Large-scale Structure Surveys Research Articles

Effective halo model: Creating a physical and accurate model of the matter power spectrum and cluster counts

We introduce a physically motivated model of the matter power spectrum, based on the halo model and perturbation theory. This model achieves 1% accuracy on all $k$-scales between $k=0.02h\text{ }\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$ to $k=1h\text{ }\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$. Our key ansatz is that the number density of halos depends on the nonlinear density contrast filtered on some unknown scale $R$. Using the effective field theory of large scale structure to evaluate the two-halo term, we obtain a model for the power spectrum with only two fitting parameters: $R$ and the effective ``sound speed,'' which encapsulates small-scale physics. This is tested with two suites of cosmological simulations across a broad range of cosmologies and found to be highly accurate. Due to its physical motivation, the statistics can be easily extended beyond the power spectrum; we additionally derive the one-loop covariance matrices of cluster counts and their combination with the matter power spectrum. This yields a significantly better fit to simulations than previous models, and includes a new model for supersample effects, which is rigorously tested with separate universe simulations. At low redshift, we find a significant ($\ensuremath{\sim}10%$) exclusion covariance from accounting for the finite size of halos which has not previously been modeled. Such power spectrum and covariance models will enable joint analysis of upcoming large-scale structure surveys, gravitational lensing surveys, and cosmic microwave background maps on scales down to the nonlinear scale. We provide a publicly released python code.

2D-FFTLog: efficient computation of real-space covariance matrices for galaxy clustering and weak lensing

ABSTRACT Accurate covariance matrices for two-point functions are critical for inferring cosmological parameters in likelihood analyses of large-scale structure surveys. Among various approaches to obtaining the covariance, analytic computation is much faster and less noisy than estimation from data or simulations. However, the transform of covariances from Fourier space to real space involves integrals with two Bessel integrals, which are numerically slow and easily affected by numerical uncertainties. Inaccurate covariances may lead to significant errors in the inference of the cosmological parameters. In this paper, we introduce a 2D-FFTLog algorithm for efficient, accurate, and numerically stable computation of non-Gaussian real-space covariances for both 3D and projected statistics. The 2D-FFTLog algorithm is easily extended to perform real-space bin-averaging. We apply the algorithm to the covariances for galaxy clustering and weak lensing for a Dark Energy Survey Year 3-like and a Rubin Observatory’s Legacy Survey of Space and Time Year 1-like survey, and demonstrate that for both surveys, our algorithm can produce numerically stable angular bin-averaged covariances with the flat sky approximation, which are sufficiently accurate for inferring cosmological parameters. The code CosmoCov for computing the real-space covariances with or without the flat-sky approximation is released along with this paper.

The impact of relativistic effects on the 3D Quasar-Lyman-α cross-correlation

We study the impact of relativistic effects in the 3-dimensional cross-correlation between Lyman-α forest and quasars. Apart from the relativistic effects, which are dominated by the Doppler contribution, several systematic effects are also included in our analysis (intervening metals, unidentified high column density systems, transverse proximity effect and effect of the UV fluctuations). We compute the signal-to-noise ratio for the Baryonic Oscillation Spectroscopic Survey (BOSS), the extended Baryonic Oscillation Spectroscopic Survey (eBOSS) and the Dark Energy Spectroscopic Instrument (DESI) surveys, showing that DESI will be able to detect the Doppler contribution in a Large Scale Structure (LSS) survey for the first time, with a S/N >7 for rmin > 10 Mpc/h, where rmin denotes the minimum comoving separation between sources. We demonstrate that several physical parameters, introduced to provide a full modelling of the cross-correlation function, are affected by the Doppler contribution. By using a Fisher matrix approach, we establish that if the Doppler contribution is neglected in the data analysis, the derived parameters will be shifted by a non-negligible amount for the upcoming surveys.

