This paper describes the open-source code Enzo, which uses block-structured adaptive mesh refinement to provide high spatial and temporal resolution for modeling astrophysical fluid flows. The code is Cartesian, can be run in one, two, and three dimensions, and supports a wide variety of physics including hydrodynamics, ideal and non-ideal magnetohydrodynamics, N-body dynamics (and, more broadly, self-gravity of fluids and particles), primordial gas chemistry, optically thin radiative cooling of primordial and metal-enriched plasmas (as well as some optically-thick cooling models), radiation transport, cosmological expansion, and models for star formation and feedback in a cosmological context. In addition to explaining the algorithms implemented, we present solutions for a wide range of test problems, demonstrate the code's parallel performance, and discuss the Enzo collaboration's code development methodology.

/pdf/enzo-an-adaptive-mesh-refinement-code-for-astrophysics-2cgbpdu97q.pdf

Enzo: An Adaptive Mesh Refinement Code for Astrophysics

Active galactic nuclei (AGN) are energetic astrophysical sources powered by accretion onto supermassive black holes in galaxies, and present unique observational signatures that cover the full electromagnetic spectrum over more than twenty orders of magnitude in frequency. The rich phenomenology of AGN has resulted in a large number of different “flavours” in the literature that now comprise a complex and confusing AGN “zoo”. It is increasingly clear that these classifications are only partially related to intrinsic differences between AGN and primarily reflect variations in a relatively small number of astrophysical parameters as well the method by which each class of AGN is selected. Taken together, observations in different electromagnetic bands as well as variations over time provide complementary windows on the physics of different sub-structures in the AGN. In this review, we present an overview of AGN multi-wavelength properties with the aim of painting their “big picture” through observations in each electromagnetic band from radio to $$\gamma $$
 -rays as well as AGN variability. We address what we can learn from each observational method, the impact of selection effects, the physics behind the emission at each wavelength, and the potential for future studies. To conclude, we use these observations to piece together the basic architecture of AGN, discuss our current understanding of unification models, and highlight some open questions that present opportunities for future observational and theoretical progress.

Active galactic nuclei: what’s in a name?

We present the first cosmology results from large-scale structure in the Dark Energy Survey (DES) spanning 5000 deg$^2$. We perform an analysis combining three two-point correlation functions (3$\times$2pt): (i) cosmic shear using 100 million source galaxies, (ii) galaxy clustering, and (iii) the cross-correlation of source galaxy shear with lens galaxy positions. The analysis was designed to mitigate confirmation or observer bias; we describe specific changes made to the lens galaxy sample following unblinding of the results. We model the data within the flat $\Lambda$CDM and $w$CDM cosmological models. We find consistent cosmological results between the three two-point correlation functions; their combination yields clustering amplitude $S_8=0.776^{+0.017}_{-0.017}$ and matter density $\Omega_{\mathrm{m}} = 0.339^{+0.032}_{-0.031}$ in $\Lambda$CDM, mean with 68% confidence limits; $S_8=0.775^{+0.026}_{-0.024}$, $\Omega_{\mathrm{m}} = 0.352^{+0.035}_{-0.041}$, and dark energy equation-of-state parameter $w=-0.98^{+0.32}_{-0.20}$ in $w$CDM. This combination of DES data is consistent with the prediction of the model favored by the Planck 2018 cosmic microwave background (CMB) primary anisotropy data, which is quantified with a probability-to-exceed $p=0.13$ to $0.48$. When combining DES 3$\times$2pt data with available baryon acoustic oscillation, redshift-space distortion, and type Ia supernovae data, we find $p=0.34$. Combining all of these data sets with Planck CMB lensing yields joint parameter constraints of $S_8 = 0.812^{+0.008}_{-0.008}$, $\Omega_{\mathrm{m}} = 0.306^{+0.004}_{-0.005}$, $h=0.680^{+0.004}_{-0.003}$, and $\sum m_{\nu}<0.13 \;\mathrm{eV\; (95\% \;CL)}$ in $\Lambda$CDM; $S_8 = 0.812^{+0.008}_{-0.008}$, $\Omega_{\mathrm{m}} = 0.302^{+0.006}_{-0.006}$, $h=0.687^{+0.006}_{-0.007}$, and $w=-1.031^{+0.030}_{-0.027}$ in $w$CDM. (abridged) 

Dark Energy Survey Year 3 results: Cosmological constraints from galaxy clustering and weak lensing

