The majority of galactic baryons resides outside of the galactic disk in the diffuse gas known as the circumgalactic medium (CGM). While state-of-the art simulations excel at reproducing galactic ...disk properties, many of them struggle to drive strong galactic winds or to match the observed ionization structure of the CGM using only thermal supernova feedback. To remedy this, recent studies have invoked nonthermal cosmic ray (CR) stellar feedback prescriptions. However, numerical schemes of CR transport are still poorly constrained. We explore how the choice of CR transport affects the multiphase structure of the simulated CGM. We implement anisotropic CR physics in the astrophysical simulation code Enzo and simulate a suite of isolated disk galaxies with varying prescriptions for CR transport: isotropic diffusion, anisotropic diffusion, and streaming. We find that all three transport mechanisms result in strong, metal-rich outflows but differ in the temperature and ionization structure of their CGM. Isotropic diffusion results in a spatially uniform, warm CGM that underpredicts the column densities of low ions. Anisotropic diffusion develops a reservoir of cool gas that extends farther from the galactic center, but disperses rapidly with distance. CR streaming projects cool gas out to radii of 200 kpc, supporting a truly multiphase medium. In addition, we find that streaming is less sensitive to changes in constant parameter values like the CR injection fraction, transport velocity, and resolution than diffusion. We conclude that CR streaming is a more robust implementation of CR transport and motivates the need for detailed parameter studies of CR transport.
We present results from the "Mint" resolution DC Justice League suite of Milky Way-like zoom-in cosmological simulations, which extend our study of nearby galaxies down into the ultrafaint dwarf ...(UFD) regime for the first time. The mass resolution of these simulations is the highest ever published for cosmological Milky Way zoom-in simulations run to z = 0, with initial star (dark matter) particle masses of 994 (17900) M , and a force resolution of 87 pc. We study the surrounding dwarfs and UFDs, and find that the simulations match the observed dynamical properties of galaxies with −3 > MV > −19, and reproduce the scatter seen in the size-luminosity plane for rh 200 pc. We predict the vast majority of nearby galaxies will be observable by the Vera Rubin Observatory's coadded Legacy Survey of Space and Time. We additionally show that faint dwarfs with velocity dispersions 5 km s−1 result from severe tidal stripping of the host halo. We investigate the quenching of UFDs in a hydrodynamical Milky Way context and find that the majority of UFDs are quenched prior to interactions with the Milky Way, though some of the quenched UFDs retain their gas until infall. Additionally, these simulations yield some unique dwarfs that are the first of their kind to be simulated, e.g., an H i-rich field UFD, a late-forming UFD that has structural properties similar to Crater 2, as well as a compact dwarf satellite that has no dark matter at z = 0.
We present a self-consistent prediction from a large-scale cosmological simulation for the population of "wandering" supermassive black holes (SMBHs) of mass greater than 106 M on long-lived, ...kpc-scale orbits within Milky Way (MW)-mass galaxies. We extract a sample of MW-mass halos from the Romulus25 cosmological simulation, which is uniquely able to capture the orbital evolution of SMBHs during and following galaxy mergers. We predict that such halos, regardless of recent merger history or morphology, host an average of 5.1 3.3 SMBHs, including their central black hole, within 10 kpc from the galactic center and an average of 12.2 8.4 SMBHs total within their virial radius, not counting those in satellite halos. Wandering SMBHs exist within their host galaxies for several Gyr, often accreted by their host halo in the early Universe. We find, with >4 significance, that wandering SMBHs are preferentially found outside of galactic disks.
Quantifying global soil respiration (RSG) and its response to temperature change are critical for predicting the turnover of terrestrial carbon stocks and their feedbacks to climate change. ...Currently, estimates of RSG range from 68 to 98 Pg C year−1, causing considerable uncertainty in the global carbon budget. We argue the source of this variability lies in the upscaling assumptions regarding the model format, data timescales, and precipitation component. To quantify the variability and constrain RSG, we developed RSG models using Random Forest and exponential models, and used different timescales (daily, monthly, and annual) of soil respiration (RS) and climate data to predict RSG. From the resulting RSG estimates (range = 66.62–100.72 Pg), we calculated variability associated with each assumption. Among model formats, using monthly RS data rather than annual data decreased RSG by 7.43–9.46 Pg; however, RSG calculated from daily RS data was only 1.83 Pg lower than the RSG from monthly data. Using mean annual precipitation and temperature data instead of monthly data caused +4.84 and −4.36 Pg C differences, respectively. If the timescale of RS data is constant, RSG estimated by the first‐order exponential (93.2 Pg) was greater than the Random Forest (78.76 Pg) or second‐order exponential (76.18 Pg) estimates. These results highlight the importance of variation at subannual timescales for upscaling to RSG. The results indicated RSG is lower than in recent papers and the current benchmark for land models (98 Pg C year−1), and thus may change the predicted rates of terrestrial carbon turnover and the carbon to climate feedback as global temperatures rise.
