Related papers: Objective Classification of Galaxy Spectra using t…
Recently, machine learning methods presented a viable solution for automated classification of image-based data in various research fields and business applications. Scientists require a fast and reliable solution to be able to handle the…
We present a catalogue of 16551 edge-on galaxies created using the public DR2 data of the Pan-STARRS survey. The catalogue covers the three quarters of the sky above Dec.=-30 degrees. The galaxies were selected using a convolutional neural…
We describe application of the `shapelet' linear decomposition of galaxy images to morphological classification using images of $\sim$ 3000 galaxies from the Sloan Digital Sky Survey. After decomposing the galaxies we perform a principal…
The combination of huge databases of galaxy spectra and advances in evolutionary synthesis models in the past few years has renewed interest in an old question: How to estimate the star formation history of a galaxy out of its integrated…
We analyze a portion of the SDSS photometric catalog, consisting of approximately 10,000 objects that have been spectroscopically classified into stars, galaxies, QSOs, late-type stars and unknown objects (spectroscopically unclassified…
In this paper, we employe a new statistical analysis technique, Ensemble Learning for Independent Component Analysis (EL-ICA), on the synthetic galaxy spectra from a newly released high resolution evolutionary model by Bruzual & Charlot. We…
This work identifies the orientation of galaxies in the Galaxy zoo data set. The images are first identified by the number of principal components required to represent 99 percent of the variance of the image. K means clustering is used to…
The construction of a catalogue of galaxy groups from the 2-degree Field Galaxy Redshift Survey (2dFGRS) is described. Groups are identified by means of a friends-of-friends percolation algorithm which has been thoroughly tested on mock…
We extend a recently developed galaxy morphology classification method, Quantitative Multiwavelength Morphology (QMM), to connect galaxy morphologies to their underlying physical properties. The traditional classification of galaxies…
In this work we introduce a new method to perform the identification of groups of galaxies and present results of the identification of galaxy groups in the Seventh Data Release of the Sloan Digital Sky Survey (SDSS-DR7). Our methodology…
We present a proof of concept of a new galaxy group finder method, Markov graph Clustering (MCL; Van Dongen 2000) that naturally handles probabilistic linking criteria. We introduce a new figure of merit, the variation of information…
The mid-infrared emission from 18 nearby galaxies imaged with the IRAC instrument on Spitzer Space Telescope samples the spatial distributions of the reddening-free stellar photospheric emission and the warm dust in the ISM. These two…
We introduce an information-theoretic measure, the Renyi information, to describe the galaxy distribution in space. We discuss properties of the information measure, and demonstrate its relationship with the probability distribution…
Accurate measurement of galaxy structures is a prerequisite for quantitative investigation of galaxy properties or evolution. Yet, the impact of galaxy inclination and dust on commonly used metrics of galaxy structure is poorly quantified.…
We aim to extend and test the classifiers presented in a previous work against an independent dataset. We complement the assessment of the validity of the classifiers by applying them to the set of OGLE light curves treated as variable…
This paper proposes a deep representation learning using an information-theoretic loss with an aim to increase the inter-class distances as well as within-class similarity in the embedded space. Tasks such as anomaly and out-of-distribution…
We demonstrate a new statistical method of determining the global photometric properties of the Milky Way (MW) to an unprecedented degree of accuracy, allowing our Galaxy to be compared directly to objects measured in extragalactic surveys.…
We examine a general framework for visualizing datasets of high (> 2) dimensionality, and demonstrate it using the morphology of galaxies at moderate redshifts. The distributions of various populations of such galaxies are examined in a…
In many applications, Neural Nets (NNs) have classification performance on par or even exceeding human capacity. Moreover, it is likely that NNs leverage underlying features that might differ from those humans perceive to classify. Can we…
Whenever communication takes place to fulfil a goal, an effective way to encode the source data to be transmitted is to use an encoding rule that allows the receiver to meet the requirements of the goal. A formal way to identify the…