The impact of baryonic processes on the two-point correlation functions of galaxies, subhaloes and matter

The observed clustering of galaxies and the cross-correlation of galaxies and mass provide important constraints on both cosmology and models of galaxy formation. Even though the dissipation and feedback processes associated with galaxy formation are thought to affect the distribution of matter, essentially all models used to predict clustering data are based on collisionless simulations. Here, we use large hydrodynamical simulations to investigate how galaxy formation affects the autocorrelation functions of galaxies and subhaloes, as well as their cross-correlation with matter. We show that the changes due to the inclusion of baryons are not limited to small scales and are even present in samples selected by subhalo mass. Samples selected by subhalo mass cluster ~10% more strongly in a baryonic run on scales r > 1Mpc/h, and this difference increases for smaller separations. While the inclusion of baryons boosts the clustering at fixed subhalo mass on all scales, the sign of the effect on the cross-correlation of subhaloes with matter can vary with radius. We show that the large-scale effects are due to the change in subhalo mass caused by the strong feedback associated with galaxy formation and may therefore not affect samples selected by number density. However, on scales r < r_vir significant differences remain after accounting for the change in subhalo mass. We conclude that predictions for galaxy-galaxy and galaxy-mass clustering from models based on collisionless simulations will have errors greater than 10% on sub-Mpc scales, unless the simulation results are modified to correctly account for the effects of baryons on the distributions of mass and satellites.Comment: 15 pages, 9 figures. Replaced to match the version accepted by MNRA

Age × stage-classified demographic analysis: a comprehensive approach

This paper presents a comprehensive theory for the demographic analysis of populations in which individuals are classified by both age and stage. The earliest demographic models were age classified. Ecologists adopted methods developed by human demographers and used life tables to quantify survivorship and fertility of cohorts and the growth rates and structures of populations. Later, motivated by studies of plants and insects, matrix population models structured by size or stage were developed. The theory of these models has been extended to cover all the aspects of age‐classified demography and more. It is a natural development to consider populations classified by both age and stage. A steady trickle of results has appeared since the 1960s, analyzing one or another aspect of age × stage‐classified populations, in both ecology and human demography. Here, we use the vec‐permutation formulation of multistate matrix population models to incorporate age‐ and stage‐specific vital rates into demographic analysis. We present cohort results for the life table functions (survivorship, mortality, and fertility), the dynamics of intra‐cohort selection, the statistics of longevity, the joint distribution of age and stage at death, and the statistics of life disparity. Combining transitions and fertility yields a complete set of population dynamic results, including population growth rates and structures, net reproductive rate, the statistics of lifetime reproduction, and measures of generation time. We present a complete analysis of a hypothetical model species, inspired by poecilogonous marine invertebrates that produce two kinds of larval offspring. Given the joint effects of age and stage, many familiar demographic results become multidimensional, so calculations of marginal and mixture distributions are an important tool. From an age‐classified point of view, stage structure is a form of unobserved heterogeneity. From a stage‐classified point of view, age structure is unobserved heterogeneity. In an age × stage‐classified model, variance in demographic outcomes can be partitioned into contributions from both sources. Because these models are formulated as matrices, they are amenable to a complete sensitivity analysis. As more detailed and longer longitudinal studies are developed, age × stage‐classified demography will become more common and more important

The contributions of maternal age heterogeneity to variance in lifetime reproductive output

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in van Daalen, S. F., Hernandez, C. M., Caswell, H., Neubert, M. G., & Gribble, K. E. The contributions of maternal age heterogeneity to variance in lifetime reproductive output. American Naturalist,199(5), (2022): 603-616, https://doi.org/10.1086/718716.Variance among individuals in fitness components reflects both genuine heterogeneity between individuals and stochasticity in events experienced along the life cycle. Maternal age represents a form of heterogeneity that affects both the mean and the variance of lifetime reproductive output (LRO). Here, we quantify the relative contribution of maternal age heterogeneity to the variance in LRO using individual-level laboratory data on the rotifer Brachionus manjavacas to parameterize a multistate age × maternal age matrix model. In B. manjavacas, advanced maternal age has large negative effects on offspring survival and fertility. We used multistate Markov chains with rewards to quantify the contributions to variance in LRO of heterogeneity and of the stochasticity inherent in the outcomes of probabilistic transitions and reproductive events. Under laboratory conditions, maternal age heterogeneity contributes 26% of the variance in LRO. The contribution changes when mortality and fertility are reduced to mimic more ecologically relevant environments. Over the parameter space where populations are near stationarity, maternal age heterogeneity contributes an average of 3% of the variance. Thus, the contributions of maternal age heterogeneity and individual stochasticity can be expected to depend strongly on environmental conditions; over most of the parameter space, the variance in LRO is dominated by stochasticity.K.E.G. was supported by grant 5K01AG049049 from the National Institute on Aging, by National Science Foundation (NSF) CAREER grant IOS-1942606, and by the Bay and Paul Foundations. H.C. and S.F.v.D. were supported by the European Research Council through Advanced Grants 322829 and 788195 and by the Dutch Research Council through grant ALWOP.2015.100. S.F.v.D. was furthermore supported by the Postdoctoral Scholar Program at Woods Hole Oceanographic Institution, with funding provided by the Doherty Foundation. C.M.H. was supported by an NSF Graduate Research Fellowship. M.G.N. received funding from the Paul MacDonald Fye Chair for Excellence in Oceanography at the Woods Hole Oceanographic Institution

Tomographic weak lensing shear spectra from large N-body and hydrodynamical simulations

Forthcoming experiments will enable us to determine tomographic shear spectra at a high precision level. Most predictions about them have until now been biased on algorithms yielding the expected linear and non-linear spectrum of density fluctuations. Even when simulations have been used, so-called Halofit (Smith et al 2003) predictions on fairly large scales have been needed. We wish to go beyond this limitation. We perform N-body and hydrodynamical simulations within a sufficiently large cosmological volume to allow a direct connection between simulations and linear spectra. While covering large length-scales, the simulation resolution is good enough to allow us to explore the high-l harmonics of the cosmic shear (up to l ~ 50000), well into the domain where baryon physics becomes important. We then compare shear spectra in the absence and in presence of various kinds of baryon physics, such as radiative cooling, star formation, and supernova feedback in the form of galactic winds. We distinguish several typical properties of matter fluctuation spectra in the different simulations and test their impact on shear spectra. We compare our outputs with those obtainable using approximate expressions for non--linear spectra, and identify substantial discrepancies even between our results and those of purely N-body results. Our simulations and the treatment of their outputs however enable us, for the first time, to obtain shear results taht are fully independent of any approximate expression, also in the high-l range, where we need to incorporate a non-linear power spectrum of density perturbations, and the effects of baryon physics. This will allow us to fully exploit the cosmological information contained in future high--sensitivity cosmic shear surveys, exploring the physics of cosmic shears via weak lensing measurements.Comment: 13 pages, 19 figures, A&A in pres