Morphology of the Galaxy Distribution from Wavelet Denoising

Martínez, V. J.; Starck, Jean-Luc; Saar, E.; Donoho, David L.; Reynolds, Simon; Cruz, Pablo De La; Paredes, Silvestre

doi:10.1086/497125

Cited by 35 publications

(44 citation statements)

References 36 publications

(50 reference statements)

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“…Importantly, Martínez et al (2005) and Saar et al (2007) have generalized the use of Minkowski Functionals by calculating their values in a hierarchy of scales generated from waveletsmoothed volume limited subsamples of the 2dF catalogue. This approach is particularly effective in dealing with non-Gaussian point distributions since the smoothing is not predicated on the use of Gaussian smoothing kernels.…”

Section: Topological Methodsmentioning

confidence: 99%

The multiscale morphology filter: identifying and extracting spatial patterns in the galaxy distribution

Aragón-Calvo¹,

Jones²,

Weygaert³

et al. 2007

A&A

243

288

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Aims. We present here a new method, MMF, for automatically segmenting cosmic structure into its basic components: clusters, filaments, and walls. Importantly, the segmentation is scale independent, so all structures are identified without prejudice as to their size or shape. The method is ideally suited for extracting catalogues of clusters, walls, and filaments from samples of galaxies in redshift surveys or from particles in cosmological N-body simulations: it makes no prior assumptions about the scale or shape of the structures. Methods. Our Multiscale Morphology Filter (MMF) method has been developed on the basis of visualization and feature extraction techniques in computer vision and medical research. The density or intensity field of the sample is smoothed over a range of scales. The smoothed signals are processed through a morphology response filter whose form is dictated by the particular morphological feature it seeks to extract, and depends on the local shape and spatial coherence of the intensity field. The morphology signal at each location is then defined to be the one with the maximum response across the full range of smoothing scales. The success of our method in identifying anisotropic features such as filaments and walls depends critically on the use of an optimally defined intensity field. This is accomplished by applying the DTFE reconstruction methodology to the sample particle or galaxy distribution. Results. We have tested our MMF Filter against a set of heuristic models of weblike patterns such as are seen in the Megaparsec cosmic matter distribution. To test its effectiveness in the context of more realistic configurations we also present preliminary results from the MMF analysis of an N-body model. Comparison with alternative prescriptions for feature extraction shows that MMF is a remarkably strong structure finder

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Section: Topological Methodsmentioning

confidence: 99%

The multiscale morphology filter: identifying and extracting spatial patterns in the galaxy distribution

Aragón-Calvo¹,

Jones²,

Weygaert³

et al. 2007

A&A

243

288

View full text Add to dashboard Cite

show abstract

“…Quite possibly the introduction of more advanced geometry based methods to trace the density field may prove a major advance towards solving this problem. Martínez et al (2005) have generalized the use of Minkowski Functionals by calculating their values in variously smoothed volume limited subsamples of the 2dF catalogue.…”

Section: Topological Methodsmentioning

confidence: 99%

Data Analysis in Cosmology

Martı́nez¹,

Saar²,

Gonzales³

et al. 2009

Lecture Notes in Physics

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“…We perform the calculation for a catalogue described in Martínez et al (2005). It is a volume limited sample extracted from the 2dF Galaxy Redshift Survey, which contains 8487 galaxies and has been cut to obtain a rectangular volume.…”

Section: Test Of Gaussianitymentioning

confidence: 99%

“…On the contrary, for s = 1, 2 h −1 Mpc, there are significant deviations from a gaussian topology. In Martínez et al (2005) the galaxy field is first denoised using a multiscale wavelet decomposition. The idea is to look at the topology of the real continuous field, instead of the discrete galaxy distribution smoothed at different scales.…”

Section: Test Of Gaussianitymentioning

confidence: 99%