Related papers: Predicting Localized Primordial Star Formation wit…
Understanding the physical properties of star-forming cores as mass reservoirs for protostars, and the impact of turbulence, is crucial in star formation studies. We implemented passive tracer particles in clump-scale numerical simulations…
Conventional methods of 3D object generative modeling learn volumetric predictions using deep networks with 3D convolutional operations, which are direct analogies to classical 2D ones. However, these methods are computationally wasteful in…
We present coupled stellar evolution (SE) and 3D radiation-hydrodynamic (RHD) simulations of the evolution of primordial protostars, their immediate environment, and the dynamic accretion history under the influence of stellar ionizing and…
In this paper we examine aspects of primordial star formation in a gravitino warm dark matter universe with a cosmological constant. We compare a set of simulations using a single cosmological realization but with a wide range of warm dark…
In two previous papers, we presented simulations of the first galaxies in a representative volume of the Universe. The simulations are unique because we model feedback-regulated galaxy formation, using time-dependent,…
We study the formation of the first generation of stars in the standard cold dark matter model, using a very high-resolution hydordynamic simulations. Our simulation achieves a dynamic range of 10^{10} in length scale. With accurate…
In order to prepare for the upcoming wide-field cosmological surveys, large simulations of the Universe with realistic galaxy populations are required. In particular, the tendency of galaxies to naturally align towards overdensities, an…
We propose a light-weight deep convolutional neural network (CNN) to estimate the cosmological parameters from simulated 3-dimensional dark matter distributions with high accuracy. The training set is based on 465 realizations of a cubic…
Ionizing UV radiation and supernova flows amidst clustered minihalos at high redshift regulated the rise of the first stellar populations in the universe. Previous studies have addressed the effects of very massive primordial stars on the…
We present a novel method for including the effects of early (pre-supernova) feedback in simulations of galaxy evolution. Rather than building a model which attempts to match idealized, small-scale simulations or analytic approximations, we…
The formation and mass distribution of the first stars depend on various environmental factors in the early universe. We compare 120 cosmological hydrodynamical simulations to explore how the baryonic streaming velocity (SV) relative to…
The concordance model of cosmology and structure formation predicts the formation of isolated very massive stars at high redshifts in dark matter dominated halos of 10^5 to 10^6 Msun. These stars photo-ionize their host primordial molecular…
We investigate prestellar core formation and accretion based on three-dimensional hydrodynamic simulations. Our simulations represent local $\sim 1$pc regions within giant molecular clouds where a supersonic turbulent flow converges,…
Reproducing color-magnitude diagrams (CMDs) of star-resolved galaxies is one of the most precise methods for measuring the star formation history (SFH) of nearby galaxies back to the earliest time. The upcoming big data era poses challenges…
It has been argued that the low-mass primordial stars ($m_{\rm Pop III}\,\leq 0.8\,M_\odot$) are likely to enter the main sequence and hence possibly be found in the present-day Galaxy. However, due to limitations in existing numerical…
(abridged) Context: Both observations and simulations of embedded protostars have progressed rapidly in recent years. Bringing them together is an important step in advancing our knowledge about the earliest phases of star formation. Aims:…
We present a simulation-based inference framework using a convolutional neural network to infer dynamical masses of galaxy clusters from their observed 3D projected phase-space distribution, which consists of the projected galaxy positions…
In this study, we develop an artificial neural network to estimate the infrared (IR) luminosity and star formation rates (SFR) of galaxies. Our network is trained using 'true' IR luminosity values derived from modeling the IR spectral…
We studied the star formation rate (SFR) in cosmological hydrodynamical simulations of galaxy (proto-)clusters in the redshift range $0<z<4$, comparing them to recent observational studies; we also investigated the effect of varying the…
We perform a three dimensional radiation hydrodynamics simulation to investigate the formation of first stars from initial collapse of a primordial gas cloud to formation and growth of protostars. The simulation is integrated until 0.1 Myrs…