Figure 5 - uploaded by Greg L. Bryan
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The formation of a disk-like galaxy in an AMR simulation. The upper left panel shows the gas density on the root grid, and each panel in clockwise order shows an increasingly smaller region at higher resolution.
Source publication
Using galactic clusters, galactic formation, and the first stars
as examples, the author demonstrates how adaptive mesh refinement
techniques can be successfully applied to cosmological research. The
method combines adaptive refinement of interesting regions with modern
grid-based methods for solving hydrodynamic equations
Context in source publication
Context 1
... to concentrate the available computa- tional power on the area of interest while in- cluding the surrounding material's long-range gravitational effects, we employ the same focus- ing technique as for galaxy-cluster simulations. Figure 5's first panel clearly demonstrates this; it shows a projection of the gas density through much of the computational box. Most of the re- gion has visibly large grid cells, while a small re- gion, approximately 1% of the total volume, is adaptively refined. ...
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... We use the grid-based, adaptive mesh refinement (AMR) code Enzo (O'shea et al. 2005;Bryan et al. 2014) to model the formation of primordial gas cloud with turbulence. The AMR technique (Berger & Colella 1989;Bryan 1999;Norman & Bryan 1999;Bryan & Norman 2000) automatically increase the spatial resolution if the designated physical quantities, such as density and velocity, of the grids satisfy the refinement criteria. Enzo combines the N-body scheme (Hockney & Eastwood 1988;Couchman 1991) for the collisionless particles and the Eulerian method for fluid dynamics; it solves the compressible Euler equations by means of MUSCL-based method (Wang et al. 2008) and second-order Runge-Kutta scheme (Shu & Osher 1988) for time integration. ...
This paper studies the effect of turbulence in the formation process of the Population III (Pop III) stars as known as the first stars, which play a key role in the cosmic evolution. Previous cosmological simulations of Pop III star formation suggested these stars would have a typical mass of $\mathrm{\sim 100 \, M_\odot}$. However, this mass scale is inconsistent with the recent observations of the extremely metal-poor stars that infer the mass scale of the Pop III stars to be around $\mathrm{25 \, M_\odot}$. This mass discrepancy may be due to the unresolved turbulence of the Pop III star-forming cloud driven by the accrecting primordial gas during the mini-halo formation in the previous cosmological simulations. Unfortunately, such turbulent flow cannot be resolved in these simulations. To examine the effect of the turbulence in the Pop III star-forming cloud, we use the adaptive mesh refinement (AMR) code, $\texttt{Enzo}$ to model the turbulent Pop III star-forming cloud using an artificial-driven turbulence scheme and including the relevant gas physics. This artificial-driven turbulence uses the stochastic forcing model to mimic the unresolved turbulence inside mini-halos. We find that several clumps with dense cores of $\mathrm{22.7 - 174.9 \, M_\odot}$ form in the turbulent Pop III star-forming cloud. These cores are subjected to the Jeans instability, and they will soon collapse to form stars. As turbulence becomes stronger and more compressive, the number of clumps increases. Our results suggest strong and compressive turbulence can effectively fragment primordial star-forming clouds and decrease the theoretical mass scale of Pop III stars that possibly resolves the mass discrepancy between simulations and observations.
... Results from cosmological hydrodynamic simulations also suggest that cold, neutral hydrogen gas is preferentially found near void centres, where there is no shock-heating from structure formation. Kreckel et al. (2011), a study of galaxies in the Enzo simulation (Bryan 1999), found that low-luminosity dwarf galaxies are over-represented near the centre of the void region. A more recent cosmological simulation using over a thousand voids by Rodríguez Medrano et al. (2021) found that most intergalactic hydrogen in the interiors of voids exists in a diffuse, low temperature phase (T<10 15 K), which is strong in Ly absorption. ...
We investigate the spatial distribution of Lyman-$\alpha$ (Ly $\alpha$) absorbers within cosmic voids. We create a catalogue of cosmic voids in Sloan Digital Sky Survey Data Release 7 (SDSS DR7) with the VoidFinder algorithm of the Void Analysis Software Toolkit (VAST). Using the largest catalogue of low-redshift (z $\leq$ 0.75) IGM absorbers to date, we identify 392 Ly $\alpha$ absorbers inside voids. The fraction of Ly $\alpha$ absorbers inside voids (65 per cent) is comparable to the volume filling fraction of voids (68 per cent), and significantly greater than the fraction of galaxies inside voids (21 per cent). Inside voids, the spatial distribution of Ly $\alpha$ absorbers differs markedly from that of galaxies. Galaxy density rises sharply near void edges, while Ly $\alpha$ absorber density is relatively uniform. The radial distribution of Ly $\alpha$ absorbers inside voids differs marginally from a random distribution. We find that lower column density Ly $\alpha$ absorbers are more centrally concentrated inside voids than higher column density Ly $\alpha$ absorbers. These results suggest the presence of two populations of Ly $\alpha$ absorbers: low column density systems that are nearly uniformly distributed in the interiors of voids and systems associated with galaxies at the edges of voids.