Spitzer IRAC selection is a powerful tool for identifying luminous AGN. For deep IRAC data, however, the AGN selection wedges currently in use are heavily contaminated by star-forming galaxies, especially at high redshift. Using the large samples of luminous AGN and high-redshift star-forming galaxies in COSMOS, we redefine the AGN selection criteria for use in deep IRAC surveys. The new IRAC criteria are designed to be both highly complete and reliable, and incorporate the best aspects of the current AGN selection wedges and of infrared power-law selection while excluding high redshift star-forming galaxies selected via the BzK, DRG, LBG, and SMG criteria. At QSO-luminosities of log L(2-10 keV) (ergs/s) > 44, the new IRAC criteria recover 75% of the hard X-ray and IRAC-detected XMM-COSMOS sample, yet only 38% of the IRAC AGN candidates have X-ray counterparts, a fraction that rises to 52% in regions with Chandra exposures of 50-160 ks. X-ray stacking of the individually X-ray non-detected AGN candidates leads to a hard X-ray signal indicative of heavily obscured to mildly Compton-thick obscuration (log N_H (cm^-2) = 23.5 +/- 0.4). While IRAC selection recovers a substantial fraction of luminous unobscured and obscured AGN, it is incomplete to low-luminosity and host-dominated AGN.

Identifying Luminous AGN in Deep Surveys: Revised IRAC Selection Criteria

Active galactic nuclei (AGN) are energetic astrophysical sources powered by accretion onto supermassive black holes in galaxies, and present unique observational signatures that cover the full electromagnetic spectrum over more than twenty orders of magnitude in frequency. The rich phenomenology of AGN has resulted in a large number of different “flavours” in the literature that now comprise a complex and confusing AGN “zoo”. It is increasingly clear that these classifications are only partially related to intrinsic differences between AGN and primarily reflect variations in a relatively small number of astrophysical parameters as well the method by which each class of AGN is selected. Taken together, observations in different electromagnetic bands as well as variations over time provide complementary windows on the physics of different sub-structures in the AGN. In this review, we present an overview of AGN multi-wavelength properties with the aim of painting their “big picture” through observations in each electromagnetic band from radio to $$\gamma $$γ-rays as well as AGN variability. We address what we can learn from each observational method, the impact of selection effects, the physics behind the emission at each wavelength, and the potential for future studies. To conclude, we use these observations to piece together the basic architecture of AGN, discuss our current understanding of unification models, and highlight some open questions that present opportunities for future observational and theoretical progress.

Report on the ESO Workshop ''Active Galactic Nuclei: what's in a name?''

The physics and demographics of type 2 quasars remain poorly understood, and new samples of such objects selected in a variety of ways can give insight into their physical properties, evolution, and relationship to their host galaxies. We present a sample of 2758 type 2 quasars at z $\leq$ 1 from the SDSS-III/BOSS spectroscopic database, selected on the basis of their emission-line properties. We probe the luminous end of the population by requiring the rest-frame equivalent width of [OIII] to be > 100 A. We distinguish our objects from star-forming galaxies and type 1 quasars using line widths, standard emission line ratio diagnostic diagrams at z 0.52. The majority of our objects have [OIII] luminosities in the range 10^8.5-10^10 L$_{\odot}$ and redshifts between 0.4 and 0.65. Our sample includes over 400 type 2 quasars with incorrectly measured redshifts in the BOSS database; such objects often show kinematic substructure or outflows in the [OIII] line. The majority of the sample has counterparts in the WISE survey, with median infrared luminosity {\nu}L{\nu}[12{\mu}m] = 4.2 x 10^44 erg/sec. Only 34 per cent of the newly identified type 2 quasars would be selected by infrared color cuts designed to identify obscured active nuclei, highlighting the difficulty of identifying complete samples of type 2 quasars. We make public the multi-Gaussian decompositions of all [OIII] profiles for the new sample and for 568 type 2 quasars from SDSS I/II, together with non-parametric measures of line profile shapes and identify over 600 candidate double-peaked [OIII] profiles.

Spectroscopic identification of type 2 quasars at z < 1 in SDSS-III/BOSS

Fluctuations of the 21 cm brightness temperature before the formation of the first stars hold the promise of becoming a high-precision cosmological probe in the future. The growth of overdensities is very well described by perturbation theory at that epoch, and the signal can in principle be predicted to arbitrary accuracy for given cosmological parameters. Recently, Tseliakhovich and Hirata pointed out a previously neglected and important physical effect, due to the fact that baryons and cold dark matter (CDM) have supersonic relative velocities after recombination. This relative velocity suppresses the growth of matter fluctuations on scales $k\ensuremath{\sim}10--{10}^{3}\text{ }\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$. In addition, the amplitude of the small-scale power spectrum is modulated on the large scales over which the relative velocity varies, corresponding to $k\ensuremath{\sim}0.005--1\text{ }\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$. In this paper, the effect of the relative velocity on 21 cm brightness temperature fluctuations from redshifts $z\ensuremath{\ge}30$ is computed. We show that the 21 cm power spectrum is affected on most scales. On small scales, the signal is typically suppressed several tens of percent, except for extremely small scales ($k\ensuremath{\gtrsim}2000\text{ }\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$) for which the fluctuations are boosted by resonant excitation of acoustic waves. On large scales, 21 cm fluctuations are enhanced due to the nonlinear dependence of the brightness temperature on the underlying gas density and temperature. The enhancement of the 21 cm power spectrum is of a few percent at $k\ensuremath{\sim}0.1\text{ }\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$ and up to tens of percent at $k\ensuremath{\lesssim}0.005\text{ }\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$, for standard $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ cosmology. In principle this effect allows one to probe the small-scale matter power spectrum not only through a measurement of small angular scales but also through its effect on large angular scales.

