dorsal/arxiv
View SchemaReduction of time-resolved space-based CCD photometry developed for MOST Fabry Imaging data
| Authors | P. Reegen, T. Kallinger, D. Frast, M. Gruberbauer, D. Huber, J. M. Matthews, D. Punz, S. Schraml, W. W. Weiss, R. Kuschnig, A. F. J. Moffat, G. A. H. Walker, D. B. Guenther, S. M. Rucinski, D. Sasselov |
|---|---|
| Categories | |
| ArXiv ID | physics/0703153 |
| URL | https://arxiv.org/abs/physics/0703153 |
| DOI | 10.1111/j.1365-2966.2006.10082.x |
| Journal | 2006MNRAS.367.1417R |
Abstract
The MOST (Microvariability & Oscillations of STars) satellite obtains ultraprecise photometry from space with high sampling rates and duty cycles. Astronomical photometry or imaging missions in low Earth orbits, like MOST, are especially sensitive to scattered light from Earthshine, and all these missions have a common need to extract target information from voluminous data cubes. They consist of upwards of hundreds of thousands of two-dimensional CCD frames (or sub-rasters) containing from hundreds to millions of pixels each, where the target information, superposed on background and instrumental effects, is contained only in a subset of pixels (Fabry Images, defocussed images, mini-spectra). We describe a novel reduction technique for such data cubes: resolving linear correlations of target and background pixel intensities. This stepwise multiple linear regression removes only those target variations which are also detected in the background. The advantage of regression analysis versus background subtraction is the appropriate scaling, taking into account that the amount of contamination may differ from pixel to pixel. The multivariate solution for all pairs of target/background pixels is minimally invasive of the raw photometry while being very effective in reducing contamination due to, e.g., stray light. The technique is tested and demonstrated with both simulated oscillation signals and real MOST photometry.
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"abstract": "The MOST (Microvariability \u0026 Oscillations of STars) satellite obtains\nultraprecise photometry from space with high sampling rates and duty cycles.\nAstronomical photometry or imaging missions in low Earth orbits, like MOST, are\nespecially sensitive to scattered light from Earthshine, and all these missions\nhave a common need to extract target information from voluminous data cubes.\nThey consist of upwards of hundreds of thousands of two-dimensional CCD frames\n(or sub-rasters) containing from hundreds to millions of pixels each, where the\ntarget information, superposed on background and instrumental effects, is\ncontained only in a subset of pixels (Fabry Images, defocussed images,\nmini-spectra). We describe a novel reduction technique for such data cubes:\nresolving linear correlations of target and background pixel intensities. This\nstepwise multiple linear regression removes only those target variations which\nare also detected in the background. The advantage of regression analysis\nversus background subtraction is the appropriate scaling, taking into account\nthat the amount of contamination may differ from pixel to pixel. The\nmultivariate solution for all pairs of target/background pixels is minimally\ninvasive of the raw photometry while being very effective in reducing\ncontamination due to, e.g., stray light. The technique is tested and\ndemonstrated with both simulated oscillation signals and real MOST photometry.",
"arxiv_id": "physics/0703153",
"authors": [
"P. Reegen",
"T. Kallinger",
"D. Frast",
"M. Gruberbauer",
"D. Huber",
"J. M. Matthews",
"D. Punz",
"S. Schraml",
"W. W. Weiss",
"R. Kuschnig",
"A. F. J. Moffat",
"G. A. H. Walker",
"D. B. Guenther",
"S. M. Rucinski",
"D. Sasselov"
],
"categories": [
"physics.data-an"
],
"doi": "10.1111/j.1365-2966.2006.10082.x",
"journal_ref": "2006MNRAS.367.1417R",
"title": "Reduction of time-resolved space-based CCD photometry developed for MOST Fabry Imaging data",
"url": "https://arxiv.org/abs/physics/0703153"
},
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