DeepAI AI Chat
Log In Sign Up

DeepMerge: Classifying High-redshift Merging Galaxies with Deep Neural Networks

by   A. Ćiprijanović, et al.
University of Belgrade

We investigate and demonstrate the use of convolutional neural networks (CNNs) for the task of distinguishing between merging and non-merging galaxies in simulated images, and for the first time at high redshifts (i.e. z=2). We extract images of merging and non-merging galaxies from the Illustris-1 cosmological simulation and apply observational and experimental noise that mimics that from the Hubble Space Telescope; the data without noise form a "pristine" data set and that with noise form a "noisy" data set. The test set classification accuracy of the CNN is 79% for pristine and 76% for noisy. The CNN outperforms a Random Forest classifier, which was shown to be superior to conventional one- or two-dimensional statistical methods (Concentration, Asymmetry, the Gini, M_20 statistics etc.), which are commonly used when classifying merging galaxies. We also investigate the selection effects of the classifier with respect to merger state and star formation rate, finding no bias. Finally, we extract Grad-CAMs (Gradient-weighted Class Activation Mapping) from the results to further assess and interrogate the fidelity of the classification model.


page 5

page 11

page 13

page 16


A class of ie-merging functions

We describe a general class of ie-merging functions and pose the problem...

DeepMerge II: Building Robust Deep Learning Algorithms for Merging Galaxy Identification Across Domains

In astronomy, neural networks are often trained on simulation data with ...

Results Merging in the Patent Domain

In this paper, we test machine learning methods for results merging in p...

A study on the deviations in performance of FNNs and CNNs in the realm of grayscale adversarial images

Neural Networks are prone to having lesser accuracy in the classificatio...

Classification Uncertainty of Deep Neural Networks Based on Gradient Information

We study the quantification of uncertainty of Convolutional Neural Netwo...

Neural Style Representations and the Large-Scale Classification of Artistic Style

The artistic style of a painting is a subtle aesthetic judgment used by ...

Merging of neural networks

We propose a simple scheme for merging two neural networks trained with ...