ABSTRACT
The splashback radius, Rsp, is a physically motivated halo boundary that separates infalling and collapsed matter of haloes. We study Rsp in the hydrodynamic and dark matter-only ...IllustrisTNG simulations. The most commonly adopted signature of Rsp is the radius at which the radial density profiles are steepest. Therefore, we explicitly optimize our density profile fit to the profile slope and find that this leads to a $\sim 5{{\ \rm per\ cent}}$ larger radius compared to other optimizations. We calculate Rsp for haloes with masses between 1013 and 15 M⊙ as a function of halo mass, accretion rate, and redshift. Rsp decreases with mass and with redshift for haloes of similar M200 m in agreement with previous work. We also find that Rsp/R200 m decreases with halo accretion rate. We apply our analysis to dark matter, gas, and satellite galaxies associated with haloes to investigate the observational potential of Rsp. The radius of steepest slope in gas profiles is consistently smaller than the value calculated from dark matter profiles. The steepest slope in galaxy profiles, which are often used in observations, tends to agree with dark matter profiles but is lower for less massive haloes. We compare Rsp in hydrodynamic and N-body dark matter-only simulations and do not find a significant difference caused by the addition of baryonic physics. Thus, results from dark matter-only simulations should be applicable to realistic haloes.
We use the BAHAMAS (BAryons and HAloes of MAssive Systems) and MACSIS (MAssive ClusterS and Intercluster Structures) hydrodynamic simulations to quantify the impact of baryons on the mass ...distribution and dynamics of massive galaxy clusters, as well as the bias in X-ray and weak lensing mass estimates. These simulations use the subgrid physics models calibrated in the BAHAMAS project, which include feedback from both supernovae and active galactic nuclei. They form a cluster population covering almost two orders of magnitude in mass, with more than 3500 clusters with masses greater than 10 super( 14) M... at z = 0. We start by characterizing the clusters in terms of their spin, shape and density profile, before considering the bias in both weak lensing and hydrostatic mass estimates. Whilst including baryonic effects leads to more spherical, centrally concentrated clusters, the median weak lensing mass bias is unaffected by the presence of baryons. In both the dark matter only and hydrodynamic simulations, the weak lensing measurements underestimate cluster masses by ...10 per cent for clusters with M200 = 10 super( 15) M... and this bias tends to zero at higher masses. We also consider the hydrostatic bias when using both the true density and temperature profiles, and those derived from X-ray spectroscopy. When using spectroscopic temperatures and densities, the hydrostatic bias decreases as a function of mass, leading to a bias of ...40 per cent for clusters with M500 greater than or equal to 10 super( 15) M... This is due to the presence of cooler gas in the cluster outskirts. Using mass weighted temperatures and the true density profile reduces this bias to 5-15 per cent. (ProQuest: ... denotes formulae/symbols omitted.)
Abstract
We use the Cluster-EAGLE simulations to explore the velocity bias introduced when using galaxies, rather than dark matter particles, to estimate the velocity dispersion of a galaxy cluster, ...a property known to be tightly correlated with cluster mass. The simulations consist of 30 clusters spanning a mass range 14.0 ≤ log10(M200 c/M⊙) ≤ 15.4, with their sophisticated subgrid physics modelling and high numerical resolution (subkpc gravitational softening), making them ideal for this purpose. We find that selecting galaxies by their total mass results in a velocity dispersion that is 5–10 per cent higher than the dark matter particles. However, selecting galaxies by their stellar mass results in an almost unbiased (<5 per cent) estimator of the velocity dispersion. This result holds out to z = 1.5 and is relatively insensitive to the choice of cluster aperture, varying by less than 5 per cent between r500 c and r200 m. We show that the velocity bias is a function of the time spent by a galaxy inside the cluster environment. Selecting galaxies by their total mass results in a larger bias because a larger fraction of objects have only recently entered the cluster and these have a velocity bias above unity. Galaxies that entered more than 4 Gyr ago become progressively colder with time, as expected from dynamical friction. We conclude that velocity bias should not be a major issue when estimating cluster masses from kinematic methods.
