Cosmic Density Field Research Articles

Constraining primordial non-Gaussianity with postreconstructed galaxy bispectrum in redshift space

Galaxy bispectrum is a promising probe of inflationary physics in the early Universe as a measure of primordial non-Gaussianity (PNG), whereas its signal-to-noise ratio is significantly affected by the mode coupling due to nonlinear gravitational growth. In this paper, we examine the standard reconstruction method of linear cosmic mass density fields from nonlinear galaxy density fields to decorrelate the covariance in redshift-space galaxy bispectra. In particular, we evaluate the covariance of the bispectrum for massive-galaxy-sized dark matter halos with reconstruction by using 4000 independent $N$-body simulations. Our results show that the bispectrum covariance for the postreconstructed field approaches the Gaussian prediction at scale of $k<0.2\text{ }\text{ }h\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$. We also verify the leading-order PNG-induced bispectrum is not affected by details of the reconstruction with perturbative theory. We then demonstrate the constraining power of the postreconstructed bispectrum for PNG at redshift of approximately 0.5. Further, we perform a Fisher analysis to make a forecast of PNG constraints by galaxy bispectra including anisotropic signals. Assuming a massive galaxy sample in the Sloan Digital Sky Survey Baryon Oscillation Spectroscopic Survey, we find that the postreconstructed bispectrum can constrain the local, equilateral, and orthogonal types of PNG with $\mathrm{\ensuremath{\Delta}}{f}_{\mathrm{NL}}\ensuremath{\sim}13$, 90, and 42, respectively, improving the constraints with the prereconstructed bispectrum by a factor of 1.3--3.2. In conclusion, the reconstruction plays an essential role in constraining various types of PNG signatures with a level of $\mathrm{\ensuremath{\Delta}}{f}_{\mathrm{NL}}\ensuremath{\lesssim}1$ from the galaxy bispectrum based on upcoming galaxy surveys.

Main-sequence Scatter is Real: The Joint Dependence of Galaxy Clustering on Star Formation and Stellar Mass

Abstract We present new measurements of the clustering of stellar-mass-complete samples of ∼40,000 SDSS galaxies at z ∼ 0.03 as a joint function of stellar mass and specific star formation rate (sSFR). Our results confirm what Coil et al. find at z ∼ 0.7: galaxy clustering is a stronger function of sSFR at fixed stellar mass than of stellar mass at fixed sSFR. We also find that galaxies above the star-forming main sequence (SFMS) with higher sSFR are less clustered than galaxies below the SFMS with lower sSFR, at a given stellar mass. A similar trend is present for quiescent galaxies. This confirms that main-sequence scatter, and scatter within the quiescent sequence, is physically connected to the large-scale cosmic density field. We compare the resulting galaxy bias versus sSFR, and relative bias versus sSFR ratio, for different galaxy samples across 0 < z < 1.2 to mock galaxy catalogs based on the empirical galaxy evolution model of Behroozi et al. This model fits PRIMUS and DEEP2 clustering data well at intermediate redshift, but agreement with SDSS is not as strong. We show that increasing the correlation between galaxy SFR and halo accretion rate at z ∼ 0 in the model substantially improves agreement with SDSS data. Mock catalogs suggest that central galaxies contribute substantially to the dependence of clustering on sSFR at a given stellar mass and that the signal is not simply an effect of satellite galaxy fraction differences with sSFR. Our results are highly constraining for galaxy evolution models and show that the stellar-to-halo mass relation depends on sSFR.

Cosmic birth: efficient Bayesian inference of the evolving cosmic web from galaxy surveys

