Related papers: A Deep Learning Approach for Characterizing Major …
Machine learning has been successfully applied in varied field but whether it is a viable tool for determining the distance to molecular clouds in the Galaxy is an open question. In the Galaxy, the kinematic distance is commonly employed as…
In the context of radio galaxy classification, most state-of-the-art neural network algorithms have been focused on single survey data. The question of whether these trained algorithms have cross-survey identification ability or can be…
We measure the mass growth rate by merging for a wide range of galaxy types. We present the small-scale (0.014 < r < 11 h70^{-1} Mpc) projected cross-correlation functions w(rp) of galaxy subsamples from the spectroscopic sample of the NYU…
The mergers of massive black hole binaries could generate rich electromagnetic emissions, which allow us to probe the environments surrounding these massive black holes and gain deeper insights into the high energy astrophysics. However,…
We present a deep machine learning (ML)-based technique for accurately determining $\sigma_8$ and $\Omega_m$ from mock 3D galaxy surveys. The mock surveys are built from the AbacusCosmos suite of $N$-body simulations, which comprises 40…
We present the prospects for the early (pre-merger) detection and localization of compact-binary coalescences using gravitational waves over the next 10 years. Early warning can enable the direct observation of the prompt and early…
We combine star formation along the `main sequence', quiescence, and clustering and merging to produce an empirical model for the evolution of individual galaxies. Main sequence star formation alone would significantly steepen the stellar…
We propose a new method to estimate the photometric redshift of galaxies by using the full galaxy image in each measured band. This method draws from the latest techniques and advances in machine learning, in particular Deep Neural…
At high redshift, due to both observational limitations and the variety of galaxy morphologies in the early universe, measuring galaxy structure can be challenging. Non-parametric measurements such as the CAS system have thus become an…
Understanding the formation and evolution of ring galaxies, which possess an atypical ring-like structure, is crucial for advancing knowledge of black holes and galaxy dynamics. However, current catalogs of ring galaxies are limited, as…
The next generation of submillimetre/millimetre instruments will provide us with a deeper insight into the mechanisms that rule galaxy formation. As the brightest starbursts are thought to be heavily obscured at optical wavelengths, the…
Utilizing a high-resolution (114 pc/h) adaptive mesh-refinement cosmological galaxy formation simulation of the standard cold dark matter model with a large (2000-3000 galaxies with stellar mass greater than 1e9 Msun) statistical sample, we…
We present an analysis of specific star formation rates (sSFR) across the galaxy merger sequence using visual classifications from the Zooniverse citizen science project "Cosmic Disco: Characterizing Galaxy Collisions". Our sample comprises…
From a Chandra survey of nine interacting galaxy systems the evolution of X-ray emission during the merger process has been investigated. It is found that the X-ray luminosity peaks ~300 Myr before nuclear coalescence, and then dips, even…
The total masses of galaxy clusters characterize many aspects of astrophysics and the underlying cosmology. It is crucial to obtain reliable and accurate mass estimates for numerous galaxy clusters over a wide range of redshifts and mass…
We present a deep-learning artificial intelligence model that is capable of learning and forecasting the late-inspiral, merger and ringdown of numerical relativity waveforms that describe quasi-circular, spinning, non-precessing binary…
We describe a layer-by-layer algorithm for training deep convolutional networks, where each step involves gradient updates for a two layer network followed by a simple clustering algorithm. Our algorithm stems from a deep generative model…
Calculating the galaxy merger rate requires both a census of galaxies identified as merger candidates, and a cosmologically-averaged `observability' timescale T_obs(z) for identifying galaxy mergers. While many have counted galaxy mergers…
The global 21 cm HI emission-line profile of a galaxy encodes valuable information on the spatial distribution and kinematics of the neutral atomic gas. Galaxy interactions significantly influence the HI disk and imprint observable features…
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…