On the formation of dwarf galaxies and stellar halos

Using analytic arguments and a suite of very high resolution (10^3 Msun per particle) cosmological hydro-dynamical simulations, we argue that high redshift, z ~ 10, M ~ 10^8 Msun halos, form the smallest `baryonic building block' (BBB) for galaxy formation. These halos are just massive enough to efficiently form stars through atomic line cooling and to hold onto their gas in the presence of supernovae winds and reionisation. These combined effects, in particular that of the supernovae feedback, create a sharp transition: over the mass range 3-10x10^7 Msun, the BBBs drop two orders ofmagnitude in stellar mass. Below ~2x10^7 Msun, galaxies will be dark with almost no stars and no gas. Above this scale is the smallest unit of galaxy formation: the BBB. A small fraction (~100) of these gas rich BBBs fall in to a galaxy the size of the Milky Way. Ten percent of these survive to become the observed LG dwarf galaxies at the present epoch. Those in-falling halos on benign orbits which keep them far away from the Milky Way or Andromeda manage to retain their gas and slowly form stars - these become the smallest dwarf irregular galax ies; those on more severe orbits lose their gas faster than they can form stars and become the dwarf spheroidals. The remaining 90% of the BBBs will be accreted. We show that this gives a metallicity and total stellar mass consistent with the Milky Way old stellar halo (abridged).Comment: 15 pages, 7 figures, one figure added to match accepted version. Some typos fixed. MNRAS in pres

Cosmological N-body simulations with suppressed variance

We present and test a method that dramatically reduces variance arising from the sparse sampling of wavemodes in cosmological simulations. The method uses two simulations which are fixed (the initial Fourier mode amplitudes are fixed to the ensemble average power spectrum) and paired (with initial modes exactly out of phase). We measure the power spectrum, monopole and quadrupole redshift-space correlation functions, halo mass function and reduced bispectrum at $z=1$. By these measures, predictions from a fixed pair can be as precise on non-linear scales as an average over 50 traditional simulations. The fixing procedure introduces a non-Gaussian correction to the initial conditions; we give an analytic argument showing why the simulations are still able to predict the mean properties of the Gaussian ensemble. We anticipate that the method will drive down the computational time requirements for accurate large-scale explorations of galaxy bias and clustering statistics, enabling more precise comparisons with theoretical models, and facilitating the use of numerical simulations in cosmological data interpretation

Quadratic genetic modifications: a streamlined route to cosmological simulations with controlled merger history

Recent work has studied the interplay between a galaxy's history and its observable properties using ‘genetically modified’ cosmological zoom simulations. The approach systematically generates alternative histories for a halo, while keeping its cosmological environment fixed. Applications to date altered linear properties of the initial conditions, such as the mean overdensity of specified regions; we extend the formulation to include quadratic features, such as local variance, that determines the overall importance of smooth accretion relative to mergers in a galaxy's history. We introduce an efficient algorithm for this new class of modification and demonstrate its ability to control the variance of a region in a one-dimensional toy model. Outcomes of this work are twofold: (i) a clarification of the formulation of genetic modifications and (ii) a proof of concept for quadratic modifications leading the way to a forthcoming implementation in cosmological simulations

How to build a catalogue of linearly evolving cosmic voids

Cosmic voids provide a powerful probe of the origin and evolution of structures in the Universe because their dynamics can remain near-linear to the present day. As a result, they have the potential to connect large-scale structure at late times to early Universe physics. Existing ‘watershed’-based algorithms, however, define voids in terms of their morphological properties at low redshift. The degree to which the resulting regions exhibit linear dynamics is consequently uncertain, and there is no direct connection to their evolution from the initial density field. A recent void definition addresses these issues by considering ‘anti-haloes’. This approach consists of inverting the initial conditions of an N-body simulation to swap overdensities and underdensities. After evolving the pair of initial conditions, anti-haloes are defined by the particles within the inverted simulation that are inside haloes in the original (uninverted) simulation. In this work, we quantify the degree of non-linearity of both anti-haloes and watershed voids using the Zel’dovich approximation. We find that non-linearities are introduced by voids with radii less than 5Mpch−1⁠, and that both anti-haloes and watershed voids can be made into highly linear sets by removing these voids

Genetically modified haloes: towards controlled experiments in ΛCDM galaxy formation

We propose a method to generate ‘genetically modified’ (GM) initial conditions for high-resolution simulations of galaxy formation in a cosmological context. Building on the Hoffman–Ribak algorithm, we start from a reference simulation with fully random initial conditions, then make controlled changes to specific properties of a single halo (such as its mass and merger history). The algorithm demonstrably makes minimal changes to other properties of the halo and its environment, allowing us to isolate the impact of a given modification. As a significant improvement over previous work, we are able to calculate the abundance of the resulting objects relative to the reference simulation. Our approach can be applied to a wide range of cosmic structures and epochs; here we study two problems as a proof of concept. First, we investigate the change in density profile and concentration as the collapse times of three individual haloes are varied at fixed final mass, showing good agreement with previous statistical studies using large simulation suites. Secondly, we modify the z = 0 mass of haloes to show that our theoretical abundance calculations correctly recover the halo mass function. The results demonstrate that the technique is robust, opening the way to controlled experiments in galaxy formation using hydrodynamic zoom simulations