... In fact, the range is derived from a semivariogram model representing a crude estimate of varying ranges occurring at various scales. It is intuitively clear that depending on the degree of heterogeneity, which is spatiotemporally variable, the grid size needs to be adaptively adjusted (Bryan, 1999). For the sake of simplicity, but at a higher computational cost, we adopt a numerical solution which is to first simulate on a coarse grid and then on a finer one until the difference with respect to the previous grid size across all pixels reaches an acceptable value (< 1 %). ...
Most studies on validation of satellite trace gas retrievals or atmospheric
chemical transport models assume that pointwise measurements, which roughly
represent the element of space, should compare well with satellite (model)
pixels (grid box). This assumption implies that the field of interest must
possess a high degree of spatial homogeneity within the pixels (grid box),
which may not hold true for species with short atmospheric lifetimes or in
the proximity of plumes. Results of this assumption often lead to a
perception of a nonphysical discrepancy between data, resulting from
different spatial scales, potentially making the comparisons prone to
overinterpretation. Semivariogram is a mathematical expression of spatial
variability in discrete data. Modeling the semivariogram behavior permits
carrying out spatial optimal linear prediction of a random process field
using kriging. Kriging can extract the spatial information (variance)
pertaining to a specific scale, which in turn translates pointwise data to
a gridded space with quantified uncertainty such that a grid-to-grid
comparison can be made. Here, using both theoretical and real-world
experiments, we demonstrate that this classical geostatistical approach can
be well adapted to solving problems in evaluating model-predicted or
satellite-derived atmospheric trace gases. This study suggests that
satellite validation procedures using the present method must take kriging
variance and satellite spatial response functions into account. We present
the comparison of Ozone Monitoring Instrument (OMI) tropospheric NO2
columns against 11 Pandora spectrometer instrument (PSI) systems during the
DISCOVER-AQ campaign over Houston. The least-squares fit to the paired data shows a low slope (OMI=0.76×PSI+1.18×1015 molecules cm−2, r2=0.66), which is indicative of varying biases in OMI. This perceived slope, induced by the problem of spatial scale, disappears in the comparison of the convolved kriged PSI and OMI (0.96×PSI+0.66×1015 molecules cm−2,
r2=0.72), illustrating that OMI possibly has a constant systematic
bias over the area. To avoid gross errors in comparisons made between
gridded data vs. pointwise measurements, we argue that the concept of
semivariogram (or spatial autocorrelation) should be taken into
consideration, particularly if the field exhibits a strong degree of spatial
heterogeneity at the scale of satellite and/or model footprints.
... Numerical simulations predict what properties we should expect from inflowing and outflowing material over a galactic histories, such as the size, angular momentum, and luminosity. [1][2][3][4][5] However, without direct measurements of these properties, these theories are difficult to back up. ...
The Faint Intergalactic-medium Redshifted Emission Balloon (FIREBall-2, FB-2) is designed to discover and map faint UV emission from the circumgalactic medium around low redshift galaxies (z ~ 0.3 (C IV); z ~ 0.7 (Lyα); z ~ 1.0 (O VI)). FIREBall-2's first launch, on September 22nd 2018 out of Ft. Sumner, NM, was abruptly cut short due to a hole that developed in the balloon. FIREBall-2 was unable to observe above its minimum require altitude (25 km; nominal: 32 km) for its shortest required time (2 hours; nominal: 8+ hours). The shape of the deflated balloon, as well as a concurrent full moon close to our observed target field, revealed a severe, off-axis scattered light path directly to the UV science detector. Additional damage to FB-2 added complications to the ongoing effort to prepare FB-2 for a quick re-flight. Upon landing, several mirrors in the optical chain, including the two large telescope mirrors, were damaged, resulting in chunks of material broken off the sides and reflecting surfaces. The magnifying optical element, called the focal corrector, was discovered to be misaligned beyond tolerance after the 2018 flight, with one of its two mirrors damaged from the landing impact. We describe the steps taken thus far to mitigate the damage to the optics, as well as procedures and results from the ongoing efforts to re-align the focal corrector and spectrograph optics. We report the throughput of the spectrograph before and after the 2018 flight and plans for improving it. Finally, we describe several methods by which we address the scattered light issues seen from FIREBall-2's 2018 campaign and present the current status of FB-2 to fly during the summer campaign in Palestine, TX in 2020.