Neutrino effects on the morphology of cosmic large-scale structure

In this work, we propose a powerful probe of neutrino effects on the large-scale structure (LSS) of the Universe, i.e., Minkowski functionals (MFs). The morphology of LSS can be fully described by four MFs. This tool, with strong statistical power, is robust to various systematics and can comprehensively probe all orders of N-point statistics. By using a pair of high-resolution N-body simulations, for the first time, we comprehensively studied the subtle neutrino effects on the morphology of LSS. For an ideal LSS survey of volume $\sim1.73$ Gpc$^3$/$h^3$, neutrino signals are mainly detected from void regions with a significant level up to $\thicksim 10\sigma$ and $\thicksim 300\sigma$ for CDM and total matter density fields, respectively. This demonstrates its enormous potential for much improving the neutrino mass constraint in the data analysis of up-coming ambitious LSS surveys.

Forecast for FAST: from galaxies survey to intensity mapping

ABSTRACT The Five-Hundred-Meter Aperture Spherical Radio Telescope (FAST) is the largest single-dish radio telescope in the world. In this paper, we make forecast on the FAST H i large-scale structure survey by mock observations. We consider a drift scan survey with the L-band 19 beam receiver, which may be commensal with the pulsar search and Galactic H i survey. We also consider surveys at lower frequency, using either the current single feed wide-band receiver or a future multibeam phased array feed (PAF) in the UHF band. We estimate the number density of detected H i galaxies and the measurement error in positions and the precision of the surveys are evaluated using both Fisher matrix and simulated observations. The measurement error in the H i galaxy power spectrum is estimated, and we find that the error is relatively large even at moderate redshifts, as the number of positively detected galaxies drops drastically with increasing redshift. However, good cosmological measurement could be obtained with the intensity mapping technique where the large scale H i distribution is measured without resolving individual galaxies. The figure of merit for the dark energy equation of state with different observation times is estimated, and we find that with the existing L-band multibeam receiver, a good measurement of low redshift large-scale structure can be obtained, which complements the existing optical surveys. With a PAF in the UHF band, the constraint can be much stronger, reaching the level of a dark energy task force stage IV experiment.

Cosmological Constraints from the Redshift Dependence of the Alcock–Paczynski Effect: Possibility of Estimating the Nonlinear Systematics Using Fast Simulations

Abstract The tomographic Alcock–Paczynski (AP) method is so far the best method in separating the AP signal from the redshift space distortion (RSD) effects and deriving powerful constraints on cosmological parameters using the ≲ 40 h − 1 Mpc clustering region. To guarantee that the method can be easily applied to the future large-scale structure surveys, we study the possibility of estimating the systematics of the method using the fast simulation method. The major contribution of the systematics comes from the nonzero redshift evolution of the RSD effects, which is quantified by ξ ˆ Δ s ( μ , z ) in our analysis, and estimated using the BigMultidark exact N-body simulation and approximate COmoving Lagrangian Acceleration (COLA) simulation samples. We find about 5%/10% evolution when comparing the ξ ˆ Δ s ( μ , z ) measured as z = 0.5/z = 1 to the measurements at z = 0. We checked the inaccuracy in the 2pCFs computed using COLA, and find it 5–10 times smaller than the intrinsic systematics of the tomographic AP method, indicating that using COLA to estimate the systematics is good enough. Finally, we test the effect of halo bias, and find ≲1.5% change in ξ ˆ Δ s when varying the halo mass within the range of 2 × 1012–1014 M ⊙. We will perform more studies to achieve an accurate and efficient estimation of the systematics in the redshift range of z = 0–1.5.

Modelling the matter bispectrum at small scales in modified gravity

Future large-scale structure surveys will measure three-point statistics with high statistical significance. This will offer significant improvements on our understanding of gravity, provided we can model these statistics accurately. {We assess the performance of several schemes for theoretical modelling of the matter bispectrum, including halo-model based approaches and fitting formulae. We compare the model predictions against N-body simulations, considering scales up to kmax = 4 h/Mpc, well into non-linear regime of structure formation. Focusing on the equilateral configuration, we conduct this analysis for three theories of gravity: general relativity, f(R) gravity, and the DGP braneworld model. Additionally, we compute the lensing convergence bispectrum for these models. We find that all current modelling prescriptions in modified gravity, in particular for theories with scale-dependent linear growth, fail to attain the accuracy required by the precision of the Stage IV surveys such as Euclid. Among these models, we find that a halo-model corrected fitting formula achieves the best overall performance.}

