Large-scale fluctuations in the cosmic ionising background: the impact of beamed source emission

When modelling the ionisation of gas in the intergalactic medium after reionisation, it is standard practice to assume a uniform radiation background. This assumption is not always appropriate; models with radiative transfer show that large-scale ionisation rate fluctuations can have an observable impact on statistics of the Lyman-alpha forest. We extend such calculations to include beaming of sources, which has previously been neglected but which is expected to be important if quasars dominate the ionising photon budget. Beaming has two effects: first, the physical number density of ionising sources is enhanced relative to that directly observed; and second, the radiative transfer itself is altered. We calculate both effects in a hard-edged beaming model where each source has a random orientation, using an equilibrium Boltzmann hierarchy in terms of spherical harmonics. By studying the statistical properties of the resulting ionisation rate and HI density fields at redshift $z\sim 2.3$, we find that the two effects partially cancel each other; combined, they constitute a maximum $5\%$ correction to the power spectrum $P_{\mathrm{HI}}(k)$ at $k=0.04 \, h/\mathrm{Mpc}$. On very large scales ($k<0.01\, h/\mathrm{Mpc}$) the source density renormalisation dominates; it can reduce, by an order of magnitude, the contribution of ionising shot-noise to the intergalactic HI power spectrum. The effects of beaming should be considered when interpreting future observational datasets.Comment: 8 pages, 4 figure

Tangos: the agile numerical galaxy organization system

We present Tangos, a Python framework and web interface for database-driven analysis of numerical structure formation simulations. To understand the role that such a tool can play, consider constructing a history for the absolute magnitude of each galaxy within a simulation. The magnitudes must first be calculated for all halos at all timesteps and then linked using a merger tree; folding the required information into a final analysis can entail significant effort. Tangos is a generic solution to this information organization problem, aiming to free users from the details of data management. At the querying stage, our example of gathering properties over history is reduced to a few clicks or a simple, single-line Python command. The framework is highly extensible; in particular, users are expected to define their own properties which tangos will write into the database. A variety of parallelization options are available and the raw simulation data can be read using existing libraries such as pynbody or yt. Finally, tangos-based databases and analysis pipelines can easily be shared with collaborators or the broader community to ensure reproducibility. User documentation is provided separately.Comment: Clarified various points and further improved code performance; accepted for publication in ApJS. Tutorials (including video) at http://tiny.cc/tango

Genetically modified halos: towards controlled experiments in Λ\LambdaCDM 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 time of three individual halos are varied at fixed final mass, showing good agreement with previous statistical studies using large simulation suites. Second, we modify the $z=0$ mass of halos 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.Comment: Version accepted by MNRAS; 13 pages, 6 Figures, comments still welcom

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 $\delta_A(x, t_{initial})=-\delta_B(x,t_{initial})$ (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 {\Lambda}CDM initial conditions, and in the linear regime evolve identically up to the overall sign. As non-linear 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.Comment: 10 pages (including appendix), 6 figures. To be submitted to PR

Avoiding bias in reconstructing the largest observable scales from partial-sky data

Obscuration due to Galactic emission complicates the extraction of information from cosmological surveys, and requires some combination of the (typically imperfect) modeling and subtraction of foregrounds, or the removal of part of the sky. This particularly affects the extraction of information from the largest observable scales. Maximum-likelihood estimators for reconstructing the full-sky spherical harmonic coefficients from partial-sky maps have recently been shown to be susceptible to contamination from within the sky cut, arising due to the necessity to band-limit the data by smoothing prior to reconstruction. Using the WMAP 7-year data, we investigate modified implementations of such estimators which are robust to the leakage of contaminants from within masked regions. We provide a measure, based on the expected amplitude of residual foregrounds, for selecting the most appropriate estimator for the task at hand. We explain why the related quadratic maximum-likelihood estimator of the angular power spectrum does not suffer from smoothing-induced bias.Comment: 8 pages, 8 figures. v2: replaced with version accepted by PRD (minor amendments to text only

Machine learning cosmological structure formation

We train a machine learning algorithm to learn cosmological structure formation from N-body simulations. The algorithm infers the relationship between the initial conditions and the final dark matter haloes, without the need to introduce approximate halo collapse models. We gain insights into the physics driving halo formation by evaluating the predictive performance of the algorithm when provided with different types of information about the local environment around dark matter particles. The algorithm learns to predict whether or not dark matter particles will end up in haloes of a given mass range, based on spherical overdensities. We show that the resulting predictions match those of spherical collapse approximations such as extended Press-Schechter theory. Additional information on the shape of the local gravitational potential is not able to improve halo collapse predictions; the linear density field contains sufficient information for the algorithm to also reproduce ellipsoidal collapse predictions based on the Sheth-Tormen model. We investigate the algorithm's performance in terms of halo mass and radial position and perform blind analyses on independent initial conditions realisations to demonstrate the generality of our results.Comment: 10 pages, 7 figures. Minor changes to match version published in MNRAS. Accepted on 22/06/201

Dancing to ChaNGa: A Self-Consistent Prediction For Close SMBH Pair Formation Timescales Following Galaxy Mergers

We present the first self-consistent prediction for the distribution of formation timescales for close Supermassive Black Hole (SMBH) pairs following galaxy mergers. Using ROMULUS25, the first large-scale cosmological simulation to accurately track the orbital evolution of SMBHs within their host galaxies down to sub-kpc scales, we predict an average formation rate density of close SMBH pairs of 0.013 cMpc^-3 Gyr^-1. We find that it is relatively rare for galaxy mergers to result in the formation of close SMBH pairs with sub-kpc separation and those that do form are often the result of Gyrs of orbital evolution following the galaxy merger. The likelihood and timescale to form a close SMBH pair depends strongly on the mass ratio of the merging galaxies, as well as the presence of dense stellar cores. Low stellar mass ratio mergers with galaxies that lack a dense stellar core are more likely to become tidally disrupted and deposit their SMBH at large radii without any stellar core to aid in their orbital decay, resulting in a population of long-lived 'wandering' SMBHs. Conversely, SMBHs in galaxies that remain embedded within a stellar core form close pairs in much shorter timescales on average. This timescale is a crucial, though often ignored or very simplified, ingredient to models predicting SMBH mergers rates and the connection between SMBH and star formation activity.Comment: 11 pages, 7 figures, accepted for publication in MNRA