Search

We analyze high-resolution hydrodynamics simulations of an isolated disk dwarf galaxy with an explicit model for unresolved turbulence and turbulence-based star formation prescription. We examine the characteristic values of the star formation efficiency per free-fall time, $\epsilon_\mathrm{ff}$, and its variations with local environment properties, such as metallicity, UV flux, and surface density. We show that the star formation efficiency per free-fall time in $\approx 10$ pc star-forming regions of the simulated disks has values in the range $\epsilon_\mathrm{ff}\approx 0.01-0.1$, similar to observational estimates, with no trend with metallicity and only a weak trend with the UV flux. Likewise, $\epsilon_{\rm ff}$ estimated using projected patches of 500 pc size does not vary with metallicity and shows only a weak trend with average UV flux and gas surface density. The characteristic values of $\epsilon_\mathrm{ff}\approx 0.01-0.1$ arise naturally in the simulations via the combined effect of dynamical gas compression and ensuing stellar feedback that injects thermal and turbulent energy. The compression and feedback regulate the virial parameter, $\alpha_\mathrm{vir}$, in star-forming regions, limiting it to $\alpha_\mathrm{vir}\approx 3-10$. Turbulence plays an important role in the universality of $\epsilon_\mathrm{ff}$ because turbulent energy and its dissipation are not sensitive to metallicity and UV flux that affect thermal energy. Our results indicate that the universality of observational estimates of $\epsilon_\mathrm{ff}$ can be plausibly explained by the turbulence-driven and feedback-regulated properties of star-forming regions., Comment: Submitted to the Open Journal of Astrophysics

Fast and accurate approximations of gas cooling and heating functions are needed for hydrodynamic galaxy simulations. We use machine learning to analyze atomic gas cooling and heating functions in the presence of a generalized incident local radiation field computed by Cloudy. We characterize the radiation field through binned radiation field intensities instead of the photoionization rates used in our previous work. We find a set of 6 energy bins whose intensities exhibit relatively low correlation. We use these bins as features to train machine learning models to predict Cloudy cooling and heating functions at fixed metallicity. We compare the relative SHAP importance of the features. From the SHAP analysis, we identify a feature subset of 3 energy bins ($0.5-1, 1-4$, and $13-16 \, \mathrm{Ry}$) with the largest importance and train additional models on this subset. We compare the mean squared errors and distribution of errors on both the entire training data table and a randomly selected 20% test set withheld from model training. The machine learning models trained with 3 and 6 bins, as well as 3 and 4 photoionization rates, have comparable accuracy everywhere. We conclude that 3 energy bins (or 3 analogous photoionization rates: molecular hydrogen photodissociation, neutral hydrogen HI, and fully ionized carbon CVI) are sufficient to characterize the dependence of the gas cooling and heating functions on our assumed incident radiation field model., Comment: 12 + 5 pages, 7 + 4 figures. To be submitted to OJA. Comments welcome!

The role of unresolved structures ("mini-halos") in determining the consumption of ionizing photons during cosmic reionization remains an unsolved problem in modeling cosmic reionization, despite recent extensive studies with small-box high-resolution simulations by Park et al. and Chan et al., because the small-box studies are not able to fully sample all environments. In this paper these simulations are combined with large-box simulations from the "Cosmic Reionization On Computers" (CROC) project, allowing one to account for the full range of environments and to produce an estimate for the number of recombinations per hydrogen atom that are missed in large-scale simulations like CROC or Thesan. I find that recombinations in unresolved mini-halos are completely negligible compared to recombinations produced in large-scale cosmic structures and inside more massive, fully resolved halos. Since both Park et al. and Chan et al. studies have severe limitations, the conclusions of this paper may need to be verified with more representative sets of small-box high-resolution simulations., Comment: Submitted to ApJ

We examine the evolution of the phase diagram of the low-density intergalactic medium during the Epoch of Reionization in simulation boxes with varying reionization histories from the Cosmic Reionization on Computers project. The PDF of gas temperature at fixed density exhibits two clear modes: a warm and cold temperature mode, corresponding to the gas inside and outside of ionized bubbles. We find that the transition between the two modes is "universal" in the sense that its timing is accurately parameterized by the value of the volume-weighted neutral fraction for any reionization history. This "universality" is more complex than just a reflection of the fact that ionized gas is warm and neutral gas is cold: it holds for the transition at a fixed value of gas density, and gas at different densities transitions from the cold to the warm mode at different values of the neutral fraction, reflecting a non-trivial relationship between the ionization history and the evolving gas density PDF. Furthermore, the "emergence" of the tight temperature-density relation in the warm mode is also approximately "universally" controlled by the volume-weighted neutral fraction for any reionization history. In particular, the "emergence" of the temperature-density relation (as quantified by the rapid decrease in its width) occurs when the neutral fraction is $10^{-4}\lesssim X_\mathrm{HI} \lesssim10^{-3}$ for any reionization history. Our results indicate that the neutral fraction is a primary quantity controlling the various properties of the temperature-density relation, regardless of reionization history., Comment: 7 pages, 10 figures. Updated to match accepted version in MNRAS

We use a suite of hydrodynamics simulations of the interstellar medium (ISM) within a galactic disk, which include radiative transfer, a non-equilibrium model of molecular hydrogen, and a realistic model for star formation and feedback, to study the structure of the ISM and H$_2$ abundance as a function of local ISM properties. We show that the star formation rate and structure of the ISM are sensitive to the metallicity of the gas with a progressively smoother density distribution with decreasing metallicity. In addition to the well-known trend of the HI-H$_2$ transition shifting to higher densities with decreasing metallicity, the maximum achieved molecular fraction in the interstellar medium drops drastically at $Z \lesssim 0.2 \, Z_\odot$ as the formation time of H$_2$ becomes much longer than a typical lifetime of dense regions of the ISM. We present accurate fitting formulae for both volumetric and projected $f_\mathrm{H_2}$ measured on different scales as a function of gas metallicity, UV radiation field, and gas density. We show that when the formulae are applied to the patches in the simulated galaxy the overall molecular gas mass is reproduced to better than a factor of $\lesssim 1.5$ across the entire range of metallicities and scales. We also show that the presented fit is considerably more accurate than any of the previous $f_\mathrm{H_2}$ models and fitting formulae in the low-metallicity regime. The fit can thus be used for modeling molecular gas in low-resolution simulations and semi-analytic models of galaxy formation in the dwarf and high-redshift regimes., Comment: 17 pages, 12 figures; submitted to ApJ