ABSTRACT We present cosmic birth (COSMological Initial Conditions from Bayesian Inference Reconstructions with THeoretical models): an algorithm to reconstruct the primordial and evolved cosmic density fields from galaxy surveys on the light-cone. The displacement and peculiar velocity fields are obtained from forward modelling at different redshift snapshots given some initial cosmic density field within a Gibbs-sampling scheme. This allows us to map galaxies, observed in a light-cone, to a single high redshift and hereby provide tracers and the corresponding survey completeness in Lagrangian space including tetrahedral tessellation mapping. These Lagrangian tracers in turn permit us to efficiently obtain the primordial density field, making the cosmic birth code general to any structure formation model. Our tests are restricted for the time being to augmented Lagrangian perturbation theory. We show how to robustly compute the non-linear Lagrangian bias from clustering measurements in a numerical way, enabling us to get unbiased dark matter field reconstructions at initial cosmic times. We also show that we can accurately recover the information of the dark matter field from the galaxy distribution based on a detailed simulation. Novel key ingredients to this approach are a higher order Hamiltonian-sampling technique and a non-diagonal Hamiltonian mass matrix. This technique could be used to study the Eulerian galaxy bias from galaxy surveys and could become an ideal baryon acoustic reconstruction technique. In summary, this method represents a general reconstruction technique, including in a self-consistent way a survey mask, non-linear and non-local bias, and redshift-space distortions, with an efficiency about 10 times superior to previous comparable methods.

Solar wind temperature–velocity relationship over the last five solar cycles and Forbush decreases associated with different types of interplanetary disturbance

ABSTRACT The behaviour of the solar wind (SW) proton temperature and velocity and their relationship during Forbush decreases (FDs) associated with various types of solar source – coronal mass ejections (CMEs) and coronal holes (CHs) – have been studied. Analysis of cosmic ray variations, SW temperature, velocity, density, plasma beta, and magnetic field (from 1965–2019) is carried out using three databases: the OMNI database, Variations of Cosmic Rays database (IZMIRAN) and Forbush Effects & Interplanetary Disturbances database (IZMIRAN). Comparison of the observed SW temperature (T) and velocity (V) for the undisturbed SW allows us to derive a formula for the expected SW temperature (Texp, the temperature given by a T–V formula, if V is the observed SW speed). The results reveal a power-law T–V dependence with a steeper slope for low speeds (V < 425 km s−1, exponent = 3.29 ± 0.02) and flatter slope for high speeds (V > 425 km s−1, exponent = 2.25 ± 0.02). A study of changes in the T–V dependence over the last five solar cycles finds that this dependence varies with solar activity. The calculated temperature index KT = T/Texp can be used as an indicator of interplanetary and solar sources of FDs. It usually has abnormally large values in interaction regions of different-speed SW streams and abnormally low values inside magnetic clouds (MCs). The results obtained help us to identify the different kinds of interplanetary disturbance: interplanetary CMEs, sheaths, MCs, corotating interaction regions, high-speed streams from CHs, and mixed events.

Nonlinear 3D cosmic web simulation with heavy-tailed generative adversarial networks

Fast and accurate simulations of the non-linear evolution of the cosmic density field are a major component of many cosmological analyses, but the computational time and storage required to run them can be exceedingly large. For this reason, we use generative adversarial networks (GANs) to learn a compressed representation of the 3D matter density field that is fast and easy to sample, and for the first time show that GANs are capable of generating samples at the level of accuracy of other conventional methods. Using sub-volumes from a suite of GADGET-2 N-body simulations, we demonstrate that a deep-convolutional GAN can generate samples that capture both large- and small-scale features of the matter density field, as validated through a variety of n-point statistics. The use of a data scaling that preserves high-density features and a heavy-tailed latent space prior allow us to obtain state of the art results for fast 3D cosmic web generation. In particular, the mean power spectra from generated samples agree to within 5% up to k=3 and within 10% for k<5 when compared with N-body simulations, and similar accuracy is obtained for a variety of bispectra. By modeling the latent space with a heavy-tailed prior rather than a standard Gaussian, we better capture sample variance in the high-density voxel PDF and reduce errors in power spectrum and bispectrum covariance on all scales. Furthermore, we show that a conditional GAN can smoothly interpolate between samples conditioned on redshift. Deep generative models, such as the ones described in this work, provide great promise as fast, low-memory, high-fidelity forward models of large-scale structure.

