STROOPWAFEL: Simulating rare outcomes from astrophysical populations, with application to gravitational-wave sources

Gravitational-wave observations of double compact object (DCO) mergers are providing new insights into the physics of massive stars and the evolution of binary systems. Making the most of expected near-future observations for understanding stellar physics will rely on comparisons with binary population synthesis models. However, the vast majority of simulated binaries never produce DCOs, which makes calculating such populations computationally inefficient. We present an importance sampling algorithm, STROOPWAFEL, that improves the computational efficiency of population studies of rare events, by focusing the simulation around regions of the initial parameter space found to produce outputs of interest. We implement the algorithm in the binary population synthesis code COMPAS, and compare the efficiency of our implementation to the standard method of Monte Carlo sampling from the birth probability distributions. STROOPWAFEL finds $\sim$25-200 times more DCO mergers than the standard sampling method with the same simulation size, and so speeds up simulations by up to two orders of magnitude. Finding more DCO mergers automatically maps the parameter space with far higher resolution than when using the traditional sampling. This increase in efficiency also leads to a decrease of a factor $\sim$3-10 in statistical sampling uncertainty for the predictions from the simulations. This is particularly notable for the distribution functions of observable quantities such as the black hole and neutron star chirp mass distribution, including in the tails of the distribution functions where predictions using standard sampling can be dominated by sampling noise.Comment: Accepted. Data and scripts to reproduce main results is publicly available. The code for the STROOPWAFEL algorithm will be made publicly available. Early inquiries can be addressed to the lead autho

Validating Semi-Analytic Models of High-Redshift Galaxy Formation using Radiation Hydrodynamical Simulations

We use a cosmological hydrodynamic simulation calculated with Enzo and the semi-analytic galaxy formation model (SAM) GAMMA to address the chemical evolution of dwarf galaxies in the early universe. The long-term goal of the project is to better understand the origin of metal-poor stars and the formation of dwarf galaxies and the Milky Way halo by cross-validating these theoretical approaches. We combine GAMMA with the merger tree of the most massive galaxy found in the hydrodynamic simulation and compare the star formation rate, the metallicity distribution function (MDF), and the age-metallicity relationship predicted by the two approaches. We found that the SAM can reproduce the global trends of the hydrodynamic simulation. However, there are degeneracies between the model parameters and more constraints (e.g., star formation efficiency, gas flows) need to be extracted from the simulation to isolate the correct semi-analytic solution. Stochastic processes such as bursty star formation histories and star formation triggered by supernova explosions cannot be reproduced by the current version of GAMMA. Non-uniform mixing in the galaxy's interstellar medium, coming primarily from self-enrichment by local supernovae, causes a broadening in the MDF that can be emulated in the SAM by convolving its predicted MDF with a Gaussian function having a standard deviation of ~0.2 dex. We found that the most massive galaxy in the simulation retains nearby 100% of its baryonic mass within its virial radius, which is in agreement with what is needed in GAMMA to reproduce the global trends of the simulation.Comment: 26 pages, 13 figures, 2 tables, submitted to ApJ (version 2

The formation of compact massive self-gravitating discs in metal-free haloes with virial temperatures of ~ 13000-30000 K

We have used the hydrodynamical AMR code ENZO to investigate the dynamical evolution of the gas at the centre of dark matter haloes with virial velocities of ~ 20 - 30 kms and virial temperatures of ~ 13000-30000 K at z ~ 15 in a cosmological context. The virial temperature of the dark matter haloes is above the threshold where atomic cooling by hydrogen allows the gas to cool and collapse. We neglect cooling by molecular hydrogen and metals, as may be plausible if H_2 cooling is suppressed by a meta-galactic Lyman-Werner background or an internal source of Lyman-Werner photons, and metal enrichment has not progressed very far. The gas in the haloes becomes gravitationally unstable and develops turbulent velocities comparable to the virial velocities of the dark matter haloes. Within a few dynamical times it settles into a nearly isothermal density profile over many decades in radius losing most of its angular momentum in the process. About 0.1 - 1 % of the baryons, at the centre of the dark matter haloes, collapse into a self-gravitating, fat, ellipsoidal, centrifugally supported exponential disc with scale-length of ~ 0.075-0.27 pc and rotation velocities of 25-60 kms. We are able to follow the settling of the gas into centrifugal support and the dynamical evolution of the compact disc in each dark matter halo for a few dynamical times. The dynamical evolution of the gas at the centre of the haloes is complex. In one of the haloes the gas at the centre fragments into a triple system leading to strong tidal perturbations and eventually to the in-fall of a secondary smaller clump into the most massive primary clump. The formation of centrifugally supported self-gravitating massive discs is likely to be an important intermediary stage en route to the formation of a massive black hole seed.Comment: Re-submitted to MNRAS taking into account the referee's suggestions for moderate revision. 16 pages, 11 figure

A Multi-Code Analysis Toolkit for Astrophysical Simulation Data

The analysis of complex multiphysics astrophysical simulations presents a unique and rapidly growing set of challenges: reproducibility, parallelization, and vast increases in data size and complexity chief among them. In order to meet these challenges, and in order to open up new avenues for collaboration between users of multiple simulation platforms, we present yt (available at http://yt.enzotools.org/), an open source, community-developed astrophysical analysis and visualization toolkit. Analysis and visualization with yt are oriented around physically relevant quantities rather than quantities native to astrophysical simulation codes. While originally designed for handling Enzo's structure adaptive mesh refinement (AMR) data, yt has been extended to work with several different simulation methods and simulation codes including Orion, RAMSES, and FLASH. We report on its methods for reading, handling, and visualizing data, including projections, multivariate volume rendering, multi-dimensional histograms, halo finding, light cone generation and topologically-connected isocontour identification. Furthermore, we discuss the underlying algorithms yt uses for processing and visualizing data, and its mechanisms for parallelization of analysis tasks.Comment: 18 pages, 6 figures, emulateapj format. Resubmitted to Astrophysical Journal Supplement Series with revisions from referee. yt can be found at http://yt.enzotools.org