Gas cooling and heating functions play a crucial role in galaxy formation. But, it is computationally expensive to exactly compute these functions in the presence of an incident radiation field. These computations can be greatly sped up by using interpolation tables of pre-computed values, at the expense of making significant and sometimes even unjustified approximations. Here, we explore the capacity of machine learning to approximate cooling and heating functions with a generalized radiation field. Specifically, we use the machine learning algorithm XGBoost to predict cooling and heating functions calculated with the photoionization code Cloudy at fixed metallicity, using different combinations of photoionization rates as features. We perform a constrained quadratic fit in metallicity to enable a fair comparison with traditional interpolation methods at arbitrary metallicity. We consider the relative importance of various photoionization rates through both a principal component analysis (PCA) and calculation of SHapley Additive exPlanation (SHAP) values for our XGBoost models. We use feature importance information to select different subsets of rates to use in model training. Our XGBoost models outperform a traditional interpolation approach at each fixed metallicity, regardless of feature selection. At arbitrary metallicity, we are able to reduce the frequency of the largest cooling and heating function errors compared to an interpolation table. We find that the primary bottleneck to increasing accuracy lies in accurately capturing the metallicity dependence. This study demonstrates the potential of machine learning methods such as XGBoost to capture the non-linear behavior of cooling and heating functions., Comment: 12+4 pages, 6+2 figures. Published in MNRAS. Updated to match MNRAS accepted version

We model the interstellar dust content of the reionization era with a suite of cosmological, fluid-dynamical simulations of galaxies with stellar masses ranging from $\sim 10^5 - 10^9 M_{\odot}$ in the first $1.2$ billion years of the universe. We use a post-processing method that accounts for dust creation and destruction processes, allowing us to systematically vary the parameters of these processes to test whether dust-dependent observable quantities of galaxies at these epochs could be useful for placing constraints on dust physics. We then forward model observable properties of these galaxies to compare to existing data. We find that we are unable to simultaneously match existing observational constraints with any one set of model parameters. Specifically, the models which predict the largest dust masses $D/Z \gtrsim 0.1$ at $z = 5$ -- because of high assumed production yields and/or efficient growth via accretion in the interstellar medium -- are preferred by constraints on total dust mass and infrared luminosities, but these models produce far too much extinction in the ultraviolet, preventing them from matching observations of $\beta_{\rm UV}$. To investigate this discrepancy, we analyze the relative spatial distribution of stars and dust as probed by infrared (IR) and ultraviolet (UV) emission, which appear to exhibit overly symmetric morphologies compared to existing data, likely due to the limitations of the stellar feedback model used in the simulations. Our results indicate that the observable properties of the dust distribution in high redshift galaxies are a particularly strong test of stellar feedback., Comment: Submitted to ApJ, comments welcome

Lyman limit systems (LLSs) are dense hydrogen clouds with high enough HI column densities to absorb Lyman continuum photons emitted from distant quasars. Their high column densities imply an origin in dense environments; however, the statistics and distribution of LLSs at high redshifts still remain uncertain. In this paper, we use self-consistent radiative transfer cosmological simulations from the "Cosmic Reionization On Computers" (CROC) project to study the physical properties of LLSs at the tail end of cosmic reionization at $z\sim6$. We generate 3000 synthetic quasar sightlines to obtain a large number of LLS samples in the simulations. In addition, with the high physical fidelity and resolution of CROC, we are able to quantify the association between these LLS samples and nearby galaxies. Our results show that the fraction LLSs spatially associated with nearby galaxies is increasing with the HI column density. Moreover, we find that LLSs that are not near any galaxy typically reside in filamentary structures connecting neighboring galaxies in the intergalactic medium (IGM). This quantification of the distribution and associations of LLSs to large scale structures informs our understanding of the IGM-galaxy connection during the Epoch of Reionization, and provides a theoretical basis for interpreting future observations., Comment: 11 pages, 10 figures, submitted to ApJ

Baryons both increase halo concentration through adiabatic contraction and expel mass through feedback processes. However, it is not well understood how the radiation fields prevalent during the epoch of reionization affect the evolution of concentration in dark matter halos. We investigate how baryonic physics during the epoch of reionization modify the structure of dark matter halos in the Cosmic Reionization On Computers (CROC) simulations. We use two different measures of halo concentration to quantify the effects. We compare concentrations of halos matched between full physics simulations and dark-matter-only simulations with identical initial conditions between $5 \leq z \leq 9$. Baryons in full physics simulations do pull matter towards the center, increasing the maximum circular velocity compared to dark-matter-only simulations. However, their overall effects are much less than if all the baryons were simply centrally concentrated indicating that heating processes efficiently counteract cooling effects. Finally, we show that the baryonic effects on halo concentrations at $z\approx5$ are relatively insensitive to environmental variations of reionization history. These results are pertinent to models of galaxy-halo connection during the epoch of reionization., Comment: 9 pages, 7 figures, comments are welcome

Observations of the Lyman-$\alpha$ (Ly$\alpha$) forest from spectroscopic surveys such as BOSS/eBOSS, or the ongoing DESI, offer a unique window to study the growth of structure on megaparsec scales. Interpretation of these measurements is a complicated task, requiring hydrodynamical simulations to model and marginalise over the thermal and ionisation state of the intergalactic medium. This complexity has limited the use of Ly$\alpha$ clustering measurements in joint cosmological analyses. In this work we show that the cosmological information content of the 1D power spectrum ($P_\mathrm{1D}$) of the Ly$\alpha$ forest can be compressed into a simple two-parameter likelihood without any significant loss of constraining power. We simulate $P_\mathrm{1D}$ measurements from DESI using hydrodynamical simulations and show that the compressed likelihood is model independent and lossless, recovering unbiased results even in the presence of massive neutrinos or running of the primordial power spectrum., Comment: Published in ApJ. 17 pages, 7 figures

High-redshift quasars ionize HeII into HeIII around them, heating the IGM in the process and creating large regions with elevated temperature. In this work, we demonstrate a method based on a convolutional neural network (CNN) to recover the spatial profile for $T_0$, the temperature at the mean cosmic density, in quasar proximity zones. We train the neural network with synthetic spectra drawn from a Cosmic Reionization on Computers simulation. We discover that the simple CNN is able to recover the temperature profile with an accuracy of $\approx 1400$ K in an idealized case of negligible observational uncertainties. We test the robustness of the CNN and discover that it is robust against the uncertainties in quasar host halo mass, quasar continuum and ionizing flux. We also find that the CNN has good generality with regard to the hardness of quasar spectra. Saturated pixels pose a bigger problem for accuracy and may downgrade the accuracy to $1700$ K in the outer parts of the proximity zones. Using our method, one could distinguish whether gas is inside or outside the HeIII region created by the quasar. Because the size of the HeIII region is closely related to the total quasar lifetime, this method has great potential in constraining the quasar lifetime on $\sim $Myr timescales., Comment: 10 pages, 11 figures, comments welcome

