North Ecliptic Pole merging galaxy catalogue
arXiv:2202.10780 · doi:10.1051/0004-6361/202141013
Abstract
We aim to generate a catalogue of merging galaxies within the 5.4 sq. deg. North Ecliptic Pole over the redshift range . To do this, imaging data from the Hyper Suprime-Cam are used along with morphological parameters derived from these same data. The catalogue was generated using a hybrid approach. Two neural networks were trained to perform binary merger non-merger classifications: one for galaxies with and another for . Each network used the image and morphological parameters of a galaxy as input. The galaxies that were identified as merger candidates by the network were then visually checked by experts. The resulting mergers will be used to calculate the merger fraction as a function of redshift and compared with literature results. We found that 86.3% of galaxy mergers at and 79.0% of mergers at are expected to be correctly identified by the networks. Of the 34 264 galaxies classified by the neural networks, 10 195 were found to be merger candidates. Of these, 2109 were visually identified to be merging galaxies. We find that the merger fraction increases with redshift, consistent with literature results from observations and simulations, and that there is a mild star-formation rate enhancement in the merger population of a factor of .
Accepted to A&A, 26 pages, 20 figures, 8 tables, 3 appendixes, full tables 1 and 4 will be available on CDS
References in corpus (45)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- The EAGLE project: Simulating the evolution and assembly of galaxies and their environments
- Introducing the Illustris Project: Simulating the coevolution of dark and visible matter in the Universe
- Mass and environment as drivers of galaxy evolution in SDSS and zCOSMOS and the origin of the Schechter function
- Star Formation in AEGIS Field Galaxies since z=1.1 : The Dominance of Gradually Declining Star Formation, and the Main Sequence of Star-Forming Galaxies
- A Highly Consistent Framework for the Evolution of the Star-Forming "Main Sequence" from z~0-6
- Rotation-invariant convolutional neural networks for galaxy morphology prediction
- Galaxy Pairs in the Sloan Digital Sky Survey I: Star Formation, AGN Fraction, and the Luminosity/Mass-Metallicity Relation
- The Evolution of Galaxy Structure over Cosmic Time
- Galaxy pairs in the Sloan Digital Sky Survey - IX: Merger-induced AGN activity as traced by the Wide-field Infrared Survey Explorer
- The Structures of Distant Galaxies I: Galaxy Structures and the Merger Rate to z~3 in the Hubble Ultra-Deep Field
- Galaxy Interactions Trigger Rapid Black Hole Growth: an unprecedented view from the Hyper Suprime-Cam Survey
- A definitive merger-AGN connection at z~0 with CFIS: mergers have an excess of AGN and AGN hosts are more frequently disturbed
- Merging and Clustering of the Swift BAT AGN Sample
- A chronicle of galaxy mass assembly in the EAGLE simulation
- Observational constraints on the merger history of galaxies since : Probabilistic galaxy pair counts in the CANDELS fields
- Galaxy And Mass Assembly (GAMA): Galaxy close-pairs, mergers, and the future fate of stellar mass
- Interacting galaxies on FIRE-2: The connection between enhanced star formation and interstellar gas content
- TiNy Titans: The Role of Dwarf-Dwarf Interactions in the Evolution of Low Mass Galaxies
- A consistent measure of the merger histories of massive galaxies using close-pair statistics I: Major mergers at
- Deep learning predictions of galaxy merger stage and the importance of observational realism
- Incidence of WISE-Selected Obscured AGNs in Major Mergers and Interactions from the SDSS
- Galaxy And Mass Assembly (GAMA): the effect of close interactions on star formation in galaxies
- Galaxy And Mass Assembly (GAMA): Refining the Local Galaxy Merger Rate using Morphological Information
- Massive Close Pairs Measure Rapid Galaxy Assembly in Mergers at High Redshift
- Galaxy Merger Rates up to z 3 using a Bayesian Deep Learning Model A Major-Merger classifier using IllustrisTNG Simulation data
- Late-stage galaxy mergers in COSMOS to z~1
- Identifying Galaxy Mergers in Observations and Simulations with Deep Learning
- Convolutional neural network identification of galaxy post-mergers in UNIONS using IllustrisTNG
- Diverse Structural Evolution at z > 1 in Cosmologically Simulated Galaxies
- Modelling CO emission from hydrodynamic simulations of nearby spirals, starbursting mergers, and high-redshift galaxies
- The merger fraction of active and inactive galaxies in the local Universe through an improved non-parametric classification
- Optical - Near-Infrared catalogue for the AKARI North Ecliptic Pole Deep Field
- The Morphology-Density relationship in 1<z<2 clusters
- Chandra survey in the AKARI North Ecliptic Pole Deep Field. I. X-ray data, point-like source catalog, sensitivity maps, and number counts
- Galaxy mergers up to z < 2.5 II: AGN incidence of merging galaxies at separations of 3-15 kpc
- Galaxy interactions in IllustrisTNG-100, I: The power and limitations of visual identification
- Defining the (Black Hole)-Spheroid Connection with the Discovery of Morphology-Dependent Substructure in the -- and -- Diagrams: New Tests for Advanced Theories and Realistic Simulations
- Towards robust determination of non-parametric morphologies in marginal astronomical data: resolving uncertainties with cosmological hydrodynamical simulations
- Identification of AKARI infrared sources by Deep HSC Optical Survey: Construction of New Band-Merged Catalogue in the NEP-Wide field
- Galaxy and Mass Assembly: luminosity and stellar mass functions in GAMA groups
- The mass--metallicity relation AKARI-FMOS infrared galaxies at in the AKARI North Ecliptic Pole Deep Survey Field
- CFHT MegaPrime/MegaCam -band source catalogue of the North Ecliptic Pole Wide field
- Photometric Redshifts in the North Ecliptic Pole Wide Field based on a Deep Optical Survey with Hyper Suprime-Cam
- Morphology-assisted galaxy mass-to-light predictions using deep learning