Related papers: Identifying Galaxy Mergers in Simulated CEERS NIRC…
Galaxy mergers have long been proposed as a mechanism for funneling gas toward galactic centres, potentially triggering accretion onto supermassive black holes (SMBHs) and igniting active galactic nuclei (AGN). While simulations often…
We propose a random forest (RF) machine learning approach to determine the accreted stellar mass fractions ($f_\mathrm{acc}$) of central galaxies, based on various dark matter halo and galaxy features. The RF is trained and tested using…
We present an automatic method to identify galaxy mergers using the morphological information contained in the residual images of galaxies after the subtraction of a Sersic model. The removal of the bulk signal from the host galaxy light is…
We present a full analysis of galaxy major merger pair fractions, merger rates, and mass accretion rates, thus uncovering the role of mergers in galaxy formation at the earliest previously unexplored epoch of $4.5<z<11.5$. We target…
We estimate the evolution of the galaxy-galaxy merger fraction for $M_\star>10^{10.5}M_\odot$ galaxies over $0.25<z<1$ in the $\sim$18.6 deg$^2$ deep CLAUDS+HSC-SSP surveys. We do this by training a Random Forest Classifier to identify…
Galaxy mergers are traditionally one of the favoured mechanisms for quenching star formation. To test this paradigm in the context of modern cosmological simulations, we use the IllustrisTNG simulation to investigate the impact of…
Estimates of galaxy merger rates based on counts of close pairs typically assume that most of the observed systems will merge within a few hundred Myr (for projected pair separations <25 kpc/h). Here we investigate these assumptions using…
We aim to generate a catalogue of merging galaxies within the 5.4 sq. deg. North Ecliptic Pole over the redshift range $0.0 < z < 0.3$. To do this, imaging data from the Hyper Suprime-Cam are used along with morphological parameters derived…
We investigate the evolution of the galaxy merger rate predicted by two semi-analytical galaxy formation models implemented on the Millennium Simulation of dark matter structure growth. The fraction of merging galaxy pairs at each time-step…
We present the first results from applying the Santa Cruz semi-analytic model (SAM) for galaxy formation on merger trees extracted from a dark matter only version of the IllustrisTNG (TNG) simulations. We carry out a statistical comparison…
Mergers play a critical role in galaxy evolution, but their relationship to their surrounding environments is unexplored at high redshift. We investigate the galaxy merger rate among 124 [OIII] emitters at $5.3<z<6.9$ as a function of local…
This paper presents direct evidence for hierarchical galaxy assembly out to redshifts z ~ 3. We identify major mergers using the model-independent CAS (concentration, asymmetry, clumpiness) physical morphological system on galaxies…
Various galaxy merger detection methods have been applied to diverse datasets. However, it is difficult to understand how they compare. We aim to benchmark the relative performance of machine learning (ML) merger detection methods. We…
The role of major mergers in galaxy and black hole formation is not well constrained. To help address this, we develop an automated method to identify late-stage galaxy mergers before coalescence of the galactic cores. The resulting sample…
In this paper of ERGO-ML (Extracting Reality from Galaxy Observables with Machine Learning), we develop a model that infers the merger/assembly histories of galaxies directly from optical images. We apply the self-supervised contrastive…
A fundamental feature of galaxies is their structure, yet we are just now understanding the evolution of structural properties in quantitative ways. As such, we explore the quantitative non-parametric structural evolution of 16,778 galaxies…
Galaxy morphology is one of the most fundamental ways to describe galaxy properties, but the morphology we observe may be affected by wavelength and spatial resolution, which may introduce systematic bias when comparing galaxies at…
Non-parametric morphology measures are a powerful tool for identifying galaxy mergers at low redshifts. We employ cosmological zoom simulations using Gizmo with the Mufasa feedback scheme, post-processed using 3D dust radiative transfer…
Numerical simulations of variants of the CDM~model with different cosmological parameters are used to compare statistical measures such as mass spectra, merger processes, and autocorrelation functions, for different models with relevant…
Aims. We present the application of a fully connected neural network (NN) for galaxy merger identification using exclusively photometric information. Our purpose is not only to test the method's efficiency, but also to understand what…