Bi-phasic or diauxic growth is often observed when microbes are grown in a chemically defined medium containing two sugars (for example glucose and lactose). Typically, the two growth stages are ...separated by an often lengthy phase of arrested growth, the so-called lag-phase. Diauxic growth is usually interpreted as an adaptation to maximise population growth in multi-nutrient environments. However, the lag-phase implies a substantial loss of growth during the switch-over. It therefore remains unexplained why the lag-phase is adaptive. Here we show by means of a stochastic simulation model based on the bacterial PTS system that it is not possible to shorten the lag-phase without incurring a permanent growth-penalty. Mechanistically, this is due to the inherent and well established limitations of biological sensors to operate efficiently at a given resource cost. Hence, there is a trade-off between lost growth during the diauxic switch and the long-term growth potential of the cell. Using simulated evolution we predict that the lag-phase will evolve depending on the distribution of conditions experienced during adaptation. In environments where switching is less frequently required, the lag-phase will evolve to be longer whereas, in frequently changing environments, the lag-phase will evolve to be shorter.
ABSTRACT
We introduce the First Light And Reionisation Epoch Simulations (FLARES), a suite of zoom simulations using the EAGLE model. We resimulate a range of overdensities during the Epoch of ...Reionization (EoR) in order to build composite distribution functions, as well as explore the environmental dependence of galaxy formation and evolution during this critical period of galaxy assembly. The regions are selected from a large $(3.2 \, \mathrm{cGpc})^{3}$ parent volume, based on their overdensity within a sphere of radius 14 h−1 cMpc. We then resimulate with full hydrodynamics, and employ a novel weighting scheme that allows the construction of composite distribution functions that are representative of the full parent volume. This significantly extends the dynamic range compared to smaller volume periodic simulations. We present an analysis of the galaxy stellar mass function (GSMF), the star formation rate distribution function (SFRF), and the star-forming sequence (SFS) predicted by FLARES, and compare to a number of observational and model constraints. We also analyse the environmental dependence over an unprecedented range of overdensity. Both the GSMF and the SFRF exhibit a clear double-Schechter form, up to the highest redshifts (z = 10). We also find no environmental dependence of the SFS normalization. The increased dynamic range probed by FLARES will allow us to make predictions for a number of large area surveys that will probe the EoR in coming years, carried out on new observatories such as Roman and Euclid.
We present the MAssive ClusterS and Intercluster Structures (MACSIS) project, a suite of 390 clusters simulated with baryonic physics that yields realistic massive galaxy clusters capable of matching ...a wide range of observed properties. MACSIS extends the recent BAryons and HAloes of MAssive Systems simulation to higher masses, enabling robust predictions for the redshift evolution of cluster properties and an assessment of the effect of selecting only the hottest systems. We study the observable-mass scaling relations and the X-ray luminosity-temperature relation over the complete observed cluster mass range. As expected, we find that the slope of these scaling relations and the evolution of their normalization with redshift depart significantly from the self-similar predictions. However, for a sample of hot clusters with core-excised temperatures k sub( B)T greater than or equal to 5 keV, the normalization and the slope of the observable-mass relations and their evolution are significantly closer to self-similar. The exception is the temperature-mass relation, for which the increased importance of non-thermal pressure support and biased X-ray temperatures leads to a greater departure from self-similarity in the hottest systems. As a consequence, these also affect the slope and evolution of the normalization in the luminosity-temperature relation. The median hot gas profiles show good agreement with observational data at z = 0 and z = 1, with their evolution again departing significantly from the self-similar prediction. However, selecting a hot sample of clusters yields profiles that evolve significantly closer to the self-similar prediction. In conclusion, our results show that understanding the selection function is vital for robust calibration of cluster properties with mass and redshift.