Opening reionization: quantitative morphology of the epoch of reionization and its connection to the cosmic density field

ABSTRACT We introduce a versatile and spatially resolved morphological characterization of binary fields, rooted in the opening transform of mathematical morphology. We subsequently apply it to the thresholded ionization field in simulations of cosmic reionization and study the morphology of ionized regions. We find that an ionized volume element typically resides in an ionized region with radius ∼8 h−1 cMpc at the midpoint of reionization (z ≈ 7.5) and follow the bubble size distribution even beyond the overlap phase. We find that percolation of the fully ionized component sets in when 25 per cent of the universe is ionized and that the resulting infinite cluster incorporates all ionized regions above ∼8 h−1 cMpc. We also quantify the clustering of ionized regions of varying radius with respect to matter and on small scales detect the formation of superbubbles in the overlap phase. On large scales, we quantify the bias values of the centres of ionized and neutral regions of different sizes and not only show that the largest ones at the high-point of reionization can reach b ≈ 30, but also that early small ionized regions are positively correlated with matter and large neutral regions and late small ionized regions are heavily antibiased with respect to matter, down to b ≲ −20.

Consistent modeling of velocity statistics and redshift-space distortions in one-loop perturbation theory

The peculiar velocities of biased tracers of the cosmic density field contain important information about the growth of large scale structure and generate anisotropy in the observed clustering of galaxies. Using N-body data, we show that velocity expansions for halo redshift-space power spectra are converged at the percent-level at perturbative scales for most line-of-sight angles μ when the first three pairwise velocity moments are included, and that the third moment is well-approximated by a counterterm-like contribution. We compute these pairwise-velocity statistics in Fourier space using both Eulerian and Lagrangian one-loop perturbation theory using a cubic bias scheme and a complete set of counterterms and stochastic contributions. We compare the models and show that our models fit both real-space velocity statistics and redshift-space power spectra for both halos and a mock sample of galaxies at sub-percent level on perturbative scales using consistent sets of parameters, making them appealing choices for the upcoming era of spectroscopic, peculiar-velocity and kSZ surveys.

Super-resolution emulator of cosmological simulations using deep physical models

ABSTRACT We present an extension of our recently developed Wasserstein optimized model to emulate accurate high-resolution (HR) features from computationally cheaper low-resolution (LR) cosmological simulations. Our deep physical modelling technique relies on restricted neural networks to perform a mapping of the distribution of the LR cosmic density field to the space of the HR small-scale structures. We constrain our network using a single triplet of HR initial conditions and the corresponding LR and HR evolved dark matter simulations from the quijote suite of simulations. We exploit the information content of the HR initial conditions as a well-constructed prior distribution from which the network emulates the small-scale structures. Once fitted, our physical model yields emulated HR simulations at low computational cost, while also providing some insights about how the large-scale modes affect the small-scale structure in real space.

Measuring the evolution of intergalactic gas from z = 0 to 5 using the kinematic Sunyaev–Zel’dovich effect

ABSTRACT A complete census of baryons in the late Universe is a long-standing challenge due to the intermediate temperate and rarefied character of the majority of cosmic gas. To gain insight into this problem, we extract measurements of the kinematic Sunyaev–Zel’dovich (kSZ) effect from the cross-correlation of angular redshift fluctuations maps, which contain precise information about the cosmic density and velocity fields, and cosmic microwave background maps high-pass filtered using aperture photometry; we refer to this technique as angular redshift fluctuations (ARF)–kSZ tomography. Remarkably, we detect significant cross-correlation for a wide range of redshifts and filter apertures using 6dF galaxies, BOSS galaxies, and SDSS quasars as tracers, yielding a 11σ detection of the kSZ effect. We then leverage these measurements to set constraints on the location, density, and abundance of gas inducing the kSZ effect, finding that this gas resides outside dark matter haloes, presents densities ranging from 10 to 250 times the cosmic average, and comprises half of cosmic baryons. Taken together, these findings indicate that ARF–kSZ tomography provides a nearly complete census of intergalactic gas from z = 0 to 5.