We introduce a model for the explicit evolution of interstellar dust in a cosmological galaxy formation simulation. We post-process a simulation from the Cosmic Reionization on Computers project (CROC, Gnedin 2014), integrating an ordinary differential equation for the evolution of the dust-to-gas ratio along pathlines in the simulation sampled with a tracer particle technique. This model incorporates the effects of dust grain production in asymptotic giant branch (AGB) star winds and supernovae (SN), grain growth due to the accretion of heavy elements from the gas phase of the interstellar medium (ISM), and grain destruction due to thermal sputtering in the high temperature gas of supernova remnants (SNRs). A main conclusion of our analysis is the importance of a carefully chosen dust destruction model, for which different reasonable parameterizations can predict very different values at the $\sim 100$ pc resolution of the ISM in our simulations. We run this dust model on the single most massive galaxy in a 10$h^{-1}$ co-moving Mpc box, which attains a stellar mass of $\sim 2\times10^9 M_{\odot}$ by $z=5$. We find that the model is capable of reproducing dust masses and dust-sensitive observable quantities broadly consistent with existing data from high-redshift galaxies. The total dust mass in the simulated galaxy is somewhat sensitive to parameter choices for the dust model, especially the timescale for grain growth due to accretion in the ISM. Consequently, observable quantities that can constrain galaxy dust masses at these epochs are potentially useful for placing constraints on dust physics., Comment: Submitted to ApJ, comments welcome!

The transformation of cold neutral intergalactic hydrogen into a highly ionized warm plasma marks the end of the cosmic dark ages and the beginning of the age of galaxies. The details of this process reflect the nature of the early sources of radiation and heat, the statistical characteristics of the large-scale structure of the Universe, the thermodynamics and chemistry of cosmic baryons, and the histories of star formation and black hole accretion. A number of massive data sets from new ground- and space-based instruments and facilities over the next decade are poised to revolutionize our understanding of primeval galaxies, the reionization photon budget, the physics of the intergalactic medium (IGM), and the fine-grained properties of hydrogen gas in the "cosmic web". In this review we survey the physics and key aspects of reionization-era modeling and describe the diverse range of computational techniques and tools currently available in this field., Comment: Accepted to Living Reviews in Computational Astrophysics. This is a "living" review and will be updated regularly. If we missed or misrepresented your recent work, we offer sincere apology and welcome a friendly comment - we will fix our error in the next revision

Understanding the connections between galaxy stellar mass, star formation rate, and dark matter halo mass represents a key goal of the theory of galaxy formation. Cosmological simulations that include hydrodynamics, physical treatments of star formation, feedback from supernovae, and the radiative transfer of ionizing photons can capture the processes relevant for establishing these connections. The complexity of these physics can prove difficult to disentangle and obfuscate how mass-dependent trends in the galaxy population originate. Here, we train a machine learning method called Explainable Boosting Machines (EBMs) to infer how the stellar mass and star formation rate of nearly 6 million galaxies simulated by the Cosmic Reionization on Computers (CROC) project depend on the physical properties of halo mass, the peak circular velocity of the galaxy during its formation history $v_\mathrm{peak}$, cosmic environment, and redshift. The resulting EBM models reveal the relative importance of these properties in setting galaxy stellar mass and star formation rate, with $v_\mathrm{peak}$ providing the most dominant contribution. Environmental properties provide substantial improvements for modeling the stellar mass and star formation rate in only $\lesssim10\%$ of the simulated galaxies. We also provide alternative formulations of EBM models that enable low-resolution simulations, which cannot track the interior structure of dark matter halos, to predict the stellar mass and star formation rate of galaxies computed by high-resolution simulations with detailed baryonic physics., Comment: 27 pages, 18 figures, Submitted to AAS Journals

I explore the properties of "dark gaps" - regions in quasar absorption spectra without significant transmission - with several simulations from the Cosmic Reionization On Computers (CROC) project. CROC simulations in largest available boxes (120 cMpc) come close to matching both the distribution of mean opacities and the frequency of dark gaps, but alas not in the same model: the run that matches the mean opacities fails to contain enough dark gaps and vice versa.:( Never-the-less, the run that matches the dark gap distributions serves as a counter-example to claims in the literature that the dark gap statistics requires a late end to reionization - in that run reionization ends at z=6.7 (likely too early). While multiple factors contribute to the frequency of large dark gaps in the simulations, the primary factor that controls the overall shape of the dark gap distribution is the ionization level in voids - the lowest density regions produce the highest transmission spikes that terminate long gaps. As the result, the dark gap distribution correlates strongly with the fraction of the spectrum above the gap detection threshold, the observed distribution is matched by the simulation in which this fraction is 2%. Hence, the gap distribution by itself does not constrain the timing of reionization., Comment: Submitted to ApJ

We perform maximum likelihood estimates (MLEs) for single and double flavor ultralight dark matter (ULDM) models using the Spitzer Photometry and Accurate Rotation Curves (SPARC) database. These estimates are compared to MLEs for several commonly used cold dark matter (CDM) models. By comparing various CDM models we find, in agreement with previous studies, that the Burkert and Einasto models tend to perform better than other commonly used CDM models. We focus on comparisons between the Einasto and ULDM models and analyze cases for which the ULDM particle masses are: free to vary; and fixed. For each of these analyses, we perform fits assuming the soliton and halo profiles are: summed together; and matched at a given radius. When we let the particle masses vary, we find a negligible preference for any particular range of particle masses, within $10^{-25}\,\text{eV}\leq m\leq10^{-19}\,\text{eV}$, when assuming the summed models. For the matched models, however, we find that almost all galaxies prefer particles masses in the range $10^{-23}\,\text{eV}\lesssim m\lesssim10^{-20}\,\text{eV}$. For both double flavor models we find that most galaxies prefer approximately equal particle masses. We find that the summed models give much larger variances with respect to the soliton-halo (SH) relation than the matched models. When the particle masses are fixed, the matched models give median and mean soliton and halo values that fall within the SH relation bounds, for most masses scanned. When the particle masses are fixed in the fitting procedure, we find the best fit results for the particle mass $m=10^{-20.5}\,\text{eV}$ (for the single flavor models) and $m_1=10^{-20.5}\,\text{eV}$, $m_2=10^{-20.2}\,\text{eV}$ for the double flavor, matched model. We discuss how our study will be furthered using a reinforcement learning algorithm., Comment: 36 pages, 25 figures, 2 appendices

