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Related papers: Estimating the distribution of Galaxy Morphologies…

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The small-scale environment characterized by the local density is known to play a crucial role in deciding the galaxy properties but the role of large-scale environment on galaxy formation and evolution still remain a less clear issue. We…

Cosmology and Nongalactic Astrophysics · Physics 2016-12-30 Biswajit Pandey , Suman Sarkar

We explore the mass distribution of material associated with galaxies from the observation of gravitational weak lensing for the galaxy mass correlation function with the aid of $N$-body simulations of dark matter. The latter is employed to…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-28 Shogo Masaki , Masataka Fukugita , Naoki Yoshida

We investigate how galaxies in VIPERS (the VIMOS Public Extragalactic Redshift Survey) inhabit the cosmological density field by examining the correlations across the observable parameter space of galaxy properties and clustering strength.…

We estimate the distribution of intrinsic shapes of the APM galaxy clusters from their corresponding distribution of projected shapes. We smooth the discrete galaxy distribution and define the cluster shape by fitting the best ellipse to…

Astrophysics · Physics 2007-05-23 Spyros Basilakos , Manolis Plionis , Steve Maddox

Large-scale astrophysical systems are non-extensive due to their long-range force of gravity. Here we show an approach toward the statistical mechanics of such self-gravitating systems (SGS). This is a generalization of the standard…

Astrophysics · Physics 2007-05-23 Akika Nakamichi , Izumi Joichi , Osamu Iguchi , Masahiro Morikawa

This conference shows the impressive rate of advances in the observations and theoretical interpretations of large-scale structure. But to explain my feeling that we may still have a lot to learn I offer some comments on our sociology,…

Astrophysics · Physics 2007-05-23 P. J. E. Peebles

Non-trivial spatial topology of the Universe may give rise to potentially measurable signatures in the cosmic microwave background. We explore different machine learning approaches to classify harmonic-space realizations of the microwave…

It is now practically the norm for data to be very high dimensional in areas such as genetics, machine vision, image analysis and many others. When analyzing such data, parametric models are often too inflexible while nonparametric…

Methodology · Statistics 2011-05-31 Abhishek Bhattacharya , Garritt Page , David Dunson

The log-normal distribution represents the probability of finding randomly distributed particles in a micro canonical ensemble with high entropy. To a first approximation, a modified form of this distribution with a truncated termination…

Astrophysics of Galaxies · Physics 2015-03-12 John H. Marr

In some scientific fields, a scaling is able to modify the topology of an observed object. Our goal in the present work is to introduce a new formalism adapted to the mathematical representation of this kind of phenomenon. To this end, we…

Geometric Topology · Mathematics 2008-12-11 Guy Wallet

We train three convolutional neural networks (CNNs) to classify galaxies with Galaxy Zoo 2 dataset and extract the activations from the last fully connected layer or the last average pooling layer of CNNs to study the high-dimensional…

Astrophysics of Galaxies · Physics 2018-07-17 Jia-Ming Dai , Jizhou Tong

Sparse coding is a proven principle for learning compact representations of images. However, sparse coding by itself often leads to very redundant dictionaries. With images, this often takes the form of similar edge detectors which are…

Computer Vision and Pattern Recognition · Computer Science 2015-03-19 James Bergstra , Aaron Courville , Yoshua Bengio

Understanding how galaxies trace the underlying matter density field is essential for characterizing the influence of the large-scale structure on galaxy formation, being therefore a key ingredient in observational cosmology. This…

An analysis of high-dimensional data can offer a detailed description of a system but is often challenged by the curse of dimensionality. General dimensionality reduction techniques can alleviate such difficulty by extracting a few…

Methodology · Statistics 2021-09-28 Di Bo , Hoon Hwangbo , Vinit Sharma , Corey Arndt , Stephanie C. TerMaath

Global Stellar Formation Rates or SFRs are crucial to constrain theories of galaxy formation and evolution. SFR's are usually estimated via spectroscopic observations which require too much previous telescope time and therefore cannot match…

Instrumentation and Methods for Astrophysics · Physics 2019-01-24 Michele Delli Veneri , Stefano Cavuoti , Massimo Brescia , Giuseppe Riccio , Giuseppe Longo

To understand the universe and to interpret the cosmological parameters governing its evolution it is necessary to contrast the data from galaxy surveys with simulation. Typically it entails using computationally expensive N -body…

Cosmology and Nongalactic Astrophysics · Physics 2019-05-02 Tolga Yapici , Zachery Brown , Regina Demina , Segev BenZvi

I present various simulations of an on-going large sub-mm survey, SHADES, showing how constraints can be put on galaxy formation models and cosmology from this survey.

Astrophysics · Physics 2017-03-29 Eelco van Kampen

Galaxies are arranged in interconnected walls and filaments forming a cosmic web encompassing huge, nearly empty, regions between the structures. Many statistical methods have been proposed in the past in order to describe the galaxy…

Astrophysics · Physics 2016-02-17 J-L. Starck , V. J. Martinez , D. L. Donoho , O. Levi , P. Querre , E. Saar

I review the general progress made in the study of galaxy evolution concentrating on the impact of systematic ground-based spectroscopic surveys of faint galaxies and high resolution imaging with Hubble Space Telescope. The picture emerging…

Astrophysics · Physics 2009-10-28 R. S. Ellis

Sparse coding aims to model data vectors as sparse linear combinations of basis elements, but a majority of related studies are restricted to continuous data without spatial or temporal structure. A new model-based sparse coding (MSC)…

Methodology · Statistics 2021-08-24 Xin Xing , Rui Xie , Wenxuan Zhong
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