Photometric redshifts: estimating their contamination and distribution using clustering information
نویسندگان
چکیده
منابع مشابه
Estimating Photometric Redshifts Using Genetic Algorithms
Photometry is used as a cheap and easy way to estimate redshifts of galaxies, which would otherwise require considerable amounts of expensive telescope time. However, the analysis of photometric redshift datasets is a task where it is sometimes difficult to achieve a high classification accuracy. This work presents a custom Genetic Algorithm (GA) for mining the Hubble Deep Field North (HDF-N) d...
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We present a new approach to obtaining photometric redshifts using a kernel learning technique called Support Vector Machines (SVMs). Unlike traditional spectral energy distribution fitting, this technique requires a large and representative training set. When one is available, however, it is likely to produce results that are comparable to the best obtained using template fitting and artificia...
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We calculate photometric redshifts from the Sloan Digital Sky Survey Data Release 2 Galaxy Sample using artificial neural networks (ANNs). Different input patterns based on various parameters (e.g. magnitude, color index, flux information) are explored and their performances for redshift prediction are compared. For ANN technique, any parameter may be easily incorporated as input, but our resul...
متن کاملPhotometric Redshifts and Photometry Errors
We examine the impact of non-Gaussian photometry errors on photometric redshift performance. We find that they greatly increase the scatter, but this can be mitigated to some extent by incorporating the correct noise model into the photometric redshift estimation process. However, the remaining scatter is still equivalent to that of a much shallower survey with Gaussian photometry errors. We al...
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ژورنال
عنوان ژورنال: Monthly Notices of the Royal Astronomical Society
سال: 2010
ISSN: 0035-8711
DOI: 10.1111/j.1365-2966.2010.17191.x