Measuring the density of the intergalactic medium using quasar sightlines in the epoch of reionization is challenging due to the saturation of Lyman-$\alpha$ absorption. Near a luminous quasar, however, the enhanced radiation creates a proximity zone observable in the quasar spectra where the Lyman-$\alpha$ absorption is not saturated. In this study, we use $10$ high-resolution ($R\gtrsim 10,000$) $z\sim 6$ quasar spectra from the extended XQR-30 sample to measure the density field in the quasar proximity zones. We find a variety of environments within $3$ pMpc distance from the quasars. We compare the observed density cumulative distribution function (CDF) with models from the $\textit{Cosmic Reionization on Computers}$ simulation, and find a good agreement between $1.5$ to $3$pMpc from the quasar. This region is far away from the quasar hosts and hence approaching the mean density of the universe, which allows us to use the CDF to set constraints on the cosmological parameter $\sigma_8=0.6\pm0.3$. The uncertainty is mainly due to the limited number of high-quality quasar sightlines currently available. Utilizing the more than $>200$ known quasars at $z\gtrsim 6$, this method will allow us in the future to tighten the constraint on $\sigma_8$ to the percent level. In the region closer to the quasar within $1.5$ pMpc, we find the density is higher than predicted in the simulation by $1.23 \pm 0.17$, suggesting the typical host dark matter halo mass of a bright quasar ($M_{\rm 1450}<-26.5$) at $z\sim 6$ is $\log_{\rm 10} (M/M_\odot)=12.5^{+0.4}_{-0.7}$., Comment: 16 pages, 11 figures, submitted to ApJ, comments are welcome

Using a suite of self-similar cosmological simulations, we measure the probability distribution functions (PDFs) of real-space density, redshift-space density, and their geometric mean. We find that the real-space density PDF is well-described by a function of two parameters: $n_s$, the spectral slope, and $\sigma_L$, the linear rms density fluctuation. For redshift-space density and the geometric mean of real- and redshift-space densities, we introduce a third parameter, $s_L={\sqrt{\langle(dv^L_{\rm pec}/dr)^2\rangle}}/{H}$. We find that density PDFs for the LCDM cosmology is also well-parameterized by these three parameters. As a result, we are able to use a suite of self-similar cosmological simulations to approximate density PDFs for a range of cosmologies. We make the density PDFs publicly available and provide an analytical fitting formula for them., Comment: 9 pages, 10 figures, submitted to ApJ, comments welcome

Cooling and heating functions describe how radiative processes impact the thermal state of a gas as a function of its temperature and other physical properties. In a most general case the functions depend on the detailed distributions of ionic species and on the radiation spectrum. Hence, these functions may vary on a very wide range of spatial and temporal scales. In this paper, we explore cooling and heating functions between $5\leq z \leq10$ in simulated galaxies from the Cosmic Reionization On Computers (CROC) project. We compare three functions. First, the actual cooling and heating rates of hydrodynamic cells as a function of cell temperature. Second, the median cooling and heating functions computed using median interstellar medium (ISM) properties (median ISM). Last, the median of the cooling and heating functions of all gas cells (instantaneous). We find that the median ISM and instantaneous approaches to finding a median cooling and heating function give identical results within the spread due to cell-to-cell variation. However, the actual cooling (heating) rates experienced by the gas at different temperatures in the simulations do not correspond to either summarized cooling (heating) functions. In other words, the thermodynamics of the gas in the simulations cannot be described by a single set of a cooling plus a heating function with a spatially constant radiation field that could be computed with common tools, such as Cloudy., Comment: 12 pages, 7 figures. Key figure: figure 2. Accepted to ApJ

We describe a novel end-to-end approach using Machine Learning to reconstruct the power spectrum of cosmological density perturbations at high redshift from observed quasar spectra. State-of-the-art cosmological simulations of structure formation are used to generate a large synthetic dataset of line-of-sight absorption spectra paired with 1-dimensional fluid quantities along the same line-of-sight, such as the total density of matter and the density of neutral atomic hydrogen. With this dataset, we build a series of data-driven models to predict the power spectrum of total matter density. We are able to produce models which yield reconstruction to accuracy of about 1% for wavelengths $k \leq 2 h Mpc^{-1}$, while the error increases at larger $k$. We show the size of data sample required to reach a particular error rate, giving a sense of how much data is necessary to reach a desired accuracy. This work provides a foundation for developing methods to analyse very large upcoming datasets with the next-generation observational facilities., Comment: 10 pages, 9 figures

We introduce the cosmological HYPER code based on an innovative hydro-particle-mesh (HPM) algorithm for efficient and rapid simulations of gas and dark matter. For the HPM algorithm, we update the approach of Gnedin & Hui (1998) to expand the scope of its application from the lower-density intergalactic medium (IGM) to the higher-density intracluster medium (ICM). While the original algorithm tracks only one effective particle species, the updated version separately tracks the gas and dark matter particles as they do not exactly trace each other on small scales. For the approximate hydrodynamics solver, the pressure term in the gas equations of motion is calculated using robust physical models. In particular, we use a dark matter halo model, ICM pressure profile, and IGM temperature-density relation, all of which can be systematically varied for parameter-space studies. We show that the HYPER simulation results are in good agreement with the halo model expectations for the density, temperature, and pressure radial profiles. Simulated galaxy cluster scaling relations for Sunyaev-Zel'dovich (SZ) and X-ray observables are also in good agreement with mean predictions, with scatter comparable to that found in hydrodynamic simulations. HYPER also produces lightcone catalogs of dark matter halos and full-sky tomographic maps of the lensing convergence, SZ effect, and X-ray emission. These simulation products are useful for testing data analysis pipelines, generating training data for machine learning, understanding selection and systematic effects, and for interpreting astrophysical and cosmological constraints., Comment: 24 pages, 14 figures

An error in the gravitational force that the source of gravity induces on itself (a self-force error) violates both the conservation of linear momentum and the conservation of energy. If such errors are present in a self-gravitating system and are not sufficiently random to average out, the obtained numerical solution will become progressively more unphysical with time: the system will acquire or lose momentum and energy due to numerical effects. In this paper, we demonstrate how self-force errors can arise in the case where self-gravity is solved on an adaptively refined mesh when the refinement is nonuniform. We provide the analytical expression for the self-force error and numerical examples that demonstrate such self-force errors in idealized settings. We also show how these errors can be corrected to an arbitrary order by straightforward addition of correction terms at the refinement boundaries., Comment: 8 pages, 5 figures, ApJS accepted

The spatial decorrelation of dense molecular gas and young stars observed on $\lesssim 1$ kiloparsec scales in nearby galaxies indicates rapid dispersal of star-forming regions by stellar feedback. We explore the sensitivity of this decorrelation to different processes controlling the structure of the interstellar medium, the abundance of molecular gas, star formation, and feedback in a suite of simulations of an isolated dwarf galaxy with structural properties similar to NGC300 that self-consistently model radiative transfer and molecular chemistry. Our fiducial simulation reproduces the magnitude of decorrelation and its scale dependence measured in NGC300, and we show that this agreement is due to different aspects of feedback, including H$_2$ dissociation, gas heating by the locally variable UV field, early mechanical feedback, and supernovae. In particular, early radiative and mechanical feedback affects the correlation on $\lesssim 100$ pc scales, while supernovae play a significant role on $\gtrsim 100$ pc scales. The correlation is also sensitive to the choice of the local star formation efficiency per freefall time, $\epsilon_{\rm ff}$, which provides a strong observational constraint on $\epsilon_{\rm ff}$ when the global star formation rate is independent of its value. Finally, we explicitly show that the degree of correlation between the peaks of molecular gas and star formation density is directly related to the distribution of the lifetimes of star-forming regions., Comment: 21 pages + appendix, 17 figures; published in ApJ; the animated version of Figure 1 is available in the online version of the article and at https://vadimsemenov.com/research/ngc300