The bias of dark matter tracers: assessing the accuracy of mapping techniques

ABSTRACT We present a comparison between approximated methods for the construction of mock catalogues based on the halo-bias mapping technique. To this end, we use as reference a high-resolution N-body simulation of 38403 dark matter particles on a 400 h−1 Mpc cube box from the Multidark suite. In particular, we explore parametric versus non-parametric bias mapping approaches and compare them at reproducing the halo distribution in terms of the two- and three-point statistics down to $\sim 10^8\, {\rm M}_{\odot }\, h^{-1}$ halo masses. Our findings demonstrate that the parametric approach remains inaccurate even including complex deterministic and stochastic components. On the contrary, the non-parametric one is indistinguishable from the reference N-body calculation in the power spectrum beyond $k=1\, h\, {\rm Mpc}^{-1}$, and in the bispectrum for typical configurations relevant to baryon acoustic oscillation analysis. We conclude that approaches which extract the full bias information from N-body simulations in a non-parametric fashion are ready for the analysis of the new generation of large-scale structure surveys.

Developing a Large-Scale Cryogenic System for the Simultaneous Operation of Three Detector Focal Planes in TolTEC, A New Multichroic Imaging Polarimeter

TolTEC is an upcoming millimeter-wave imaging polarimeter designed to fill the focal plane of the 50-m-diameter Large Millimeter Telescope (LMT). Combined with the LMT, TolTEC will offer high-angular-resolution (5$$''$$–10$$''$$) simultaneous, polarization-sensitive observations in three wavelength bands: 1.1, 1.4, and 2.0 mm. Additionally, TolTEC will feature mapping speeds greater than $$2 \,\hbox {deg}^2/\hbox {mJy}^2/\hbox {h}$$, thus enabling wider surveys of large-scale structure, galaxy evolution, and star formation. These improvements are only possible through the integration of approximately 7000 low-noise, high-responsivity superconducting Lumped Element Kinetic Inductance Detectors. Utilizing three focal planes of detector arrays requires the design, fabrication, and characterization of a unique, large-scale cryogenic system. Based on thermal models and expected photon loading, the focal planes must have a base operational temperature below 150 mK. To achieve this base temperature, TolTEC utilizes two cryocoolers, a Cryomech pulse tube cooler and an Oxford Instruments dilution refrigerator, to establish four thermal stages: 45 K, 4 K, 1 K, and 100 mK. During the design phase, we developed an object-oriented Python code to model the heat loading on each stage as well as the thermal gradients throughout the system. This model has allowed us to improve thermal gradients in the system as well as locate areas of poor thermal conductivity prior to ending a cooldown. The results of our model versus measurements from our cooldowns will be presented along with a detailed overview of TolTEC’s cryogenic system. We anticipate TolTEC to be commissioned at the LMT by Spring 2020.

How sound are our ultralight axion approximations?

Ultralight axions (ULAs) are a promising dark-matter candidate. ULAs may have implications for small-scale challenges to the $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ model and arise in string scenarios. ULAs are already constrained by cosmic microwave background (CMB) experiments and large-scale structure surveys, and will be probed with much greater sensitivity by future efforts. It is challenging to compute observables in ULA scenarios with sufficient speed and accuracy for cosmological data analysis because the ULA field oscillates rapidly. In past work, an effective fluid approximation has been used to make these computations feasible. Here this approximation is tested against an exact solution of the ULA equations, comparing the induced error of CMB observables with the sensitivity of current and future experiments. In the most constrained mass range for a ULA dark-matter component (${10}^{\ensuremath{-}27}\text{ }\text{ }\mathrm{eV}\ensuremath{\le}{m}_{\mathrm{ax}}\ensuremath{\le}{10}^{\ensuremath{-}25}\text{ }\text{ }\mathrm{eV}$), the induced bias on the allowed ULA fraction of dark matter from Planck data is less than $1\ensuremath{\sigma}$. In the cosmic-variance limit (including temperature and polarization data), the bias is $\ensuremath{\lesssim}2\ensuremath{\sigma}$ for primary CMB anisotropies, with more severe biases (as high as $\ensuremath{\sim}4\ensuremath{\sigma}$) resulting for less reliable versions of the effective fluid approximation. If all of the standard cosmological parameters are fixed by other measurements, the expected bias rises to $4\ensuremath{-}20\ensuremath{\sigma}$ (well beyond the validity of the Fisher approximation), though the required level of degeneracy breaking will not be achieved by any planned surveys.

