test future ZL models

Spitzer Infrared Array Camera (IRAC) Pipeline: final modifications and lessons learned

In more than ten years of operations, the Spitzer Space Telescope has conducted a wide range of investigations from observing nearby asteroids to probing atmospheric properties of exoplanets to measuring masses of the most distance galaxies. Observations using the Infrared Array Camera (IRAC) at 3.6 and 4.5um will continue through mid-2019 when the James Webb Space Telescope will succeed Spitzer. In anticipation of the eventual end of the mission, the basic calibrated data reduction pipeline designed to produce flux-calibrated images has been finalized and used to reprocess all the data taken during the Spitzer warm mission. We discuss all final modifications made to the pipeline

Comparison of laboratory and in-flight performance of infared array camera (IRAC) detector arrays on Spitzer Space Telescope

The Infrared Array Camera (IRAC) on Spitzer Space Telescope includes four Raytheon Vision Systems focal plane arrays, two with InSb detectors, and two with Si:As detectors. A brief comparison of pre- flight laboratory results vs. in-flight performance is given, including quantum efficiency and noise, as well as a discussion of irregular effects, such as residual image performance, "first frame effect", "banding", "column pull-down" and multiplexer bleed. Anomalies not encountered in pre-flight testing, as well as post-flight laboratory tests on these anomalies at the University of Rochester and at NASA Ames using sister parts to the flight arrays, are emphasized

Calibration trending in the Spitzer beyond era

The Spitzer Space Telescope currently operates in the "Beyond Era", over nine years past an original cryogenic mission. As the astronomy community continues to advance scientific boundaries and push beyond original specifications, the stability of the Infrared Array Camera (IRAC) instrument is paramount. The Instrument Team (IST) monitors the pointing accuracy, temperature, and calibration and provides the information in a timely manner to observers. The IRAC IST created a calibration trending web page, available to the general astronomy community, where the team posts updates of three most pertinent scientific stability measures of the IRAC data: calibration, bias, and bad pixels. In addition, photometry and telescope properties from all the staring observations (>1500 as of April 2018) are trended to examine correlations with changes in the age or thermal properties of the telescope. A long, well-sampled baseline established by consistent monitoring outside anomalies and space weather events allows even the smallest changes to be detected

Spitzer/IRAC precision photometry: a machine learning approach

The largest source of noise in exoplanet and brown dwarf photometric time series made with Spitzer/IRAC is the coupling between intra-pixel gain variations and spacecraft pointing fluctuations. Observers typically correct for this systematic in science data by deriving an instrumental noise model simultaneously with the astrophysical light curve and removing the noise model. Such techniques for self-calibrating Spitzer photometric datasets have been extremely successful, and in many cases enabled near-photon-limited precision on exoplanet transit and eclipse depths. Self-calibration, however, can suffer from certain limitations: (1) temporal astrophysical signals can become aliased as part of the instrument model; (2) for some techniques adequate model estimation often requires a high degree of intra-pixel positional redundancy (multiple samples with nearby centroids) over long time spans; (3) many techniques do not account for sporadic high frequency telescope vibrations that smear out the point spread function. We have begun to build independent general-purpose intra-pixel systematics removal algorithms using three machine learning techniques: K-Nearest Neighbors (with kernel regression), Random Decision Forests, and Artificial Neural Networks. These methods remove many of the limitations of self-calibration: (1) they operate on a dedicated calibration database of approximately one million measurements per IRAC waveband (3.6 and 4.5 microns) of non-variable stars, and thus are independent of the time series science data to be corrected; (2) the database covers a large area of the "Sweet Spot, so the methods do not require positional redundancy in the science data; (3) machine learning techniques in general allow for flexibility in training with multiple, sometimes unorthodox, variables, including those that trace PSF smear. We focus in this report on the K-Nearest Neighbors with Kernel Regression technique. (Additional communications are in preparation describing Decision Forests and Neural Networks.