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

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.

Intra-pixel gain variations and high-precision photometry with the Infrared Array Camera (IRAC)

The Infrared Array Camera (IRAC) on the Spitzer Space Telescope has been used to measure < 10^(-4) temporal variations in point sources (such as transiting extrasolar planets) at 3.6 and 4.5 μm. Due to the under-sampled nature of the PSF, the warm IRAC arrays show variations of as much as 8% in sensitivity as the center of the PSF moves across a pixel due to normal spacecraft pointing wobble and drift. These intra-pixel gain variations are the largest source of correlated noise in IRAC photometry. Usually this effect is removed by fitting a model to the science data themselves (self-calibration), which could result in the removal of astrophysically interesting signals. We describe a new technique for significantly reducing the gain variations and improving photometric precision in a given observation, without using the data to be corrected. This comprises: (1) an adaptive centroiding and repositioning method ("Peak-Up") that uses the Spitzer Pointing Control Reference Sensor (PCRS) to repeatedly position a target to within 0.1 IRAC pixels of an area of minimal gain variation; and (2) the high-precision, high-resolution measurement of the pixel gain structure using non-variable stars. We show that the technique currently allows the reduction of correlated noise by almost an order of magnitude over raw data, which is comparable to the improvement due to self-calibration. We discuss other possible sources of correlated noise, and proposals for reducing their impact on photometric precision

Modifications to the warm Spitzer data reduction pipeline

The Spitzer Space Telescope Infrared Array Camera (IRAC) basic calibrated data reduction pipeline is designed to take a single raw frame from a single IRAC detector and produce a flux-calibrated image that has had all well-understood instrumental signatures removed. We discuss several modifications to the pipeline developed in the last two years in response to the Spitzer warm mission. Due to the different instrument characteristics in the warm mission, we have significantly changed pipeline procedures for masking residual images and mitigating column pulldown. In addition, the muxbleed correction was turned off, because it is not present in the warm data. Parameters relevant to linearity correction, bad pixels, and the photometric calibration have been updated and are continually monitored

Pointing effects and their consequences for Spitzer IRAC exoplanet observations

Spitzer observations of exoplanets routinely yield accuracies of better than one part in 10,000. However, there remain a number of issues that limit the attainable precision, particularly for long duration observations. These include initial pointing inaccuracies, pointing wobble, initial target drift, long-term pointing drifts, and low and high frequency jitter. Coupled with small scale, intrapixel sensitivity variations, all of these pointing issues have the potential to produce significant, correlated photometric noise. We examine each of these issues in turn, discussing their suspected causes and consequences, and describing possible and planned mitigation techniques

Spitzer Space Telescope Mid-IR Light Curves of Neptune

We have used the Spitzer Space Telescope in 2016 February to obtain high cadence, high signal-to-noise, 17 hr duration light curves of Neptune at 3.6 and 4.5 μm. The light curve duration was chosen to correspond to the rotation period of Neptune. Both light curves are slowly varying with time, with full amplitudes of 1.1 mag at 3.6 μm and 0.6 mag at 4.5 μm. We have also extracted sparsely sampled 18 hr light curves of Neptune at W1 (3.4 μm) and W2 (4.6 μm) from the Wide-feld Infrared Survey Explorer (WISE)/NEOWISE archive at six epochs in 2010–2015. These light curves all show similar shapes and amplitudes compared to the Spitzer light curves but with considerable variation from epoch to epoch. These amplitudes are much larger than those observed with Kepler/K2 in the visible (amplitude ~0.02 mag) or at 845 nm with the Hubble Space Telescope (HST) in 2015 and at 763 nm in 2016 (amplitude ~0.2 mag). We interpret the Spitzer and WISE light curves as arising entirely from reflected solar photons, from higher levels in Neptune's atmosphere than for K2. Methane gas is the dominant opacity source in Neptune's atmosphere, and methane absorption bands are present in the HST 763 and 845 nm, WISE W1, and Spitzer 3.6 μm filters