Spectroscopic confirmation of a mature galaxy cluster at aredshift of 2.

Galaxy clusters are the most massive virialized structures in the Universe and are formed through the gravitational accretion of matter over cosmic time1. The discovery2 of an evolved galaxy cluster at redshift z=2, corresponding to a look-back time of 10.4 billion years, provides an opportunity to study its properties. The galaxy cluster XLSSC122 was originally detected as a faint, extended X-ray source in the XMM Large Scale Structure survey and was revealed to be coincident with a compact over-density of galaxies2 with photometric redshifts of 1.9±0.2. Subsequent observations3 at millimetre wavelengths detected a Sunyaev-Zel'dovich decrement along the line of sight to XLSSC122, thus confirming the existence of hot intracluster gas, while deep imaging spectroscopy from the European Space Agency's X-ray Multi-Mirror Mission (XMM-Newton) revealed4 an extended, X-ray-bright gaseous atmosphere with a virial temperature of 60 millionKelvin, enriched with metals to the same extent as are local clusters. Here we report optical spectroscopic observations of XLSSC122 and identify 37 member galaxies at a mean redshift of 1.98, corresponding to a look-back time of 10.4 billion years. We use photometry to determine a mean, dust-free stellar age of 2.98 billion years, indicating that star formation commenced in these galaxies at a mean redshift of 12, when the Universe was only 370 million years old. The full range of inferred formation redshifts, including the effects of dust, covers the interval from 7 to 13. These observations confirm that XLSSC122 is a remarkably mature galaxy cluster with both evolved stellar populations in the member galaxies and a hot, metal-rich gas composing the intracluster medium.

Sheer shear: weak lensing with one mode

3D data compression techniques can be used to determine the natural basis of radial eigenmodes that encode the maximum amount of information in a tomographic large-scale structure survey. We explore the potential of the Karhunen-Lo\`eve decomposition in reducing the dimensionality of the data vector for cosmic shear measurements, and apply it to the final data from the \cfh survey. We find that practically all of the cosmological information can be encoded in one single radial eigenmode, from which we are able to reproduce compatible constraints with those found in the fiducial tomographic analysis (done with 7 redshift bins) with a factor of ~30 fewer datapoints. This simplifies the problem of computing the two-point function covariance matrix from mock catalogues by the same factor, or by a factor of ~800 for an analytical covariance. The resulting set of radial eigenfunctions is close to ell-independent, and therefore they can be used as redshift-dependent galaxy weights. This simplifies the application of the Karhunen-Lo\`eve decomposition to real-space and Fourier-space data, and allows one to explore the effective radial window function of the principal eigenmodes as well as the associated shear maps in order to identify potential systematics. We also apply the method to extended parameter spaces and verify that additional information may be gained by including a second mode to break parameter degeneracies. The data and analysis code are publicly available at https://github.com/emiliobellini/kl_sample.

BE-HaPPY: bias emulator for halo power spectrum including massive neutrinos

We study the clustering properties of dark matter haloes in real- and redshift-space in cosmologies with massless and massive neutrinos through a large set of state-of-the-art N-body simulations. We provide quick and easy-to-use prescriptions for the halo bias on linear and mildly non-linear scales, both in real and redshift-space, which are valid also for massive neutrinos cosmologies. Finally we present a halo bias emulator, BE-HaPPY, calibrated on the N-body simulations, which is fast enough to be used in the standard Markov Chain Monte Carlo approach to cosmological inference. For a fiducial standard ΛCDM cosmology BE-HaPPY reproduces the simulation inputs with percent or sub-percent accuracy for the halo mass cuts it is calibrated on (M>{5×1011, 1012, 3× 1012, 1013} h-1 M⊙) on the scales of interest (linear and well into the mildly non-linear regime). The approach presented here represents a well defined route to meeting the halo-bias accuracy requirements for the analysis of next-generation large-scale structure surveys. The software BE-HaPPY can run both in emulator mode and in calibration mode, on user-supplied simulations outputs, and is made publicly available.