... To investigate the effects of different galactic environments, we conducted a series of simulations using ENZO; a threedimensional adaptive mesh refinement (AMR) hydrodynamics code (Bryan & Norman 1997;Bryan 1999;Bryan et al. 2014) previously utilized successfully in galactic-scale simulations by Tasker & Tan (2009);Fujimoto et al. (2014a); Utreras et al. (2016); Jin et al. (2017). One of the strengths of this method is the ability to model multiphase gases over a wide range of temperature, density and pressure, allowing a self-consistent ISM to be easily developed. ...
We explore the effect of different galactic disc environments on the properties of star-forming clouds through variations in the background potential in a set of isolated galaxy simulations. Rising, falling and flat rotation curves expected in halo dominated, disc dominated and Milky Way-like galaxies were considered, with and without an additional two-arm spiral potential. The evolution of each disc displayed notable variations that are attributed to different regimes of stability, determined by shear and gravitational collapse. The properties of a typical cloud were largely unaffected by the changes in rotation curve, but the production of small and large cloud associations was strongly dependent on this environment. This suggests that while differing rotation curves can influence where clouds are initially formed, the average bulk properties are effectively independent of the global environment. The addition of a spiral perturbation made the greatest difference to cloud properties, successfully sweeping the gas into larger, seemingly unbound, extended structures and creating large arm-interarm contrasts.
... Our simulation was performed using Enzo; a threedimensional adaptive mesh refinement (AMR) hydrodynamics code (Bryan & Norman 1997;Bryan 1999;Bryan et al. 2014). The galaxy is simulated in a three-dimensional box of side 32 kpc with a root grid of 128 3 cells and eight levels of refinement, giving a limiting resolution of ∆xmin 1.0 pc. ...
We determine the physical properties and turbulence driving mode of molecular clouds formed in numerical simulations of a Milky Way-type disc galaxy with parsec-scale resolution. The clouds form through gravitational fragmentation of the gas, leading to average values for mass, radii and velocity dispersion in good agreement with observations of Milky Way clouds. The driving parameter (b) for the turbulence within each cloud is characterised by the ratio of the density contrast (sigma_rho) to the average Mach number (Mach) within the cloud, b = sigma_rho/Mach. As shown in previous works, b ~ 1/3 indicates solenoidal (divergence-free) driving and b ~ 1 indicates compressive (curl-free) driving. We find that the average b value of all the clouds formed in the simulations has a lower limit of b > 0.2. Importantly, we find that b has a broad distribution, covering values from purely solenoidal to purely compressive driving. Tracking the evolution of individual clouds reveals that the b value for each cloud does not vary significantly over their lifetime. Finally, we perform a resolution study with minimum cell sizes of 8, 4, 2 and 1 pc and find that the average b value increases with increasing resolution. Therefore, we conclude that our measured b values are strictly lower limits and that a resolution better than 1 pc is required for convergence. However, regardless of the resolution, we find that b varies by factors of a few in all cases, which means that the effective driving mode alters significantly from cloud to cloud.
... For the details of our simulations, we refer the reader to Cen (2012), although for completeness we reiterate the main points here. We perform cosmological simulations with the AMR Eulerian hydrodynamical code Enzo (Bryan 1999;Bryan et al. 2014). We use cosmological parameters consistent with the WMAP7-normalized LCDM model (Komatsu et al. 2011): Ω M = 0.28, Ω b = 0.046, Ω Λ = 0.72, σ 8 = 0.82, H o = 100 h km s −1 Mpc −1 = 70 km s −1 Mpc −1 , and n = 0.96. ...
The connection between dark matter halos and galactic baryons is often not
well-constrained nor well-resolved in cosmological hydrodynamical simulations.
Thus, Halo Occupation Distribution (HOD) models that assign galaxies to halos
based on halo mass are frequently used to interpret clustering observations,
even though it is well-known that the assembly history of dark matter halos is
related to their clustering. In this paper we use high-resolution
hydrodynamical cosmological simulations to compare the halo and stellar mass
growth of galaxies in a large-scale overdensity to those in a large-scale
underdensity (on scales of about 20 Mpc). The simulation reproduces assembly
bias, that halos have earlier formation times in overdense environments than in
underdense regions. We find that the stellar mass to halo mass ratio is larger
in overdense regions in central galaxies residing in halos with masses between
10$^{11}$-10$^{12.9}$ M$_{\odot}$. When we force the local density (within 2
Mpc) at z=0 to be the same for galaxies in the large-scale over- and
underdensities, we find the same results. We posit that this difference can be
explained by a combination of earlier formation times, more interactions at
early times with neighbors, and more filaments feeding galaxies in overdense
regions. This result puts the standard practice of assigning stellar mass to
halos based only on their mass, rather than considering their larger
environment, into question.