The matter density field at $z\sim 6$ is very challenging to probe. One of the traditional probes of the low density IGM that works successfully at lower redshifts is the Lyman-alpha forest in quasar spectra. However, at the end of reionization, the residual neutral hydrogen usually creates saturated absorption, thus much of the information about the gas density is lost. Luckily, in a quasar proximity zone, the ionizing radiation is exceptionally intense, thus creating a large region with non-zero transmitted flux. In this study we use the synthetic spectra from simulations to investigate how to recover the density fluctuations inside the quasar proximity zones. We show that, under ideal conditions, the density can be recovered accurately with a small scatter. We also discuss how systematics such as the quasar continuum fitting and reionization models affect the results. This study shows that by analyzing the absorption features inside quasar proximity zones we can potentially constrain quasar properties and the environments they reside in., Comment: 12 pages, 12 figures, comments welcome

The Fast Multipole Method (FMM) obeys periodic boundary conditions "natively" if it uses a periodic Green function for computing the multipole expansion in the interaction zone of each FMM oct-tree node. One can define the "optimal" Green function for such a method that results in the numerical solution that converges to the equivalent Particle-Mesh solution in the limit of sufficiently high order of multipoles. A discrete functional equation for the optimal Green function can be derived, but is not practically useful as methods for its solution are not known. Instead, this paper presents an approximation for the optimal Green function that is accurate to better than 1e-3 in LMAX norm and 1e-4 in L2 norm for practically useful multipole counts. Such an approximately optimal Green function offers a practical way for implementing FMM with periodic boundary conditions "natively", without the need to compute lattice sums or to rely on hybrid FMM-PM approaches., Comment: Accepted for publication by ApJ

In this paper, we study the sizes of quasar proximity zones with synthetic quasar absorption spectra obtained by post-processing a Cosmic Reionization On Computers (CROC) simulation. CROC simulations have both relatively large box sizes and high spacial resolution, allowing us to resolve Lyman limit systems, which are crucial for modeling the quasar absorption spectra. We find that before reionization most quasar proximity zone sizes grow steadily for $\sim 10$ Myr, while after reionization they grow rapidly but only for $\sim 0.1$ Myr. We also find a slow growth of $R_{\rm obs}$ with decreasing turn-on redshift. In addition, we find that $\sim 1-2\%$ of old quasars ($30$ Myr old) display extremely small proximity zone sizes ($<1$ proper Mpc), of which the vast majority are due to the occurrence of a damped Ly$\alpha$ absorber (DLA) or a Lyman limit system (LLS) along the line of sight. These DLAs and LLSs are contaminated with metal, which offers a way to distinguish them from the normal proximity zones of young quasars., Comment: 18 pages, 15 figures, comments welcome!

In this work we investigate the properties of the sources that reionized the intergalactic medium (IGM) in the high-redshift Universe. Using a semi-analytical model aimed at reproducing galaxies and black holes in the first 1.5 Gyr of the Universe, we revisit the relative role of star formation and black hole accretion in producing ionizing photons that can escape into the IGM. Both star formation and black hole accretion are regulated by supernova feedback, resulting in black hole accretion being stunted in low-mass halos. We explore a wide range of combinations for the escape fraction of ionizing photons (redshift-dependent, constant and scaling with stellar mass) from both star formation ($\langle f_{\rm esc}^{\rm sf} \rangle$) and AGN ($f_{\rm esc}^{\rm bh}$) to find: (i) the ionizing budget is dominated by stellar radiation from low stellar mass ($M_*<10^9 {\rm M_\odot}$ ) galaxies at $z>6$ with the AGN contribution (driven by $M_{bh}>10^6 {\rm M_\odot}$ black holes in $M_* > 10^9 {\rm M_\odot}$ galaxies) dominating at lower redshifts; (ii) AGN only contribute $10-25\%$ to the cumulative ionizing emissivity by $z=4$ for the models that match the observed reionization constraints; (iii) if the stellar mass dependence of $\langle f_{\rm esc}^{\rm sf} \rangle$ is shallower than $f_{\rm esc}^{\rm bh}$, at $z<7$ a transition stellar mass exists above which AGN dominate the escaping ionizing photon production rate; (iv) the transition stellar mass decreases with decreasing redshift. While AGN dominate the escaping emissivity above the knee of the stellar mass function at $z \sim 6.8$, they take-over at stellar masses that are a tenth of the knee mass by $z=4$., Comment: Accepted to MNRAS

We explore the connection between the stellar component of galaxies and their host halos during the epoch of reionization ($5 \leq z\leq10$) using the CROC (Cosmic Reionization on Computers) simulations. We compare simulated galaxies with observations and find that CROC underpredicts the abundance of luminous galaxies when compared to observed UV luminosity functions, and analogously the most massive galaxies when compared to observed stellar mass functions. We can trace the deficit of star formation to high redshifts, where the slope of the star formation rate to stellar mass relation is consistent with observations, but the normalization is systematically low. This results in a star formation rate density and stellar mass density that is systematically offset from observations. However, the less luminous or lower stellar mass objects have luminosities and stellar masses that agree fairly well with observational data. We explore the stellar-to-halo mass ratio, a key quantity that is difficult to measure at high redshifts and that models do not consistently predict. In CROC, the stellar-to-halo mass ratio {\it decreases} with redshift, a trend opposite to some abundance matching studies. These discrepancies uncover where future effort should be focused in order to improve the fidelity of modeling cosmic reionization. We also compare the CROC galaxy bias with observational measurements using Lyman-Break Galaxy (LBG) samples. The good agreement of simulation and data shows that the clustering of dark matter halos is properly captured in CROC., Comment: 11 pages, 9 figures, comments are welcome

Several massive ($M_{*} > 10^8 M_{\odot}$), high-redshift ($z = 8-10$) galaxies have recently been discovered to contain stars with ages of several hundred million years, pushing the onset of star formation in these galaxies back to $z\sim15$. The very existence of stars formed so early may serve as a test for cosmological models with suppressed small-scale power (and, hence, late formation of cosmic structure). We explore the ages of the oldest stars in numerical simulations from the Cosmic Reionization On Computers (CROC) project with cold dark matter (CDM) and two warm dark matter (WDM) cosmologies with 3 and 6 keV particles. There are statistically significant differences of $\sim 5\;{\rm Myr}$ between average stellar ages of massive galaxies in CDM and 3 keV WDM, while CDM and 6 keV WDM are statistically indistinguishable. Even this 5 Myr difference, however, is much less than current observational uncertainties on the stellar population properties of high-redshift galaxies. The age distributions of all galaxies in all cosmologies fail to produce a substantial Balmer break, although uncertainties in dust attenuation are a potentially significant factor. Finally, we assess the convergence of our simulation predictions and find that the systematic uncertainties on individual galaxy properties are comparable to the differences between cosmologies, suggesting these differences may not be numerically robust., Comment: Accepted in ApJ, update to match published version