Exact joint likelihood of pseudo-Cℓ estimates from correlated Gaussian cosmological fields

ABSTRACT We present the exact joint likelihood of pseudo-Cℓ power spectrum estimates measured from an arbitrary number of Gaussian cosmological fields. Our method is applicable to both spin-0 fields and spin-2 fields, including a mixture of the two, and is relevant to cosmic microwave background (CMB), weak lensing, and galaxy clustering analyses. We show that Gaussian cosmological fields are mixed by a mask in such a way that retains their Gaussianity and derive exact expressions for the covariance of the cut-sky spherical harmonic coefficients, the pseudo-aℓms, without making any assumptions about the mask geometry. We then show that each auto or cross-pseudo-Cℓ estimator can be written as a quadratic form, and apply the known joint distribution of quadratic forms to obtain the exact joint likelihood of a set of pseudo-Cℓ estimates in the presence of an arbitrary mask. We show that the same formalism can be applied to obtain the exact joint likelihood of quadratic maximum likelihood power spectrum estimates. Considering the polarization of the CMB as an example, we show using simulations that our likelihood recovers the full, exact multivariate distribution of EE, BB, and EB pseudo-Cℓ power spectra. Our method provides a route to robust cosmological constraints from future CMB and large-scale structure surveys in an era of ever-increasing statistical precision.

The Outer Rim Simulation: A Path to Many-core Supercomputers

Abstract We describe the Outer Rim cosmological simulation, one of the largest high-resolution N-body simulations performed to date, aimed at promoting science to be carried out with large-scale structure surveys. The simulation covers a volume of (4.225 Gpc)3 and evolves more than one trillion particles. It was executed on Mira, a BlueGene/Q system at the Argonne Leadership Computing Facility. We discuss some of the computational challenges posed by a system such as Mira, a many-core supercomputer, and how the simulation code, Hardware/Hybrid Accelerated Cosmology Code, has been designed to overcome these challenges. We have carried out a large range of analyses on the simulation data and we report on the results as well as the data products that have been generated. The full data set generated by the simulation totals more than 5 PB of data, making curation and handling of the data a large challenge in itself. The simulation results have been used to generate synthetic catalogs for large-scale structure surveys, including Dark Energy Spectroscopic Instrument and eBOSS, as well as experiments on the cosmic microwave background. A detailed catalog for the data challenges of the Large Synoptic Survey Telescope Dark Energy Science Collaboration has been created as well. We publicly release some of the Outer Rim halo catalogs, downsampled particle information, and lightcone data.

Tomographic weak lensing bispectrum: a thorough analysis towards the next generation of galaxy surveys

ABSTRACT We address key points for an efficient implementation of likelihood codes for modern weak lensing large-scale structure surveys. Specifically, we focus on the joint weak lensing convergence power spectrum–bispectrum probe and we tackle the numerical challenges required by a realistic analysis. Under the assumption of (multivariate) Gaussian likelihoods, we have developed a high performance code that allows highly parallelized prediction of the binned tomographic observables and of their joint non-Gaussian covariance matrix accounting for terms up to the six-point correlation function and supersample effects. This performance allows us to qualitatively address several interesting scientific questions. We find that the bispectrum provides an improvement in terms of signal-to-noise ratio (S/N) of about 10 per cent on top of the power spectrum, making it a non-negligible source of information for future surveys. Furthermore, we are capable to test the impact of theoretical uncertainties in the halo model used to build our observables; with presently allowed variations we conclude that the impact is negligible on the S/N. Finally, we consider data compression possibilities to optimize future analyses of the weak lensing bispectrum. We find that, ignoring systematics, five equipopulated redshift bins are enough to recover the information content of a Euclid-like survey, with negligible improvement when increasing to 10 bins. We also explore principal component analysis and dependence on the triangle shapes as ways to reduce the numerical complexity of the problem.