... The numerical code is a modified version of the Adaptive Mesh Refinement (AMR) code Enzo 2.0 (Bryan & Norman 1997;Bryan 1999;O'Shea et al. 2004). To solve the magnetohydrodynamical equations, we use a 2ndorder Runge-Kutta temporal update of the conserved variables with the Local Lax-Friedrichs (LLF) Riemann solver and a piecewise linear reconstruction method. ...
We utilize magnetohydrodynamic (MHD) simulations to develop a numerical model
for GMC-GMC collisions between nearly magnetically critical clouds. The goal is
to determine if, and under what circumstances, cloud collisions can cause
pre-existing magnetically subcritical clumps to become supercritical and
undergo gravitational collapse. We first develop and implement new
photodissociation region (PDR) based heating and cooling functions that span
the atomic to molecular transition, creating a multiphase ISM and allowing
modeling of non-equilibrium temperature structures. Then in 2D and with ideal
MHD, we explore a wide parameter space of magnetic field strength, magnetic
field geometry, collision velocity, and impact parameter, and compare isolated
versus colliding clouds. We find factors of ~2-3 increase in mean clump density
from typical collisions, with strong dependence on collision velocity and
magnetic field strength, but ultimately limited by flux-freezing in 2D
geometries. For geometries enabling flow along magnetic field lines, greater
degrees of collapse are seen. We discuss observational diagnostics of cloud
collisions, focussing on 13CO(J=2-1), 13CO(J=3-2), and 12CO(J=8-7) integrated
intensity maps and spectra, which we synthesize from our simulation outputs. We
find the ratio of J=8-7 to lower-J emission is a powerful diagnostic probe of
GMC collisions.
... Applying more computational resources to select parts of the domain means both application runtime and memory usage can be reduced. Developed by Berger et al. [21,23], block-structured AMR has been successfully applied to domains including cosmology, astrophysics, and shock hydrodynamics [28,53,139]. For simplicity, throughout this thesis we use the terms adaptive mesh refinement and AMR to refer to the block-structured method unless explicitly stated. ...
... Block-structured Adaptive Mesh Refinement (AMR) is a technique used to increase simulation accuracy and reduce resource usage by dynamically increasing mesh resolution in the areas in which it will be most effective. Developed by Berger et al. [21,23], AMR has been successfully applied to domains including cosmology, astrophysics, and shock hydrodynamics [28,53,139]. These areas all contain disparate physical scales that make using a fine mesh resolution throughout the problem domain unattractive. ...
... For the details of our simulations, we refer the reader to Cen (2012), although for completeness we reiterate the main points here. We perform cosmological simulations with the adaptive mesh refinement Eulerian hydrodynamical code Enzo (Bryan 1999; O'Shea et al. 2004; Joung et al. 2009). We use cosmological parameters consistent with the WMAP7- normalized LCDM model (Komatsu et al. 2011): ...
Recent surveys have found a reversal of the star formation rate (SFR)-density relation at z = 1 from that at z = 0, while the sign of the slope of the color-density relation remains unchanged. We use adaptive mesh refinement cosmological hydrodynamic simulations of a 21 × 24 × 20 h
–3 Mpc3 region to examine the SFR-density and color-density relations of galaxies at z = 0 and z = 1. The local environmental density is defined by the dark matter mass in spheres of radius 1 h
–1 Mpc, and we probe two decades of environmental densities. Our simulations produce a large increase of SFR with density at z = 1, as in the Elbaz et al. observations. We also find a significant evolution to z = 0, where the SFR-density relation is much flatter. The simulated color-density relation is consistent from z = 1 to z = 0, in agreement with observations. We find that the increase in SFR with local density at z = 1 is due to a growing population of star-forming galaxies in higher-density environments. At z = 0 and z = 1 both the SFR and cold gas mass are correlated with the galaxy halo mass, and therefore the correlation between median halo mass and local density is an important cause of the SFR-density relation at both redshifts. However, at z = 0 the local density on 1 h
–1 Mpc scales affects galaxy SFRs as much as halo mass. Finally, we find indications that while at z = 0 high-density environments depress galaxy SFRs, at z = 1 high-density environments tend to increase SFRs.