I describe a modification to the original Fast Multipole Method (FMM) of Greengard & Rokhlin that approximates the gravitation field of an FMM cell as a small uniform grid (a "gridlet") of effective masses. The effective masses on a gridlet are set from the requirement that the multipole moments of the FMM cells are reproduced exactly, hence preserving the accuracy of the gravitational field representation. The calculation of the gravitational field from a multipole expansion can then be computed for all multipole orders simultaneously, with a single Fast Fourier Transform, significantly reducing the computational cost at a given value of the required accuracy. The described approach belongs to the class of "kernel independent" variants of the FMM method and works with any Green function., Comment: Accepted for publication in the ApJ

We examine the reionization history of present-day galaxies by explicitly tracing the building blocks of halos from the Cosmic Reionization On Computers project. We track dark matter particles that belong to $z=0$ halos to trace the neutral fractions at corresponding positions during rapid global reionization. The resulting particle reionization histories allow us to explore different definitions of a halo's reionization redshift and to account for the neutral content of the interstellar medium. Consistent with previous work, we find a systematic trend of reionization redshift with mass - present day halos with higher masses have earlier reionization times. Finally, we quantify the spread of reionization times within each halo, which also has a mass dependence., Comment: 7 pages, 5 figures, Accepted to ApJ

The surface densities of molecular gas, $\Sigma_{\rm H_2}$, and the star formation rate (SFR), $\dot\Sigma_\star$, correlate almost linearly on kiloparsec scales in observed star-forming (non-starburst) galaxies. We explore the origin of the linear slope of this correlation using a suite of isolated $L_\star$ galaxy simulations. We show that in simulations with efficient feedback, the slope of the $\dot\Sigma_\star$-$\Sigma_{\rm H_2}$ relation on kiloparsec scales is insensitive to the slope of the $\dot\rho_\star$-$\rho$ relation assumed at the resolution scale. We also find that the slope on kiloparsec scales depends on the criteria used to identify star-forming gas, with a linear slope arising in simulations that identify star-forming gas using a virial parameter threshold. This behavior can be understood using a simple theoretical model based on conservation of interstellar gas mass as the gas cycles between atomic, molecular, and star-forming states under the influence of feedback and dynamical processes. In particular, we show that the linear slope emerges when feedback efficiently regulates and stirs the evolution of dense, molecular gas. We show that the model also provides insights into the likely origin of the relation between the SFR and molecular gas in real galaxies on different scales., Comment: 14 pages + appendix, 15 figures; accepted for publication in the Astrophysical Journal

We study the mass of quasar-hosting dark matter halos at z $\sim$ 6 and further constrain the fraction of dark matter halos hosting an active quasar $f_{on}$ and the quasar beaming angle $i_{\rm max}$ using observations of CII lines in the literature. We make assumptions that (1) more massive halos host brighter quasars, (2) a fraction of the halos host active quasars with a certain beaming angle, (3) cold gas in galaxies has rotational velocity $V_{\rm circ}=\alpha V_{\rm max}$, and that (4) quasars point randomly on the sky. We find that for a choice of specific $\alpha \gtrsim 1$, the most likely solution has $f_{\rm on} < 0.01$, corresponding to a small duty cycle of quasar activity. However, if we marginalize over $\alpha$, for some choices of a prior a second solution with $f_{\rm on}=1$ appears. Overall, our the constraints are highly sensitive to $\alpha$ and hence inconclusive. Stronger constraints on $f_{\rm on}$ can be made if we better understand the dynamics of cold gas in these galaxies.

Using a suite of isolated $L_\star$ galaxy simulations, we show that global depletion times and star-forming gas mass fractions in simulated galaxies exhibit systematic and well-defined trends as a function of the local star formation efficiency per freefall time, $\epsilon_{\rm ff}$, strength of stellar feedback, and star formation threshold. We demonstrate that these trends can be reproduced and explained by a simple physical model of global star formation in galaxies. Our model is based on mass conservation and the idea of gas cycling between star-forming and non-star-forming states on certain characteristic time scales under the influence of dynamical and feedback processes. Both the simulation results and our model predictions exhibit two limiting regimes with rather different dependencies of global galactic properties on the local parameters. When $\epsilon_{\rm ff}$ is small and feedback is inefficient, the total star-forming mass fraction, $f_{\rm sf}$, is independent of $\epsilon_{\rm ff}$ and the global depletion time, $\tau_{\rm dep}$, scales inversely with $\epsilon_{\rm ff}$. When $\epsilon_{\rm ff}$ is large or feedback is very efficient, these trends are reversed: $f_{\rm sf} \propto \epsilon_{\rm ff}^{-1}$ and $\tau_{\rm dep}$ is independent of $\epsilon_{\rm ff}$ but scales linearly with the feedback strength. We also compare our results with the observed depletion times and mass fractions of star-forming and molecular gas and show that they provide complementary constraints on $\epsilon_{\rm ff}$ and the feedback strength. We show that useful constraints on $\epsilon_{\rm ff}$ can also be obtained using measurements of the depletion time and its scatter on different spatial scales., Comment: 17 pages + appendix, 13 figures, 1 table; accepted for publication in ApJ

An optimally efficient explicit numerical scheme for solving fluid dynamics equations, or any other parabolic or hyperbolic system of partial differential equations, should allow local regions to advance in time with their own, locally constrained time steps. However, such a scheme can result in violation of the Courant-Friedrichs-Lewy (CFL) condition, which is manifestly non-local. Although the violations can be considered to be "weak" in a certain sense and the corresponding numerical solution may be stable, such calculation does not guarantee the correct propagation speed for arbitrary waves. We use an experimental fluid dynamics code that allows cubic "patches" of grid cells to step with independent, locally constrained time steps to demonstrate how the CFL condition can be enforced by imposing a condition on the time steps of neighboring patches. We perform several numerical tests that illustrate errors introduced in the numerical solutions by weak CFL condition violations and show how strict enforcement of the CFL condition eliminates these errors. In all our tests the strict enforcement of the CFL condition does not impose a significant performance penalty., Comment: Accepted for publication in the Journal of Computational Physics