Anisotropic halo assembly bias and redshift-space distortions

We study the effect of large-scale tidal fields on internal halo properties using a set of N-body simulations. We measure significant cross-correlations between large-scale tidal fields and several non-scalar halo properties: shapes, velocity dispersion, and angular momentum. Selection effects that couple to these non-scalar halo properties can produce anisotropic clustering even in real-space. We investigate the size of this effect and show that it can produce a non-zero quadrupole similar in size to the one generated by linear redshift-space distortions (RSD). Finally, we investigate the clustering properties of halos identified in redshift-space and find enormous deviations from the standard linear RSD model, again caused by anisotropic assembly bias. These effects could contaminate the values of cosmological parameters inferred from the observed redshift-space clustering of galaxies, groups, or 21cm emission from atomic hydrogen, if their selection depends on properties affected by halo assembly bias. We briefly discuss ways in which this effect can be measured in existing and future large-scale structure surveys.

How Far Can We Push Deconvolution? A SCUBA-2 Test Case

How far can we use multi-wavelength cross-identifications to deconvolve far-infrared images? In this short research note I explore a test case of CLEAN deconvolutions of simulated confused 850 micron SCUBA-2 data, and explore the possible scientific applications of combining this data with ostensibly deeper TolTEC Large Scale Structure (LSS) survey 1.1mm-2mm data. I show that the SCUBA-2 can be reconstructed to the 1.1mm LMT resolution and achieve an 850 micron deconvolved sensitivity of 0.7 mJy RMS, an improvement of at least ~1:5x over naive point source filtered images. The TolTEC/SCUBA-2 combination can constrain cold (<10K) observed-frame colour temperatures, where TolTEC alone cannot.

Cosmic web anisotropy is the primary indicator of halo assembly bias

ABSTRACT The internal properties of dark matter haloes correlate with the large-scale halo clustering strength at fixed halo mass – an effect known as assembly bias – and are also strongly affected by the local, non-linear cosmic web. Characterizing a halo’s local web environment by its tidal anisotropy α at scales approximately four times the halo radius, we demonstrate that these multiscale correlations represent two distinct statistical links: one between the internal property and α, and the other between α and large-scale (${\gtrsim}30\, h^{-1}\, {\rm Mpc}$) halo bias b1. We focus on scalar internal properties of haloes related to formation time (concentration cvir), shape (mass ellipsoid asphericity c/a), velocity dispersion structure (velocity ellipsoid asphericity cv/av and velocity anisotropy β), and angular momentum (dimensionless spin λ) in the mass range $8\times 10^{11}\lesssim M_{\rm vir}/(\, h^{-1}\, \mathrm{M}_{\odot })\lesssim 5\times 10^{14}$. Using conditional correlation coefficients and other detailed tests, we show that the joint distribution of α, b1, and any of the internal properties c ∈ {β, cv/av, c/a, cvir, λ} is consistent with p(α, b1, c) ≃ p(α)p(b1|α)p(c|α), at all but the largest masses. Thus, the assembly bias trends c↔b1 reflect the two fundamental correlations c↔α and b1↔α. Our results are unaffected by the exclusion of haloes with recent major merger events or splashback objects, although the latter are distinguished by the fact that α does not explain their assembly bias trends. The overarching importance of α provides a new perspective on the nature of assembly bias of distinct haloes, with potential ramifications for incorporating realistic assembly bias effects into mock catalogues of future large-scale structure surveys and for detecting galaxy assembly bias.

Dark energy perturbations in N-body simulations

We present N-body simulations which are fully compatible with general relativity, with dark energy consistently included at both the background and perturbation level. We test our approach for dark energy parameterised as both a fluid, and using the parameterised post-Friedmann (PPF) formalism. In most cases, dark energy is very smooth relative to dark matter so that its leading effect on structure formation is the change to the background expansion rate. This can be easily incorporated into Newtonian N-body simulations by changing the Friedmann equation. However, dark energy perturbations and relativistic corrections can lead to differences relative to Newtonian N-body simulations at the tens of percent level for scales k < (10−3–10−2) Mpc−1, and given the accuracy of upcoming large scale structure surveys such effects must be included. In this paper we will study both effects in detail and highlight the conditions under which they are important. We also show that our N-body simulations exactly reproduce the results of the Boltzmann solver CLASS for all scales which remain linear.