Diffuse Optical Light in Galaxy Clusters. II. Correlations with Cluster Properties

We have measured the flux, profile, color, and substructure in the diffuse intracluster light (ICL) in a sample of 10 galaxy clusters with a range of mass, morphology, redshift, and density. Deep, wide-field observations for this project were made in two bands at the 1 m Swope and 2.5 m du Pont telescopes at Las Campanas Observatory. Careful attention in reduction and analysis was paid to the illumination correction, background subtraction, point-spread function determination, and galaxy subtraction. ICL flux is detected in both bands in all 10 clusters ranging from 7.6 × 10^(10) to 7.0 × 10^(11) h^(-1)_(70) L_⊙ in r and 1.4 × 10^(10) to 1.2 × 10^(11) h^(-1)_(70) L_⊙ in the B band. These fluxes account for 6%-22% of the total cluster light within one-quarter of the virial radius in r and 4%-21% in the B band. Average ICL B - r colors range from 1.5 to 2.8 mag when k- and evolution corrected to the present epoch. In several clusters we also detect ICL in group environments near the cluster center and up to 1 h^(-1)_(70) Mpc distant from the cluster center. Our sample, having been selected from the Abell sample, is incomplete in that it does not include high-redshift clusters with low density, low flux, or low mass, and it does not include low-redshift clusters with high flux, high mass, or high density. This bias makes it difficult to interpret correlations between ICL flux and cluster properties. Despite this selection bias, we do find that the presence of a cD galaxy corresponds to both centrally concentrated galaxy profiles and centrally concentrated ICL profiles. This is consistent with ICL either forming from galaxy interactions at the center or forming at earlier times in groups and later combining in the center

Spitzer IRAC Low Surface Brightness Observations of the Virgo Cluster

We present 3.6 and 4.5 micron Spitzer IRAC imaging over 0.77 square degrees at the Virgo cluster core for the purpose of understanding the formation mechanisms of the low surface brightness intracluster light features. Instrumental and astrophysical backgrounds that are hundreds of times higher than the signal were carefully characterized and removed. We examine both intracluster light plumes as well as the outer halo of the giant elliptical M87. For two intracluster light plumes, we use optical colors to constrain their ages to be greater than 3 & 5 Gyr, respectively. Upper limits on the IRAC fluxes constrain the upper limits to the masses, and optical detections constrain the lower limits to the masses. In this first measurement of mass of intracluster light plumes we find masses in the range of 5.5 x 10^8 - 4.5 x 10^9 and 2.1 x 10^8 - 1.5 x 10^9 solar masses for the two plumes for which we have coverage. Given their expected short lifetimes, and a constant production rate for these types of streams, integrated over Virgo's lifetime, they can account for the total ICL content of the cluster implying that we do not need to invoke ICL formation mechanisms other than gravitational mechanisms leading to bright plumes. We also examined the outer halo of the giant elliptical M87. The color profile from the inner to outer halo of M87 (160 Kpc) is consistent with either a flat or optically blue gradient, where a blue gradient could be due to younger or lower metallicity stars at larger radii. The similarity of the age predicted by both the infrared and optical colors (> few Gyr) indicates that the optical measurements are not strongly affected by dust extinction.Comment: 16 pages including appendix, 9 figures, ApJ accepte

The Infrared Array Camera Dark Field: Far-Infrared to X-ray Data

We present 20 band photometry from the far-IR to X-ray in the Spitzer Infrared Array Camera (IRAC) dark field. The bias for the near-IR camera on Spitzer is calibrated by observing a ~20' diameter "dark" field near the north ecliptic pole roughly every two-to-three weeks throughout the mission duration of Spitzer. The field is unique for its extreme depth, low background, high quality imaging, time-series information, and accompanying photometry including data taken with Akari, Palomar, MMT, KPNO, Hubble, and Chandra. This serendipitous survey contains the deepest mid-IR data taken to date. This data set is well suited for studies of intermediate-redshift galaxy clusters, high-redshift galaxies, the first generation of stars, and the lowest mass brown dwarfs, among others. This paper provides a summary of the data characteristics and catalog generation from all bands collected to date as well as a discussion of photometric redshifts and initial and expected science results and goals. To illustrate the scientific potential of this unique data set, we also present here IRAC color-color diagrams