A deep understanding of the Epoch of Reionization is still missing in our knowledge of the universe. While future probes will allow us to test the precise evolution of the free electron fraction from redshifts between $z\simeq 6$ and $z\simeq 20$, at present one could ask what kind of reionization processes are allowed by present Cosmic Microwave Background temperature and polarization measurements. An early contribution to reionization could imply a departure from the standard picture where star formation determines the reionization onset. BBy considering a broad class of possible reionization parameterizations, we find that current data do not require an early reionization component in our universe and that only one marginal class of models, based on a particular realization of reionization, may point to that. In addition, the frequentist Akaike Information Criterion (AIC) provides strong evidence against alternative reionization histories, favoring the most simple reionization scenario, which describes reionization by means of only one (constant) reionization optical depth $\tau$., Comment: 16 pages, 3 figures. Version accepted for publication in JCAP

The implementation of star formation and stellar feedback in cosmological simulations plays a critical role in shaping galaxy properties. In the first paper of the series, we presented a new method to model star formation as a collection of star clusters. In this paper, we improve the algorithm by eliminating accretion gaps, boosting momentum feedback, and introducing a subgrid initial bound fraction, $f_i$, that distinguishes cluster mass from stellar particle mass. We perform a suite of simulations with different star formation efficiency per freefall time $\epsilon_{\rm ff}$ and supernova momentum feedback intensity $f_{\rm boost}$. We find that the star formation history of a Milky Way-sized galaxy is sensitive to $f_{\rm boost}$, which allows us to constrain its value, $f_{\rm boost}\approx5$, in the current simulation setup. Changing $\epsilon_{\rm ff}$ from a few percent to 200\% has little effect on global galaxy properties. However, on smaller scales, the properties of star clusters are very sensitive to $\epsilon_{\rm ff}$. We find that $f_i$ increases with $\epsilon_{\rm ff}$ and cluster mass. Through the dependence on $f_i$, the shape of the cluster initial mass function varies strongly with $\epsilon_{\rm ff}$. The fraction of clustered star formation and maximum cluster mass increase with the star formation rate surface density, with the normalization of both relations dependent on $\epsilon_{\rm ff}$. The cluster formation timescale systematically decreases with increasing $\epsilon_{\rm ff}$. Local variations in the gas accretion history lead to a 0.25~dex scatter for the integral cluster formation efficiency. Joint constraints from all the observables prefer the runs that produce a median integral efficiency of 16\%., Comment: 18 pages, 14 figure., ApJ in press

In models with dark matter made of particles with keV masses, such as a sterile neutrino, small-scale density perturbations are suppressed, delaying the period at which the lowest mass galaxies are formed and therefore shifting the reionization processes to later epochs. In this study, focusing on Warm Dark Matter (WDM) with masses close to its present lower bound, i.e. around the $3$ keV region, we derive constraints from galaxy luminosy functions, the ionization history and the Gunn-Peterson effect. We show that even if star formation efficiency in the simulations is adjusted to match the observed UV galaxy luminosity functions in both CDM and WDM models, the full distribution of Gunn-Peterson optical depth retains the strong signature of delayed reionization in the WDM model. However, until the star formation and stellar feedback model used in modern galaxy formation simulations is constrained better, any conclusions on the nature of dark matter derived from reionization observables remain model-dependent., Comment: 7 pages, 6 figures

Baryonic effects are amongst the most severe systematics to the tomographic analysis of weak lensing data which is the principal probe in many future generations of cosmological surveys like LSST, Euclid etc.. Modeling or parameterizing these effects is essential in order to extract valuable constraints on cosmological parameters. In a recent paper, Eifler et al. (2015) suggested a reduction technique for baryonic effects by conducting a principal component analysis (PCA) and removing the largest baryonic eigenmodes from the data. In this article, we conducted the investigation further and addressed two critical aspects. Firstly, we performed the analysis by separating the simulations into training and test sets, computing a minimal set of principle components from the training set and examining the fits on the test set. We found that using only four parameters, corresponding to the four largest eigenmodes of the training set, the test sets can be fitted thoroughly with an RMS $\sim 0.0011$. Secondly, we explored the significance of outliers, the most exotic/extreme baryonic scenarios, in this method. We found that excluding the outliers from the training set results in a relatively bad fit and degraded the RMS by nearly a factor of 3. Therefore, for a direct employment of this method to the tomographic analysis of the weak lensing data, the principle components should be derived from a training set that comprises adequately exotic but reasonable models such that the reality is included inside the parameter domain sampled by the training set. The baryonic effects can be parameterized as the coefficients of these principle components and should be marginalized over the cosmological parameter space., Comment: 7 pages, 8 figures, 1 table. Submitted to ApJ

We present a model that explains why galaxies form stars on a time scale significantly longer than the time scales of processes governing the evolution of interstellar gas. We show that gas evolves from a non-star-forming to a star-forming state on a relatively short time scale and thus the rate of this evolution does not limit the star formation rate. Instead, the star formation rate is limited because only a small fraction of star-forming gas is converted into stars before star-forming regions are dispersed by feedback and dynamical processes. Thus, gas cycles into and out of star-forming state multiple times, which results in a long time scale on which galaxies convert gas into stars. Our model does not rely on the assumption of equilibrium and can be used to interpret trends of depletion times with the properties of observed galaxies and the parameters of star formation and feedback recipes in simulations. In particular, the model explains how feedback self-regulates the star formation rate in simulations and makes it insensitive to the local star formation efficiency. We illustrate our model using the results of an isolated $L_*$-sized galaxy simulation that reproduces the observed Kennicutt-Schmidt relation for both molecular and atomic gas. Interestingly, the relation for molecular gas is almost linear on kiloparsec scales, although a nonlinear relation is adopted in simulation cells. We discuss how a linear relation emerges from non-self-similar scaling of the gas density PDF with the average gas surface density., Comment: 16 pages, 9 figures; accepted for publication in ApJ

Using an isolated Milky Way-mass galaxy simulation, we compare results from 9 state-of-the-art gravito-hydrodynamics codes widely used in the numerical community. We utilize the infrastructure we have built for the AGORA High-resolution Galaxy Simulations Comparison Project. This includes the common disk initial conditions, common physics models (e.g., radiative cooling and UV background by the standardized package Grackle) and common analysis toolkit yt, all of which are publicly available. Subgrid physics models such as Jeans pressure floor, star formation, supernova feedback energy, and metal production are carefully constrained across code platforms. With numerical accuracy that resolves the disk scale height, we find that the codes overall agree well with one another in many dimensions including: gas and stellar surface densities, rotation curves, velocity dispersions, density and temperature distribution functions, disk vertical heights, stellar clumps, star formation rates, and Kennicutt-Schmidt relations. Quantities such as velocity dispersions are very robust (agreement within a few tens of percent at all radii) while measures like newly-formed stellar clump mass functions show more significant variation (difference by up to a factor of ~3). Systematic differences exist, for example, between mesh-based and particle-based codes in the low density region, and between more diffusive and less diffusive schemes in the high density tail of the density distribution. Yet intrinsic code differences are generally small compared to the variations in numerical implementations of the common subgrid physics such as supernova feedback. Our experiment reassures that, if adequately designed in accordance with our proposed common parameters, results of a modern high-resolution galaxy formation simulation are more sensitive to input physics than to intrinsic differences in numerical schemes., Comment: 28 pages, 35 figures, Accepted for publication in the Astrophysical Journal, Image resolution greatly reduced, High-resolution version of this article is available at http://www.jihoonkim.org/agora/AGORA_Paper4_draft.pdf, The first paper of the AGORA Initiative is at http://adsabs.harvard.edu/abs/2014ApJS..210...14K, More information on AGORA is at http://www.AGORAsimulations.org/