New light on 21 cm intensity fluctuations from the dark ages

We present the GeneRalized ANd Differentiable Halo Occupation Distribution (GRAND- HOD) routine that generalizes the standard 5 parameter halo occupation distribution model (HOD Zheng et al. 2009) with various halo-scale physics and assembly bias. We describe the methodology of 4 different generalizations: satellite distribution generalization, velocity bias, closest approach distance generalization, and assembly bias. We showcase the signatures of these generalizations in the 2-point correlation function (2PCF) and the squeezed 3-point correlation function (squeezed 3PCF). We identify generalized HOD prescriptions that are nearly degenerate in the projected 2PCF and demonstrate that these degeneracies are broken in the redshift-space anisotropic 2PCF and the squeezed 3PCF. We also discuss the possibility of identifying degeneracies in the anisotropic 2PCF and further demonstrate the extra constraining power of the squeezed 3PCF on galaxy-halo connection models. We find that within our current HOD framework, the anisotropic 2PCF can predict the squeezed 3PCF better than its statistical error. This implies that a discordant squeezed 3PCF measurement could falsify the particular HOD model space. Alternatively, it is possible that further generalizations of the HOD model would open opportunities for the squeezed 3PCF to provide novel parameter measurements. The GRAND-HOD Python package is publicly available at this https URL com/SandyYuan/GRAND-HOD.

Exploring the squeezed three-point galaxy correlation function with generalized halo occupation distribution models

Building accurate and flexible galaxy-halo connection models is crucial in modeling galaxy clustering on non-linear scales. Recent studies have found that halo concentration by itself cannot capture the full galaxy assembly bias effect and that the local environment of the halo can be an excellent indicator of galaxy assembly bias. In this paper, we propose an extended halo occupation distribution model (HOD) that includes both a concentration-based assembly bias term and an environment-based assembly bias term. We use this model to achieve a good fit (chi^2/DoF = 1.35) on the 2D redshift-space 2-point correlation function (2PCF) of the Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxy sample. We find that the inclusion of both assembly bias terms is strongly favored by the data and the standard 5-parameter HOD is strongly rejected. More interestingly, the redshift-space 2PCF drives the assembly bias parameters in a way that preferentially assigns galaxies to lower mass halos. This results in galaxy-galaxy lensing predictions that are within 1sigma agreement with the observation, alleviating the perceived tension between galaxy clustering and lensing. We also showcase a consistent 3-5sigma preference for a positive environment-based assembly bias that persists over variations in the fit. We speculate that the environmental dependence might be driven by underlying processes such as mergers and feedback, but might also be indicative of a larger halo boundaries such as the splashback radius. Regardless, this work highlights the importance of building flexible galaxy-halo connection models and demonstrates the extra constraining power of the redshift-space 2PCF.

Evidence for galaxy assembly bias in BOSS CMASS redshift-space galaxy correlation function

We present a deep machine learning (ML)-based technique for accurately determining $\sigma_8$ and $\Omega_m$ from mock 3D galaxy surveys. The mock surveys are built from the AbacusCosmos suite of $N$-body simulations, which comprises 40 cosmological volume simulations spanning a range of cosmological models, and we account for uncertainties in galaxy formation scenarios through the use of generalized halo occupation distributions (HODs). We explore a trio of ML models: a 3D convolutional neural network (CNN), a power-spectrum-based fully connected network, and a hybrid approach that merges the two to combine physically motivated summary statistics with flexible CNNs. We describe best practices for training a deep model on a suite of matched-phase simulations and we test our model on a completely independent sample that uses previously unseen initial conditions, cosmological parameters, and HOD parameters. Despite the fact that the mock observations are quite small ($\sim0.07h^{-3}\,\mathrm{Gpc}^3$) and the training data span a large parameter space (6 cosmological and 6 HOD parameters), the CNN and hybrid CNN can constrain $\sigma_8$ and $\Omega_m$ to $\sim3\%$ and $\sim4\%$, respectively.

Sihan Yuan

Papers

Spectroscopic identification of type 2 quasars at z < 1 in SDSS-III/BOSS

New light on 21 cm intensity fluctuations from the dark ages

Exploring the squeezed three-point galaxy correlation function with generalized halo occupation distribution models

Evidence for galaxy assembly bias in BOSS CMASS redshift-space galaxy correlation function

A Hybrid Deep Learning Approach to Cosmological Constraints from Galaxy Redshift Surveys