Density weighted angular redshift fluctuations: a new cosmological observable

ABSTRACT We propose the use of angular fluctuations in the galaxy redshift field as a new way to extract cosmological information in the Universe. This new probe $\delta z (\hat{\mathbf {n}})$ consists of the statistics of sky maps built by projecting redshifts under a Gaussian window of width σz centred upon a redshift zobs, and weighted by the galaxy density field. We compute the angular power spectrum of the $\delta z (\hat{\mathbf {n}})$ field in both numerical simulations and in linear perturbation theory. From these, we find that the $\delta z (\hat{\mathbf {n}})$ field (i) is sensitive to the underlying density and peculiar velocity fields; (ii) is highly correlated, at the $\gtrsim 60\, {{\ \rm per\ cent}}$ level, to the line-of-sight projected peculiar velocity field; (iii) for narrow windows (σz &amp;lt; 0.03), it is almost completely uncorrelated to the projected galaxy angular density field under the same redshift window; and (iv) it is largely unaffected by multiplicative and additive systematic errors on the observed number of galaxies that are redshift-independent over ∼σz. We conclude that $\delta z (\hat{\mathbf {n}})$ is a simple and robust tomographic measure of the cosmic density and velocity fields, complementary to angular clustering, that will contribute to more complete exploitations of current and upcoming galaxy redshift surveys.

Constraining cosmology with big data statistics of cosmological graphs

ABSTRACT By utilizing large-scale graph analytic tools implemented in the modern big data platform, apache spark, we investigate the topological structure of gravitational clustering in five different universes produced by cosmological N-body simulations with varying parameters: (1) a WMAP 5-yr compatible ΛCDM cosmology, (2) two different dark energy equation of state variants, and (3) two different cosmic matter density variants. For the big data calculations, we use a custom build of standalone Spark/Hadoop cluster at Korea Institute for Advanced Study and Dataproc Compute Engine in Google Cloud Platform with sample sizes ranging from 7 to 200 million. We find that among the many possible graph-topological measures, three simple ones: (1) the average of number of neighbours (the so-called average vertex degree) α, (2) closed-to-connected triple fraction (the so-called transitivity) $\tau _\Delta$, and (3) the cumulative number density ns ≥ 5 of subgraphs with connected component size s ≥ 5, can effectively discriminate among the five model universes. Since these graph-topological measures are directly related with the usual n-points correlation functions of the cosmic density field, graph-topological statistics powered by big data computational infrastructure opens a new, intuitive, and computationally efficient window into the dark Universe.

Statistics of peaks of weakly non-Gaussian random fields: Effects of bispectrum in two- and three-dimensions

Analytic expressions for the statistics of peaks of random fields with weak non-Gaussianity are provided. Specifically, the abundance and spatial correlation of peaks are represented by formulas which can be evaluated only by virtually one-dimensional integrals. We assume the non-Gaussianity is weak enough such that it is represented by linear terms of the bispectrum. The formulas are formally given in $N$-dimensional space, and explicitly given in the case of $N=1,2,3$. Some examples of peak statistics in cosmological fields are calculated for the cosmic density field and weak lensing field, assuming the weak non-Gaussianity is induced by gravity. The formulas of this paper would find a fit in many applications to statistical analyses of cosmological fields.

Skewness of matter distribution in clustering dark energy cosmologies

We calculate the skewness (the third moment $S_3$) of matter distribution in dynamical dark energy cosmologies. We pay particular attention to the impact of dark energy perturbations on this quantity. There is indeed a clear signature of dark energy perturbations on this quantity. By properly allowing dark energy perturbations we show that their impact on $S_3$ is strong enough (a factor $\sim 3$ greater) to easily discriminate between clustering and non-clustering dark energy cosmologies. This indicates that high order statistics of the cosmic density field are useful to the study of dark energy models and are potentially able to rule out clustering dark energy cosmologies.

Intrinsic alignment statistics of density and velocity fields at large scales: Formulation, modeling, and baryon acoustic oscillation features

The kinematic Sunyaev-Zel'dovich effect enables us to directly probe the density-weighted velocity field up to very large cosmic scales. We investigate the effects of intrinsic alignments (IAs) of dark-matter halo shapes on cosmic density and velocity fields on such large scales. In the literature IAs have been detected up to $\sim 100~h^{-1}{\rm Mpc}$ using the gravitational shear-intrinsic ellipticity correlation and the alignment correlation function. In this paper we introduce the corresponding various velocity statistics: the (density-weighted) velocity-intrinsic ellipticity correlation as well as the alignment pairwise infall momentum, momentum correlation function, and density-weighted pairwise velocity dispersion. We derive theoretical expressions for these velocity alignment statistics for the first time based on the assumption that the density fluctuation is a Gaussian random field. Using large-volume, high-resolution $N$-body simulations, we measure the alignment statistics of density and velocity fields. The behaviors of IAs in the velocity statistics are similar to those in the density statistics, except that the halo orientations are aligned with the velocity field up to scales larger than those with the density field, $r\gg 100~h^{-1}{\rm Mpc}$, because of a factor of the wave number in the linear relation between the density and velocity fields in Fourier space, $v\propto \delta/k$. We show that the detected IAs of the velocity field can be well predicted by the linear alignment model. We also demonstrate that the baryon acoustic oscillation features can be detected in both the conventional and alignment velocity statistics. Our results indicate that observations of IAs with the velocity field on large scales can provide additional information on cosmological models, complementary to those with the density field.