We present a new implementation of star formation in cosmological simulations, by considering star clusters as a unit of star formation. Cluster particles grow in mass over several million years at the rate determined by local gas properties, with high time resolution. The particle growth is terminated by its own energy and momentum feedback on the interstellar medium. We test this implementation for Milky Way-sized galaxies at high redshift, by comparing the properties of model clusters with observations of young star clusters. We find that the cluster initial mass function is best described by a Schechter function rather than a single power law. In agreement with observations, at low masses the logarithmic slope is $\alpha\approx 1.8-2$, while the cutoff at high mass scales with the star formation rate. A related trend is a positive correlation between the surface density of star formation rate and fraction of stars contained in massive clusters. Both trends indicate that the formation of massive star clusters is preferred during bursts of star formation. These bursts are often associated with major merger events. We also find that the median timescale for cluster formation ranges from 0.5 to 4 Myr and decreases systematically with increasing star formation efficiency. Local variations in the gas density and cluster accretion rate naturally lead to the scatter of the overall formation efficiency by an order of magnitude, even when the instantaneous efficiency is kept constant. Comparison of the formation timescale with the observed age spread of young star clusters provides an additional important constraint on the modeling of star formation and feedback schemes., Comment: 17 pages, 13 figures, ApJ accepted

I show that the Reduced Speed of Light (RSL) approximation, when used properly (i.e. as originally designed - only for the local sources but not for the cosmic background), remains a highly accurate numerical method for modeling cosmic reionization. Simulated ionization and star formation histories from the "Cosmic Reionization On Computers" (CROC) project are insensitive to the adopted value of the reduced speed of light for as long as that value does not fall below about 10% of the true speed of light. A recent claim of the failure of the RSL approximation in the Illustris reionization model appears to be due to the effective speed of light being reduced in the equation for the cosmic background too, and, hence, illustrates the importance of maintaining the correct speed of light in modeling the cosmic background., Comment: Submitted to ApJ

We explore the effects of specific assumptions in the subgrid models of star formation and stellar and AGN feedback on intrinsic alignments of galaxies in cosmological simulations of "MassiveBlack-II" family. Using smaller volume simulations, we explored the parameter space of the subgrid star formation and feedback model and found remarkable robustness of the observable statistical measures to the details of subgrid physics. The one observational probe most sensitive to modeling details is the distribution of misalignment angles. We hypothesize that the amount of angular momentum carried away by the galactic wind is the primary physical quantity that controls the orientation of the stellar distribution. Our results are also consistent with a similar study by the EAGLE simulation team., Comment: 7 pages, 6 figures, submitted to ApJ

In this paper, the first in a series on galaxy formation before reionization, we focus on understanding what determines the size and morphology of stellar objects in the first low mass galaxies, using parsec- scale cosmological simulations performed with an adaptive mesh hydrodynamics code. Although the dense gas in which stars are formed tends to have a disk structure, stars are found in spheroids with little rotation. Halos with masses between 10^6 M_sun and 5x10^8 M_sun form stars stochastically, with stellar masses in the range 10^4 M_sun to 2x10^6 M_sun. Nearly independent of stellar mass, we observe a large range of half-light radii for the stars, from a few parsecs to a few hundred parsecs and surface brightnesses and mass-to-light ratios ranging from those typical of globular clusters to ultra-faint dwarfs. In our simulations, stars form in dense stellar clusters with high gas-to-star conversion efficiencies and rather uniform metallicities. A fraction of these clusters remain bound after the gas is removed by feedback, but others are destroyed, and their stars, which typically have velocity dispersions of 20 to 40 km/s, expand until they become bound by the dark matter halo. We thus speculate that the stars in ultra-faint dwarf galaxies may show kinematic and chemical signatures consistent with their origin in a few distinct stellar clusters. On the other hand, some globular clusters may form at the center of primordial dwarf galaxies and may contain dark matter, perhaps detectable in the outer parts., Comment: 15 pages, 12 figure, submitted to ApJ

We present a comparison between several observational tests of the post-reionization IGM and the numerical simulations of reionization completed under the Cosmic Reionization On Computers (CROC) project. The CROC simulations match the gap distribution reasonably well, and also provide a good match for the distribution of peak heights, but there is a notable lack of wide peaks in the simulated spectra and the flux PDFs are poorly matched in the narrow redshift interval 5.5

Using numerical cosmological simulations completed under the "Cosmic Reionization On Computers" (CROC) project, I explore theoretical predictions for the faint end of the galaxy UV luminosity functions at $z\geq 6$. A commonly used Schechter function approximation with the magnitude cut at $M_{\rm CUT}\sim-13$ provides a reasonable fit to the actual luminosity function of simulated galaxies. When the Schechter functional form is forced on the luminosity functions from the simulations, the magnitude cut $M_{\rm CUT}$ is found to vary between $-12$ and $-14$ with a mild redshift dependence. An analytical model of reionization from Madau, Haardt & Rees (1997), as used by Robertson et al. (2015), provides a good description of the simulated results, but only if the redshift dependence of the effective escape fraction (induced by physical processes not captured by the Madau, Haardt & Rees model) is accounted for., Comment: Published in ApJ Letters

In this paper I show that simulations of reionization performed under the Cosmic Reionization On Computers (CROC) project do converge in space and mass, albeit rather slowly. A fully converged solution (for a given star formation and feedback model) can be determined at a level of precision of about 20%, but such a solution is useless in practice, since achieving it in production-grade simulations would require a large set of runs at various mass and spatial resolutions, and computational resources for such an undertaking are not yet readily available. In order to make progress in the interim, I introduce a weak convergence correction factor in the star formation recipe, which allows one to approximate the fully converged solution with finite resolution simulations. The accuracy of weakly converged simulations approaches a comparable, ~20% level of precision for star formation histories of individual galactic halos and other galactic properties that are directly related to star formation rates, like stellar masses and metallicities. Yet other properties of model galaxies, for example, their HI masses, are recovered in the weakly converged runs only within a factor of two., Comment: Replaced with the accepted version