Shears from shapelets
نویسنده
چکیده
Aims. Accurate measurement of gravitational shear from images of distant galaxies is one of the most direct ways of studying the distribution of mass in the universe. We describe an implementation of a technique that is based on the shapelets formalism. Methods. The shapelets technique describes PSF and observed images in terms of Gauss-Hermite expansions (Gaussians times polynomials). It allows the various operations that a galaxy image undergoes before being registered in a camera (gravitational shear, PSF convolution, pixelation) to be modeled in a single formalism, so that intrinsic ellipticities can be derived in a single modeling step. Results. The resulting algorithm, and tests of it on idealized data as well as more realistic simulated images from the STEP project, are described. Results are very promising, with attained calibration accuracy better than a percent, and PSF ellipticity correction better than a factor of 20.
منابع مشابه
Weak gravitational shear and flexion with polar shapelets
We derive expressions, in terms of ‘polar shapelets’, for the image distortion operations associated with weak gravitational lensing. Shear causes galaxy shapes to become elongated, and is sensitive to the second derivative of the projected gravitational potential along their line of sight; flexion bends galaxy shapes into arcs, and is sensitive to the third derivative. Polar shapelets provide ...
متن کاملShapelets: I. A Method for Image Analysis
We present a new method for the analysis of images, a fundamental task in observational astronomy. It is based on the linear decomposition of each object in the image into a series of localised basis functions of different shapes, which we call ‘Shapelets’. A particularly useful set of complete and orthonormal shapelets is that consisting of weighted Hermite polynomials, which correspond to per...
متن کاملUltra-Fast Shapelets for Time Series Classification
Time series shapelets are discriminative subsequences and their similarity to a time series can be used for time series classification. Since the discovery of time series shapelets is costly in terms of time, the applicability on long or multivariate time series is difficult. In this work we propose Ultra-Fast Shapelets that uses a number of random shapelets. It is shown that Ultra-Fast Shapele...
متن کاملUnsupervised Feature Learning from Time Series
In this paper we study the problem of learning discriminative features (segments), often referred to as shapelets [Ye and Keogh, 2009] of time series, from unlabeled time series data. Discovering shapelets for time series classification has been widely studied, where many search-based algorithms are proposed to efficiently scan and select segments from a pool of candidates. However, such types ...
متن کاملAdapting ELM to Time Series Classification: A Novel Diversified Top-k Shapelets Extraction Method
ELM (Extreme Learning Machine) is a single hidden layer feed-forward network, where the weights between input and hidden layer are initialized randomly. ELM is efficient due to its utilization of the analytical approach to compute weights between hidden and output layer. However, ELM still fails to output the semantic classification outcome. To address such limitation, in this paper, we propose...
متن کامل