Painting halos from cosmic density fields of dark matter with physically motivated neural networks

We present a novel halo painting network that learns to map approximate 3D dark matter fields to realistic halo distributions. This map is provided via a physically motivated network with which we can learn the non-trivial local relation between dark matter density field and halo distributions without relying on a physical model. Unlike other generative or regressive models, a well motivated prior and simple physical principles allow us to train the mapping network quickly and with relatively little data. In learning to paint halo distributions from computationally cheap, analytical and non-linear density fields, we bypass the need for full particle mesh simulations and halo finding algorithms. Furthermore, by design, our halo painting network needs only local patches of dark matter density to predict the halos, and as such, it can predict the 3D halo distribution for any arbitrary simulation box size. Our neural network can be trained using small simulations and used to predict large halo distributions, as long as the resolutions are equivalent. We evaluate our model's ability to generate 3D halo count distributions which reproduce, to a high degree, summary statistics such as the power spectrum and bispectrum, of the input or reference realizations.

Bayesian cosmic density field inference from redshift space dark matter maps.

We present a self-consistent Bayesian formalism to sample the primordial density fields compatible with a set of dark matter density tracers after a cosmic evolution observed in redshift space. Previous works on density reconstruction did not self-consistently consider redshift space distortions or included an additional iterative distortion correction step. We present here the analytic solution of coherent flows within a Hamiltonian Monte Carlo posterior sampling of the primordial density field. We test our method within the Zel'dovich approximation, presenting also an analytic solution including tidal fields and spherical collapse on small scales. Our resulting reconstructed fields are isotropic and their power spectra are unbiased compared to the true field defined by our mock observations. Novel algorithmic implementations are introduced regarding the mass assignment kernels when defining the dark matter density field and optimization of the time-step in the Hamiltonian equations of motions. Our algorithm, dubbed barcode, promises to be specially suited for analysis of the dark matter cosmic web down to scales of a few megaparsecs. This large-scale structure is implied by the observed spatial distribution of galaxy clusters - such as obtained from X-ray, Sunyaev-Zel'dovich, or weak lensing surveys - as well as that of the intergalactic medium sampled by the Ly α forest or perhaps even by deep hydrogen intensity mapping. In these cases, virialized motions are negligible, and the tracers cannot be modelled as point-like objects. It could be used in all of these contexts as a baryon acoustic oscillation reconstruction algorithm.

The infrared-luminous progenitors of high-zquasars

Here we explore the infrared (IR) properties of the progenitors of high-z quasar host galaxies. Adopting the cosmological, data constrained semi-analytic model GAMETE/QSOdust, we simulate several independent merger histories of a luminous quasar at z ~ 6, following black hole growth and baryonic evolution in all its progenitor galaxies. We find that a fraction of progenitor galaxies (about 0.4 objects per single luminous quasar) at 6.5 < z < 8 has an IR luminosity of L_IR > 10^13 Lsun (hyper-luminous IR galaxies; HyLIRGs). HyLIRGs progenitors reside in the most massive halos, with dark matter (DM) masses of M_DM ~ 10^12.5 - 10^13 Msun. These systems can be easily observed in their ~ 1 mm-continuum emission in a few seconds of integration time with the Atacama Large Millimeter/submillimeter Array (ALMA), and at least 40% of them host nuclear BH activity that is potentially observable in the soft and hard X-ray band. Our findings are in line with recent observations of exceptional massive DM halos hosting HyLIRGs at z ~ 7, suggesting that z ~ 6 luminous quasars are indeed the signposts of these observed rare peaks in the high-z cosmic density field, and that massive IR-luminous galaxies at higher z are their natural ancestors.

