2009
DOI: 10.1088/0067-0049/186/1/10
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COSMIC INFRARED BACKGROUND FLUCTUATIONS IN DEEP SPITZER INFRARED ARRAY CAMERA IMAGES: DATA PROCESSING AND ANALYSIS

Abstract: This paper provides a detailed description of the data reduction and analysis procedures that have been employed in our previous studies of spatial fluctuation of the cosmic infrared background (CIB) using deep Spitzer Infrared Array Camera observations. The self-calibration we apply removes a strong instrumental signal from the fluctuations that would otherwise corrupt the results. The procedures and results for masking bright sources and modeling faint sources down to levels set by the instrumental noise are… Show more

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Cited by 32 publications
(68 citation statements)
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“…Thus, absolute flux measurements of the FIR-EBL constitutes a very challenging task. Although the low contribution to the net flux might prevent such absolute measurements of primordial dust emission, it might still be possible to obtain information about it by exploring the EBL angular power spectrum Kashlinsky & Odenwald 2000;Arendt et al 2010;Mitchell-Wynne et al 2015), which we will investigate in a separate paper. According to our model, these signatures should be detected at ∼ 500µm, close to the peak of dust emission from primeval sources.…”
Section: Discussionmentioning
confidence: 99%
“…Thus, absolute flux measurements of the FIR-EBL constitutes a very challenging task. Although the low contribution to the net flux might prevent such absolute measurements of primordial dust emission, it might still be possible to obtain information about it by exploring the EBL angular power spectrum Kashlinsky & Odenwald 2000;Arendt et al 2010;Mitchell-Wynne et al 2015), which we will investigate in a separate paper. According to our model, these signatures should be detected at ∼ 500µm, close to the peak of dust emission from primeval sources.…”
Section: Discussionmentioning
confidence: 99%
“…The procedure for map assembly is described in our previous papers (Kashlinsky et al , 2007a with an extensive summary, including all the tests, given in Arendt et al (2010). Our IRAC mosaics are prepared from the basic calibrated data (BCD) product using the least-squares self-calibration procedure described by Fixsen et al (2000).…”
Section: Irac-based Mapsmentioning
confidence: 99%
“…Mean-square fluctuations, F 2 (θ) ≈ q 2 P2/(2π), is then calculated, where θ is 2π/q converted into arcsec. Mean-square fluctuations are divided by the fraction of unsubtracted pixels in the image to compensate for area lost by masking (Arendt et al 2010). Unless otherwise noted, error bars shown in figures represent one standard deviation of the Poisson errors, P2/ Nq, where Nq is the number of Fourier elements in the associated bin.…”
Section: Fluctuation Analysismentioning
confidence: 99%
“…The masking process itself can cause a distortion of fluctuation spectra that must be considered when making comparisons (Arendt et al 2010;Kashlinsky et al 2012). Images are masked by multiplying the image field by a separate mask with pixel values of one everywhere except for sourcesubtracted regions that have pixel values of zero or, as shown in Fig.…”
Section: Generation Of Control Imagesmentioning
confidence: 99%