Angular momentum evolution can be predicted from cosmological initial conditions

The angular momentum of dark matter haloes controls their spin magnitude and orientation, which in turn influences the galaxies therein. However, the process by which dark matter haloes acquire angular momentum is not fully understood; in particular, it is unclear whether angular momentum growth is stochastic. To address this question, we extend the genetic modification technique to allow control over the angular momentum of any region in the initial conditions. Using this technique to produce a sequence of modified simulations, we can then investigate whether changes to the angular momentum of a specified region in the evolved universe can be accurately predicted from changes in the initial conditions alone. We find that the angular momentum in regions with modified initial conditions can be predicted between 2 and 4 times more accurately than expected from applying tidal torque theory. This result is masked when analysing the angular momentum of haloes, because particles in the outskirts of haloes dominate the angular momentum budget. We conclude that the angular momentum of Lagrangian patches is highly predictable from the initial conditions, with apparent chaotic behaviour being driven by stochastic changes to the arbitrary boundary defining the halo

Inverted initial conditions: Exploring the growth of cosmic structure and voids

We introduce and explore "paired" cosmological simulations. A pair consists of an A and B simulation with initial conditions related by the inversion δAðx; tinitialÞ ¼ −δBðx; tinitialÞ (underdensities substituted for overdensities and vice versa). We argue that the technique is valuable for improving our understanding of cosmic structure formation. The A and B fields are by definition equally likely draws from ΛCDM initial conditions, and in the linear regime evolve identically up to the overall sign. As nonlinear evolution takes hold, a region that collapses to form a halo in simulation A will tend to expand to create a void in simulation B. Applications include (i) contrasting the growth of A-halos and B-voids to test excursion-set theories of structure formation, (ii) cross-correlating the density field of the A and B universes as a novel test for perturbation theory, and (iii) canceling error terms by averaging power spectra between the two boxes. Generalizations of the method to more elaborate field transformations are suggested

Quenching and morphological evolution due to circumgalactic gas expulsion in a simulated galaxy with a controlled assembly history

We examine the influence of dark matter halo assembly on the evolution of a simulated ∼L⋆ galaxy. Starting from a zoom-in simulation of a star-forming galaxy evolved with the EAGLE galaxy formation model, we use the genetic modification technique to create a pair of complementary assembly histories: one in which the halo assembles later than in the unmodified case, and one in which it assembles earlier. Delayed assembly leads to the galaxy exhibiting a greater present-day star formation rate than its unmodified counterpart, while in the accelerated case the galaxy quenches at z ≃ 1, and becomes spheroidal. We simulate each assembly history nine times, adopting different seeds for the random number generator used by EAGLE’s stochastic subgrid implementations of star formation and feedback. The systematic changes driven by differences in assembly history are significantly stronger than the random scatter induced by this stochasticity. The sensitivity of ∼L⋆ galaxy evolution to dark matter halo assembly follows from the close coupling of the growth histories of the central black hole (BH) and the halo, such that earlier assembly fosters the formation of a more massive BH, and more efficient expulsion of circumgalactic gas. In response to this expulsion, the circumgalactic medium reconfigures at a lower density, extending its cooling time and thus inhibiting the replenishment of the interstellar medium. Our results indicate that halo assembly history significantly influences the evolution of ∼L⋆ central galaxies, and that the expulsion of circumgalactic gas is a crucial step in quenching them

An interpretable machine learning framework for dark matter halo formation

We present a generalization of our recently proposed machine-learning framework, aiming to provide new physical insights into dark matter halo formation. We investigate the impact of the initial density and tidal shear fields on the formation of haloes over the mass range 11.4 ≤ log (M/M⊙) ≤ 13.4. The algorithm is trained on an N-body simulation to infer the final mass of the halo to which each dark matter particle will later belong. We then quantify the difference in the predictive accuracy between machine-learning models using a metric based on the Kullback–Leibler divergence. We first train the algorithm with information about the density contrast in the particles’ local environment. The addition of tidal shear information does not yield an improved halo collapse model over one based on density information alone; the difference in their predictive performance is consistent with the statistical uncertainty of the density-only based model. This result is confirmed as we verify the ability of the initial conditions-to-halo mass mapping learnt from one simulation to generalize to independent simulations. Our work illustrates the broader potential of developing interpretable machine-learning frameworks to gain physical understanding of non-linear large-scale structure formation

The cosmic abundance of cold gas in the local Universe

We determine the cosmic abundance of molecular hydrogen (H2) in the local universe from the xCOLD GASS survey. To constrain the H2 mass function at low masses and correct for the effect of the lower stellar mass limit of 10^9 Msun in the xCOLD GASS survey, we use an empirical approach based on an observed scaling relation between star formation rate and gas mass. We also constrain the HI and HI+H2 mass functions using the xGASS survey, and compare it to the HI mass function from the ALFALFA survey. We find the cosmic abundance of molecular gas in the local Universe to be Omega_H2=(5.34+/-0.47)x10^-5 h^-1. Molecular gas accounts for 19.6 +/- 3.9% of the total abundance of cold gas, Omega_HI+H2=(4.66+/-0.70)x10^-4 h^-1. Galaxies with stellar masses in excess of 10^9 Msun account for 89% of the molecular gas in the local Universe, while in comparison such galaxies only contain 73% of the cold atomic gas as traced by the HI 21cm line. The xCOLD GASS CO, molecular gas and cold gas mass functions and Omega_H2 measurements provide constraints for models of galaxy evolution and help to anchor blind ALMA and NOEMA surveys attempting to determine the abundance of molecular gas at high redshifts