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SDSS Classifier The star-galaxy separator implemented in SDSS image processing pipeline photo (Lupton et al. 2001 (Lupton et al. , 2002 is equal to the difference between the point-spreadfunction magnitude ... As re-ported in Lupton et al. (2001) , "We initially hoped to use the relative likelihoods of the PSF and galaxy fits to separate stars from galaxies, but found that the stellar likelihoods were tiny ...arXiv:1912.08210v1 fatcat:owsowgg2ezdwbpz6ktnwlydlqa
Two of special interest to DESC: • Science Pipelines Definition Workgroup (scipi-wg) -Co-Chairs: Zeljko Ivezic & Robert Lupton -Refine and improve the high-level architecture of the DM Science Pipelines ... − Rework of ProcessCcdTask More from Robert in just a minute! IMPORTANT: All of these are currently on master, and will appear in the the next release (~3 months). ...doi:10.5281/zenodo.47280 fatcat:3k3b67egm5dmzdylpxj4svhzlq
better than 0.1 arcsec per coordinate (rms) for sources with r < 20.5 m (Pier et al. 2003) , and the morphological information from the images allows reliable star-galaxy separation to r ∼ 21.5 m (Lupton ...arXiv:astro-ph/0310565v1 fatcat:ydr6gjgiajhg7a5mea5aqd4yiq
Herein, we describe a method for decorrelating image differences produced by the Alard & Lupton (1998) method of PSF matching. ... In the LSST stack (and most other existing transient detection pipelines), optimal image subtraction is enabled through point spread function (PSF) matching via the method of Alard & Lupton (1998) (hereafter ...doi:10.5281/zenodo.192833 fatcat:xdmvh7s7fndufbaehkimmsqmdu
Some of these models for M13 and M92 are given in the talk by Lupton and Gunn at this conference. For M13, both anisotropy and rotation play an important role. ...doi:10.1017/s0074180900147540 fatcat:ccx4dz5wevcgpdblqlshkfazxq
Chadwick, Robert W. embley, edward t. Baker, Joseph a. Resing, John e. Lupton, Katharine V. Cashman, Robert P. Dziak, Verena tunnicliffe, David a. ... Robert P. Dziak is Senior Research Professor, Oregon State University/NOAA, Hatfield Marine Science Center, Newport, OR, USA. ...doi:10.5670/oceanog.2010.82 fatcat:64rocjv6yvgnzjvjpm7d3am6yy
This study builds on prior work on the effect of demographic variables on undergraduate attitudes towards business ethics and examines differences between US and Japanese students sampled in 2011. The samples comprised 89 US and 147 Japanese undergraduate students (n-236). Respondents completed the Attitude Towards Business Ethics (ATBEQ) questionnaire and demographic questions. Data were analyzed with SPSS ANOVA, post-hoc t-tests and with non-parametric tests. Significant Japanese and USdoi:10.5296/jse.v3i4.4179 fatcat:opf5jeu6evfmjbik46fh2p3gme
more »... t samples differed significantly (p < 0.05) on at least fifty percent of ATBEQ statements. The Japanese students expressed significantly stronger agreement with seven Machiavellian and three Social Darwinism statements whereas the US students expressed significantly stronger agreement with only two Machiavellian and one Social Darwinism statements.
better than 0.1 arcsec per coordinate (rms) for sources with r < 20.5 m (Pier et al. 2003) , and the morphological information from the images allows reliable star-galaxy separation to r ∼ 21.5 m (Lupton ...doi:10.1086/427392 fatcat:a3ubgqjuinhfbc4vlqgseo62qi
Interesting Algorithms The SDSS imaging piplelines employ a number of novel and even interesting algorithms, which are slowly being written up for publication; for example the image deblender (Lupton ...arXiv:astro-ph/0101420v2 fatcat:c3tj62uxm5a55gfytumuafypbm
Carter Lupton Robert R. ...doi:10.1525/aa.1984.86.1.02a00790 fatcat:ktxlugjanfahfa2b4ebutm5pui
We construct a galaxy catalog to r * = 21.5 using star-galaxy classification by the SDSS photometric pipeline (photo; Lupton et al. 2001 ). ... The orientation and ellipticities of individual BCGs are taken from the outputs of photo: the position angle φ deV and axis ratio α deV are the parameters of the best fit 2-D de Vaucouleurs law model (Lupton ...arXiv:astro-ph/0110383v1 fatcat:aj2f4fiyfjfzvbpqmbyw736jt4
Cross-match spatially clusters and organizes several astronomical point-source measurements from one or more surveys. Ideally, each object would be found in each survey. Unfortunately, the observation conditions and the objects themselves change continually. Even some stationary objects are missing in some observations; sometimes objects have a variable light flux and sometimes the seeing is worse. In most cases we are faced with a substantial number of differences in object detections betweenarXiv:cs/0701172v1 fatcat:kni3imhmlfaezh7rpo4gruswgm
more »... urveys and between observations taken at different times within the same survey or instrument. Dealing with such missing observations is a difficult problem. The first step is to classify misses as ephemeral - when the object moved or simply disappeared, masked - when noise hid or corrupted the object observation, or edge - when the object was near the edge of the observational field. This classification and a spatial library to represent and manipulate observational footprints help construct a Match table recording both hits and misses. Transitive closure clusters friends-of-friends into object bundles. The bundle summary statistics are recorded in a Bundle table. This design is an evolution of the Sloan Digital Sky Survey cross-match design that compared overlapping observations taken at different times. Cross-Matching Multiple Spatial Observations and Dealing with Missing Data.
We present a new method designed for optimal subtraction of two images with different seeing. Using image subtraction appears to be essential for the full analysis of the microlensing survey images, however a perfect subtraction of two images is not easy as it requires the derivation of an extremely accurate convolution kernel. Some empirical attempts to find the kernel have used the Fourier transform of bright stars, but solving the statistical problem of finding the best kernel solution hasdoi:10.1086/305984 fatcat:2woameyr4veojc2frgqfbjyaee
more »... ver really been tackled. We demonstrate that it is possible to derive an optimal kernel solution from a simple least square analysis using all the pixels of both images, and also show that it is possible to fit the differential background variation at the same time. We also show that PSF variations can also be easily handled by the method. To demonstrate the practical efficiency of the method, we analyzed some images from a Galactic Bulge field monitored by the OGLE II project. We find that the residuals in the subtracted images are very close to the photon noise expectations. We also present some light curves of variable stars, and show that, despite high crowding levels, we get an error distribution close to that expected from photon noise alone. We thus demonstrate that nearly optimal differential photometry can be achieved even in very crowded fields. We suggest that this algorithm might be particularly important for microlensing surveys, where the photometric accuracy and completeness levels could be very significantly improved by using this method.
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