Quantifying different sources of variability in global soil respiration estimates helped to constrain soil respiration projections. We developed global soil respiration models using Random Forest and exponential models and used different timescales (daily, monthly, and annual) of soil respiration and climate data to predict global soil respiration. We found global soil respiration is closer to 70‐81 Pg C yr‐1. These results highlight the need for understanding and capturing the relevant timescale for upscaling fine‐scale temporal measures to broad‐scale global flux estimates. Assuming a lower global soil respiration could substantially change the carbon‐climate feedback under global warming.
Abstract
Formation models in which terrestrial bodies grow via the pairwise accretion of planetesimals have been reasonably successful at reproducing the general properties of the Solar System, ...including small-body populations. However, planetesimal accretion has not yet been fully explored in the context of the wide variety of recently discovered extrasolar planetary systems, in particular those that host short-period terrestrial planets. In this work, we use direct
N
-body simulations to explore and understand the growth of planetary embryos from planetesimals in disks extending down to ≃1 day orbital periods. We show that planetesimal accretion becomes nearly 100% efficient at short orbital periods, leading to embryo masses that are much larger than the classical isolation mass. For rocky bodies, the physical size of the object begins to occupy a significant fraction of its Hill sphere toward the inner edge of the disk. In this regime, most close encounters result in collisions, rather than scattering, and the system does not develop a bimodal population of dynamically hot planetesimals and dynamically cold oligarchs, as is seen in previous studies. The highly efficient accretion seen at short orbital periods implies that systems of tightly packed inner planets should be almost completely devoid of any residual small bodies. We demonstrate the robustness of our results to assumptions about the initial disk model, and we also investigate the effects that our simplified collision model has on the emergence of this non-oligarchic growth mode in a planet-forming disk.
Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem ...manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.
Abstract
The orbital decay of a perturber within a larger system plays a key role in the dynamics of many astrophysical systems—from nuclear star clusters or globular clusters in galaxies, to massive ...black holes in galactic nuclei, to dwarf galaxy satellites within the dark matter halos of more massive galaxies. For many decades, there have been various attempts to determine the underlying physics and timescales of the drag mechanism, ranging from the local dynamical friction approach to descriptions based on the back-reaction of global modes induced in the background system. We present ultra-high-resolution
N
-body simulations of massive satellites orbiting a Milky Way-like galaxy (with > 10
8
particles), that appear to capture both the local
“wake”
and the global
“mode”
induced in the primary halo. We address directly the mechanism of orbital decay from the combined action of local and global perturbations and specifically analyze where the bulk of the torque originates.
ABSTRACT
Cosmological simulations are reaching the resolution necessary to study ultra-faint dwarf galaxies. Observations indicate that in small populations, the stellar initial mass function (IMF) ...is not fully populated; rather, stars are sampled in a way that can be approximated as coming from an underlying probability density function. To ensure the accuracy of cosmological simulations in the ultra-faint regime, we present an improved treatment of the IMF. We implement a self-consistent, stochastically populated IMF in cosmological hydrodynamic simulations. We test our method using high-resolution simulations of a Milky Way halo, run to z = 6, yielding a sample of nearly 100 galaxies. We also use an isolated dwarf galaxy to investigate the resulting systematic differences in galaxy properties. We find that a stochastic IMF in simulations makes feedback burstier, strengthening feedback, and quenching star formation earlier in small dwarf galaxies. For galaxies in haloes with mass ≲ 108.5 M⊙, a stochastic IMF typically leads to lower stellar mass compared to a continuous IMF, sometimes by more than an order of magnitude. We show that existing methods of ensuring discrete supernovae incorrectly determine the mass of the star particle and its associated feedback. This leads to overcooling of surrounding gas, with at least ∼10 per cent higher star formation and ∼30 per cent higher cold gas content. Going forwards, to accurately model dwarf galaxies and compare to observations, it will be necessary to incorporate a stochastically populated IMF that samples the full spectrum of stellar masses.
PDF