The IRAC Dark Field; Far- Infrared to X-ray Data

We present 20 band photometry from the far-IR to X-ray in the Spitzer IRAC dark field. The bias for the near-IR camera on Spitzer is calibrated by observing a ~20 arcminute diameter "dark" field near the north ecliptic pole roughly every two-to-three weeks throughout the mission duration of Spitzer. The field is unique for its extreme depth, low background, high quality imaging, time-series information, and accompanying photometry including data taken with Akari, Palomar, MMT, KPNO, Hubble, and Chandra. This serendipitous survey contains the deepest mid-IR data taken to date. This dataset is well suited for studies of intermediate redshift galaxy clusters, high redshift galaxies, the first generation of stars, and the lowest mass brown dwarfs, among others. This paper provides a summary of the data characteristics and catalog generation from all bands collected to date as well as a discussion of photometric redshifts and initial and expected science results and goals. To illustrate the scientific potential of this unique dataset, we also present here IRAC color color diagrams.Comment: 12 pages, ApJS accepte

Transiting Exoplanet Studies and Community Targets for JWST's Early Release Science Program

The James Webb Space Telescope (JWST) will likely revolutionize transiting exoplanet atmospheric science, due to a combination of its capability for continuous, long duration observations and its larger collecting area, spectral coverage, and spectral resolution compared to existing space-based facilities. However, it is unclear precisely how well JWST will perform and which of its myriad instruments and observing modes will be best suited for transiting exoplanet studies. In this article, we describe a prefatory JWST Early Release Science (ERS) Cycle 1 program that focuses on testing specific observing modes to quickly give the community the data and experience it needs to plan more efficient and successful transiting exoplanet characterization programs in later cycles. We propose a multi-pronged approach wherein one aspect of the program focuses on observing transits of a single target with all of the recommended observing modes to identify and understand potential systematics, compare transmission spectra at overlapping and neighboring wavelength regions, confirm throughputs, and determine overall performances. In our search for transiting exoplanets that are well suited to achieving these goals, we identify 12 objects (dubbed "community targets") that meet our defined criteria. Currently, the most favorable target is WASP-62b because of its large predicted signal size, relatively bright host star, and location in JWST's continuous viewing zone. Since most of the community targets do not have well-characterized atmospheres, we recommend initiating preparatory observing programs to determine the presence of obscuring clouds/hazes within their atmospheres. Measurable spectroscopic features are needed to establish the optimal resolution and wavelength regions for exoplanet characterization. Other initiatives from our proposed ERS program include testing the instrument brightness limits and performing phase-curve observations. The latter are a unique challenge compared to transit observations because of their significantly longer durations. Using only a single mode, we propose to observe a full-orbit phase curve of one of the previously characterized, short-orbital-period planets to evaluate the facility-level aspects of long, uninterrupted time-series observations

Galaxy Clusters in the IRAC Dark Field II: Mid-IR Sources

We present infrared luminosities, star formation rates, colors, morphologies, locations, and AGN properties of 24 micron-detected sources in photometrically detected high-redshift clusters in order to understand the impact of environment on star formation and AGN evolution in cluster galaxies. We use three newly-identified z=1 clusters selected from the IRAC dark field; the deepest ever mid-IR survey with accompanying, 14 band multiwavelength data including deep HST imaging and deep wide-area Spitzer MIPS 24 micron imaging. We find 90 cluster members with MIPS detections within two virial radii of the cluster centers, of which 17 appear to have spectral energy distributions dominated by AGN and the rest dominated by star formation. We find that 43 of the star forming are luminous infrared galaxies (LIRGs). The majority of sources (81%) are spirals or irregulars. A large fraction (at least 25%) show obvious signs of interactions. The MIPS -detected member galaxies have varied spatial distributions as compared to the MIPS-undetected members with one of the three clusters showing SF galaxies being preferentially located on the cluster outskirts, while the other 2 clusters show no such trend. Both the AGN fraction and the summed SFR of cluster galaxies increases from z=0 to 1, at a rate that is a few times faster in clusters than over the same redshift range in the field. Cluster environment does have an effect on the evolution of both AGN fraction and SFR from redshift one to the present, but does not effect the infrared luminosities or morphologies of the MIPS sample. Star formation happens in the same way regardless of environment making MIPS sources look the same in the cluster and field, however the cluster environment does encourage a more rapid evolution with time as compared to the field.Comment: 18 pages, 9 figures, ApJ accepte

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

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.

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