22 research outputs found

    The Milky Way's total satellite population and constraining the mass of the warm dark matter particle

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    The Milky Way’s (MW) satellite population is a powerful probe of warm dark matter (WDM) models as the abundance of small substructures is very sensitive to the properties of the WDM particle. However, only a partial census of the MW’s complement of satellite galaxies exists because surveys of the MW’s close environs are incomplete both in depth and in sky coverage. We present a new Bayesian analysis that combines the sample of satellites recently discovered by the Dark Energy Survey (DES) with those found in the Sloan Digital Sky Survey (SDSS) to estimate the total satellite galaxy luminosity function down to Mv = 0. We find that there should be at least 124+40−27124−27+40 (68% CL, statistical error) satellites as bright or brighter than Mv = 0 within 300 kpc of the Sun, with only a weak dependence on MW halo mass. When it comes online the Large Synoptic Survey Telescope should detect approximately half of this population. We also show that WDM models infer the same number of satellites as in ΛCDM, which will allow us to rule out those models that produce insufficient substructure to be viable

    The EAGLE simulations of galaxy formation: calibration of subgrid physics and model variations

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    We present results from thirteen cosmological simulations that explore the parameter space of the "Evolution and Assembly of GaLaxies and their Environments" (EAGLE) simulation project. Four of the simulations follow the evolution of a periodic cube L = 50 cMpc on a side, and each employs a different subgrid model of the energetic feedback associated with star formation. The relevant parameters were adjusted so that the simulations each reproduce the observed galaxy stellar mass function at z = 0.1. Three of the simulations fail to form disc galaxies as extended as observed, and we show analytically that this is a consequence of numerical radiative losses that reduce the efficiency of stellar feedback in high-density gas. Such losses are greatly reduced in the fourth simulation - the EAGLE reference model - by injecting more energy in higher density gas. This model produces galaxies with the observed size distribution, and also reproduces many galaxy scaling relations. In the remaining nine simulations, a single parameter or process of the reference model was varied at a time. We find that the properties of galaxies with stellar mass <~ M* (the "knee" of the galaxy stellar mass function) are largely governed by feedback associated with star formation, while those of more massive galaxies are also controlled by feedback from accretion onto their central black holes. Both processes must be efficient in order to reproduce the observed galaxy population. In general, simulations that have been calibrated to reproduce the low-redshift galaxy stellar mass function will still not form realistic galaxies, but the additional requirement that galaxy sizes be acceptable leads to agreement with a large range of observables

    Galaxies in the EAGLE hydrodynamical simulation and in the Durham and Munich semi-analytical models

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    We compare global predictions from the eagle hydrodynamical simulation, and two semi-analytic (SA) models of galaxy formation, l-galaxies and galform. All three models include the key physical processes for the formation and evolution of galaxies and their parameters are calibrated against a small number of observables at z ≈ 0. The two SA models have been applied to merger trees constructed from the eagle dark matter only simulation. We find that at z ≤ 2, both the galaxy stellar mass functions for stellar masses M* 109.5 M⊙ differ in some instances by an order of magnitude, while the stellar mass–size relation in eagle is a factor of ≈2 tighter than for the two SA models. Our results suggest the need for a revision of how SA models treat the effect of baryonic self-gravity on the underlying dark matter. The treatment of gas flows in the models needs to be revised based on detailed comparison with observations to understand in particular the evolution of the stellar mass–metallicity relation

    The APOSTLE simulations: solutions to the Local Group's cosmic puzzles

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    The Local Group of galaxies offer some of the most discriminating tests of models of cosmic structure formation. For example, observations of the Milky Way (MW) and Andromeda satellite populations appear to be in disagreement with N-body simulations of the "Lambda Cold Dark Matter" ({\Lambda}CDM) model: there are far fewer satellite galaxies than substructures in cold dark matter halos (the "missing satellites" problem); dwarf galaxies seem to avoid the most massive substructures (the "too-big-to-fail" problem); and the brightest satellites appear to orbit their host galaxies on a thin plane (the "planes of satellites" problem). Here we present results from APOSTLE (A Project Of Simulating The Local Environment), a suite of cosmological hydrodynamic simulations of twelve volumes selected to match the kinematics of the Local Group (LG) members. Applying the Eagle code to the LG environment, we find that our simulations match the observed abundance of LG galaxies, including the satellite galaxies of the MW and Andromeda. Due to changes to the structure of halos and the evolution in the LG environment, the simulations reproduce the observed relation between stellar mass and velocity dispersion of individual dwarf spheroidal galaxies without necessitating the formation of cores in their dark matter profiles. Satellite systems form with a range of spatial anisotropies, including one similar to that of the MW, confirming that such a configuration is not unexpected in {\Lambda}CDM. Finally, based on the observed velocity dispersion, size, and stellar mass, we provide new estimates of the maximum circular velocity for the halos of nine MW dwarf spheroidals

    The EAGLE simulation of galaxy formation: public release of halo and galaxy catalogues

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    We present the public data release of halo and galaxy catalogues extracted from the EAGLE suite of cosmological hydrodynamical simulations of galaxy formation. These simulations were performed with an enhanced version of the GADGET code that includes a modified hydrodynamics solver, time-step limiter and subgrid treatments of baryonic physics, such as stellar mass loss, element-by-element radiative cooling, star formation and feedback from star formation and black hole accretion. The simulation suite includes runs performed in volumes ranging from 25 to 100 comoving megaparsecs per side, with numerical resolution chosen to marginally resolve the Jeans mass of the gas at the star formation threshold. The free parameters of the subgrid models for feedback are calibrated to the redshift z=0 galaxy stellar mass function, galaxy sizes and black hole mass - stellar mass relation. The simulations have been shown to match a wide range of observations for present-day and higher-redshift galaxies. The raw particle data have been used to link galaxies across redshifts by creating merger trees. The indexing of the tree produces a simple way to connect a galaxy at one redshift to its progenitors at higher redshift and to identify its descendants at lower redshift. In this paper we present a relational database which we are making available for general use. A large number of properties of haloes and galaxies and their merger trees are stored in the database, including stellar masses, star formation rates, metallicities, photometric measurements and mock gri images. Complex queries can be created to explore the evolution of more than 10^5 galaxies, examples of which are provided in appendix. (abridged