Earth's future carbon balance and regional carbon exchange dynamics are inextricably linked to plant photosynthesis. Spectral vegetation indices are widely used as proxies for vegetation greenness ...and to estimate state variables such as vegetation cover and leaf area index. However, the capacity of green leaves to take up carbon can change throughout the season. We quantify photosynthetic capacity as the maximum rate of RuBP carboxylation (Vcmax) and regeneration (Jmax). Vcmax and Jmax vary within-season due to interactions between ontogenetic processes and meteorological variables. Remote sensing-based estimation of Vcmax and Jmax using leaf reflectance spectra is promising, but temporal variation in relationships between these key determinants of photosynthetic capacity, leaf reflectance spectra, and the models that link these variables has not been evaluated. To address this issue, we studied hybrid poplar (Populus spp.) during a 7-week mid-summer period to quantify seasonally-dynamic relationships between Vcmax, Jmax, and leaf spectra. We compared in situ estimates of Vcmax and Jmax from gas exchange measurements to estimates of Vcmax and Jmax derived from partial least squares regression (PLSR) and fresh-leaf reflectance spectroscopy. PLSR models were robust despite dynamic temporal variation in Vcmax and Jmax throughout the study period. Within-population variation in plant stress modestly reduced PLSR model predictive capacity. Hyperspectral vegetation indices were well-correlated to Vcmax and Jmax, including the widely-used Normalized Difference Vegetation Index. Our results show that hyperspectral estimation of plant physiological traits using PLSR may be robust to temporal variation. Additionally, hyperspectral vegetation indices may be sufficient to detect temporal changes in photosynthetic capacity in contexts similar to those studied here. Overall, our results highlight the potential for hyperspectral remote sensing to estimate determinants of photosynthetic capacity during periods with dynamic temporal variations related to seasonality and plant stress, thereby improving estimates of plant productivity and characterization of the associated carbon budget.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
We introduce the Hydrangea simulations, a suite of 24 cosmological hydrodynamic zoom-in simulations of massive galaxy clusters (M
200c = 1014–1015.4 M⊙) with baryon particle masses of ∼106 ...M⊙. Designed to study the impact of the cluster environment on galaxy formation, they are a key part of the ‘Cluster–EAGLE’ project. They use a galaxy formation model developed for the EAGLE project, which has been shown to yield both realistic field galaxies and hot gas fractions of galaxy groups consistent with observations. The total stellar mass content of the simulated clusters agrees with observations, but central cluster galaxies are too massive, by up to 0.6 dex. Passive satellite fractions are higher than in the field, and at stellar masses M
star > 1010 M⊙, this environmental effect is quantitatively consistent with observations. The predicted satellite stellar mass function matches data from local cluster surveys. Normalized to total mass, there are fewer low-mass (M
star ≲ 1010 M⊙) galaxies within the virial radius of clusters than in the field, primarily due to star formation quenching. Conversely, the simulations predict an overabundance of massive galaxies in clusters compared to the field that persists to their far outskirts (>5 r
200c). This is caused by a significantly increased stellar mass fraction of (sub-)haloes in the cluster environment, by up to ∼0.3 dex even well beyond r
200c. Haloes near clusters are also more concentrated than equally massive field haloes, but these two effects are largely uncorrelated.
ABSTRACT
Dynamically relaxed galaxy clusters have long played an important role in galaxy cluster studies because it is thought their properties can be reconstructed more precisely and with less ...systematics. As relaxed clusters are desirable, there exist a plethora of criteria for classifying a galaxy cluster as relaxed. In this work, we examine 9 commonly used observational and theoretical morphological metrics extracted from $54\, 000$mock-X synthetic X-ray images of galaxy clusters taken from the IllustrisTNG, BAHAMAS, and MACSIS simulation suites. We find that the simulated criteria distributions are in reasonable agreement with the observed distributions. Many criteria distributions evolve as a function of redshift, cluster mass, numerical resolution, and subgrid physics, limiting the effectiveness of a single relaxation threshold value. All criteria are positively correlated with each other, however, the strength of the correlation is sensitive to redshift, mass, and numerical choices. Driven by the intrinsic scatter inherent to all morphological metrics and the arbitrary nature of relaxation threshold values, we find the consistency of relaxed subsets defined by the different metrics to be relatively poor. Therefore, the use of relaxed cluster subsets introduces significant selection effects that are non-trivial to resolve.
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