Studying galaxy troughs and ridges using weak gravitational lensing with the Kilo-Degree Survey

We study projected underdensities in the cosmic galaxy density field known as 'troughs', and their overdense counterparts, which we call 'ridges'. We identify these regions using a bright sample of foreground galaxies from the photometric Kilo-Degree Survey (KiDS), specifically selected to mimic the spectroscopic Galaxy And Mass Assembly survey (GAMA). Using background galaxies from KiDS, we measure the weak gravitational lensing profiles of the troughs/ridges. We quantify the amplitude of their lensing strength $A$ as a function of galaxy density percentile rank $P$ and galaxy overdensity $\delta$, and find that the skewness in the galaxy density distribution is reflected in the total mass distribution measured by weak lensing. We interpret our results using the mock galaxy catalogue from the Marenostrum Institut de Ci\`encies de l'Espai (MICE) simulation, and find a good agreement with our observations. Using signal-to-noise weights derived from the Scinet LIghtCone Simulations (SLICS) mock catalogue we optimally stack the lensing signal of KiDS troughs with an angular radius $\theta_A$ = {5,10,15,20} arcmin, resulting in {16.8,14.9,10.13,7.55} $\sigma$ detections. Finally, we select troughs using a volume-limited sample of galaxies, split into two redshift bins between 0.1 < z < 0.3. For troughs/ridges with transverse comoving radius $R_A$ = 1.9 Mpc/h, we find no significant difference in the comoving Excess Surface Density as a function of $P$ and $\delta$ between the low- and high-redshift sample. Using the MICE and SLICS mocks we predict that trough and ridge evolution could be detected with gravitational lensing using deeper and wider lensing surveys, such as those from the Large Synoptic Survey Telescope and Euclid.

Exploring the thermal energy contents of the intergalactic mediumwith the Sunyaev–Zeldovich effect

We examine the thermal energy contents of the intergalactic medium (IGM) over three orders of magnitude in both mass density and gas temperature using thermal Sunyaev–Zeldovich effect (tSZE). The analysis is based on Planck tSZE map and the cosmic density field, reconstructed in the Sloan Digital Sky Survey Data Release 7 volume and sampled on a grid of cubic cells of |$(1\, h^{-1}{\rm Mpc})^3$|⁠, together with a matched filter technique employed to maximize the signal to noise. Our results show that the pressure–density relation of the IGM is roughly a power law given by an adiabatic equation of state, with an indication of steepening at densities higher than about 10 times the mean density of the Universe. The implied average gas temperature is |$\sim$|104 K in regions of mean density, |$\rho _{\rm m} \sim {\overline{\rho }}_{\rm m}$|⁠, increasing to about |$10^5\, {\rm K}$| for |$\rho _{\rm m} \sim 10\, {\overline{\rho }}_{\rm m}$|⁠, and to |$\gt$|106 K for |$\rho _{\rm m} \sim 100\, {\overline{\rho }}_{\rm m}$|⁠. At a given density, the thermal energy content of the IGM is also found to be higher in regions of stronger tidal fields, likely due to shock heating by the formation of large-scale structure and/or feedback from galaxies and active galactic nuclei. A comparison of the results with hydrodynamic simulations suggests that the current data can already provide interesting constraints on galaxy formation.

Splashback radius of nonspherical dark matter halos from cosmic density and velocity fields

We investigate the splashback features of dark-matter halos based on cosmic density and velocity fields. Besides the density correlation function binned by the halo orientation angle which was used in the literature, we introduce, for the first time, the corresponding velocity statistic, alignment momentum correlation function, to take into account the asphericity of halos. Using large-volume, high-resolution N-body simulations, we measure the alignment statistics of density and velocity. On halo scales, $x\sim R_\mathrm{200m} \sim 1Mpc/h$, we detect a sharp steepening in the momentum correlation associated with the physical halo boundary, or the splashback feature, which is found more prominent than in the density correlation. We also find that the splashback radius determined from the density correlation becomes $\sim 3.5\%$ smaller than that from the momentum correlation, with their correlation coefficient being 0.605. Moreover, the orientation-dependent splashback feature due to halo asphericity is measured when the density profile is determined by dark-matter particles, which can be used as a test of collisional CDM since the halo shape is predicted to be rounder in such a model.