    Marine Dynamics and Productivity in the Bay of Bengal

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    The Bay of Bengal provides important ecosystem services to the Bangladesh delta. It is also subject to the consequences of climate change as monsoon atmospheric circulation and fresh water input from the major rivers are the dominating influences. Changes in marine circulation will affect patterns of biological production through alterations in the supply of nutrients to photosynthesising plankton. Productivity in the northern Bay will also be sensitive to changes in riverborne nutrients. In turn, these changes could influence potential fish catch. The Bay also affects the physical environment of Bangladesh: relative sea-level rise is expected to be in the range of 0.5–1.7 m by 2100, and changing climate could affect the development of tropical cyclones over the Bay

    The FLAMINGO project: revisiting the S8 tension and the role of baryonic physics

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    A number of recent studies have found evidence for a tension between observations of large-scale structure (LSS) and the predictions of the standard model of cosmology with the cosmological parameters fit to the cosmic microwave background (CMB). The origin of this ‘S8 tension’ remains unclear, but possibilities include new physics beyond the standard model, unaccounted for systematic errors in the observational measurements and/or uncertainties in the role that baryons play. Here, we carefully examine the latter possibility using the new FLAMINGO suite of large-volume cosmological hydrodynamical simulations. We project the simulations onto observable harmonic space and compare with observational measurements of the power and cross-power spectra of cosmic shear, CMB lensing, and the thermal Sunyaev-Zel’dovich (tSZ) effect. We explore the dependence of the predictions on box size and resolution and cosmological parameters, including the neutrino mass, and the efficiency and nature of baryonic ‘feedback’. Despite the wide range of astrophysical behaviours simulated, we find that baryonic effects are not sufficiently large to remove the S8 tension. Consistent with recent studies, we find the CMB lensing power spectrum is in excellent agreement with the standard model, while the cosmic shear power spectrum, tSZ effect power spectrum, and the cross-spectra between shear, CMB lensing, and the tSZ effect are all in varying degrees of tension with the CMB-specified standard model. These results suggest that some mechanism is required to slow the growth of fluctuations at late times and/or on non-linear scales, but that it is unlikely that baryon physics is driving this modification

    FLAMINGO: calibrating large cosmological hydrodynamical simulations with machine learning

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    To fully take advantage of the data provided by large-scale structure surveys, we need to quantify the potential impact of baryonic effects, such as feedback from active galactic nuclei (AGN) and star formation, on cosmological observables. In simulations, feedback processes originate on scales that remain unresolved. Therefore, they need to be sourced via subgrid models that contain free parameters. We use machine learning to calibrate the AGN and stellar feedback models for the FLAMINGO (Fullhydro Large-scale structure simulations with All-sky Mapping for the Interpretation of Next Generation Observations) cosmological hydrodynamical simulations. Using Gaussian process emulators trained on Latin hypercubes of 32 smaller volume simulations, we model how the galaxy stellar mass function (SMF) and cluster gas fractions change as a function of the subgrid parameters. The emulators are then fit to observational data, allowing for the inclusion of potential observational biases. We apply our method to the three different FLAMINGO resolutions, spanning a factor of 64 in particle mass, recovering the observed relations within the respective resolved mass ranges. We also use the emulators, which link changes in subgrid parameters to changes in observables, to find models that skirt or exceed the observationally allowed range for cluster gas fractions and the SMF. Our method enables us to define model variations in terms of the data that they are calibrated to rather than the values of specific subgrid parameters. This approach is useful, because subgrid parameters are typically not directly linked to particular observables, and predictions for a specific observable are influenced by multiple subgrid parameters

    Coastal Upwelling Supplies Oxygen-Depleted Water to the Columbia River Estuary

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    Low dissolved oxygen (DO) is a common feature of many estuarine and shallow-water environments, and is often attributed to anthropogenic nutrient enrichment from terrestrial-fluvial pathways. However, recent events in the U.S. Pacific Northwest have highlighted that wind-forced upwelling can cause naturally occurring low DO water to move onto the continental shelf, leading to mortalities of benthic fish and invertebrates. Coastal estuaries in the Pacific Northwest are strongly linked to ocean forcings, and here we report observations on the spatial and temporal patterns of oxygen concentration in the Columbia River estuary. Hydrographic measurements were made from transect (spatial survey) or anchor station (temporal survey) deployments over a variety of wind stresses and tidal states during the upwelling seasons of 2006 through 2008. During this period, biologically stressful levels of dissolved oxygen were observed to enter the Columbia River estuary from oceanic sources, with minimum values close to the hypoxic threshold of 2.0 mg L−1. Riverine water was consistently normoxic. Upwelling wind stress controlled the timing and magnitude of low DO events, while tidal-modulated estuarine circulation patterns influenced the spatial extent and duration of exposure to low DO water. Strong upwelling during neap tides produced the largest impact on the estuary. The observed oxygen concentrations likely had deleterious behavioral and physiological consequences for migrating juvenile salmon and benthic crabs. Based on a wind-forced supply mechanism, low DO events are probably common to the Columbia River and other regional estuaries and if conditions on the shelf deteriorate further, as observations and models predict, Pacific Northwest estuarine habitats could experience a decrease in environmental quality
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