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Cosmic void has been proven to be an effective cosmological probe of the large-scale structure (LSS). However, since voids are usually identified in spectroscopic galaxy surveys, they are generally limited to low number density and redshift. We propose to utilize the clustering of two-dimensional (2D) voids identified using Voronoi tessellation and watershed algorithm without any shape assumption to explore the LSS. We generate mock galaxy and void catalogs for the next-generation Stage IV photometric surveys in $z = 0.8-2.0$ from simulations, develop the 2D void identification method, and construct the theoretical model to fit the 2D watershed void and galaxy angular power spectra. We find that our method can accurately extract the cosmological information, and the constraint accuracies of some cosmological parameters from the 2D watershed void clustering are even comparable to the galaxy angular clustering case, which can be further improved by as large as $\sim30\%$ in the void and galaxy joint constraints. This indicates that the 2D void clustering is a good complement to galaxy angular clustering measurements, especially for the forthcoming Stage IV surveys that detect high-redshift universe., Comment: 7 pages, 4 figures, 1 table

Accurately characterizing the true redshift (true-$z$) distribution of a photometric redshift (photo-$z$) sample is critical for cosmological analyses in imaging surveys. Clustering-based techniques, which include clustering-redshift (CZ) and self-calibration (SC) methods--depending on whether external spectroscopic data are used--offer powerful tools for this purpose. In this study, we explore the joint inference of the true-$z$ distribution by combining SC and CZ (denoted as SC+CZ). We derive simple multiplicative update rules to perform the joint inference. By incorporating appropriate error weighting and an additional weighting function, our method shows significant improvement over previous algorithms. We validate our approach using a DES Y3 mock catalog. The true-$z$ distribution estimated through the combined SC+CZ method is generally more accurate than using SC or CZ alone. To account for the different constraining powers of these methods, we assign distinct weights to the SC and CZ contributions. The optimal weights, which minimize the distribution error, depend on the relative constraining strength of the SC and CZ data. Specifically, for a spectroscopic redshift sample that represents 1% of the photo-$z$ sample, the optimal combination reduces the total error by 20% (40%) compared to using CZ (SC) alone, and it keeps the bias in mean redshift [$\Delta \bar{z} / (1 + z) $] at the level of 0.3%. Furthermore, when CZ data is only available in the low-$z$ range and the high-$z$ range relies solely on SC data, SC+CZ enables consistent estimation of the true-$z$ distribution across the entire redshift range. Our findings demonstrate that SC+CZ is an effective tool for constraining the true-$z$ distribution, paving the way for clustering-based methods to be applied at $z\gtrsim 1$., Comment: 17 pages, 13 figures

Void number counts (VNC) indicates the number of low-density regions in the large-scale structure (LSS) of the Universe, and we propose to use it as an effective cosmological probe. By generating the galaxy mock catalog based on Jiutian simulations and considering the spectroscopic survey strategy and instrumental design of the China Space Station Telescope (CSST), which can reach a magnitude limit $\sim$23 AB mag and spectral resolution $R\gtrsim200$ with a sky coverage 17,500 deg$^2$, we identify voids using the watershed algorithm without any assumption of void shape, and obtain the mock void catalog and data of the VNC in six redshift bins from $z=0.3$ to1.3. We use the Markov Chain Monte Carlo (MCMC) method to constrain the cosmological and VNC parameters. The void linear underdensity threshold $\delta_{\rm v}$ in the theoretical model is set to be a free parameter at a given redshift to fit the VNC data and explore its redshift evolution. We find that, the VNC can correctly derive the cosmological information, and the constraint strength on the cosmological parameters is comparable to that from the void size function (VSF) method, which can reach a few percentage levels in the CSST full spectroscopic survey. This is because that, since the VNC is not sensitive to void shape, the modified theoretical model can match the data better by integrating over void features, and more voids could be included in the VNC analysis by applying simpler selection criteria, which will improve the statistical significance. It indicates that the VNC can be an effective cosmological probe for exploring the LSS., Comment: 8 pages, 5 figures, 2 tables. Accepted for publication in MNRAS

The void power spectrum is related to the clustering of low-density regions in the large-scale structure (LSS) of the Universe, and can be used as an effective cosmological probe to extract the information of the LSS. We generate the galaxy mock catalogs from Jiutian simulation, and identify voids using the watershed algorithm for studying the cosmological constraint strength of the China Space Station Telescope (CSST) spectroscopic survey. The galaxy and void auto power spectra and void-galaxy cross power spectra at $z=0.3$, 0.6, and 0.9 are derived from the mock catalogs. To fit the full power spectra, we propose to use the void average effective radius at a given redshift to simplify the theoretical model, and adopt the Markov Chain Monte Carlo (MCMC) technique to implement the constraints on the cosmological and void parameters. The systematical parameters, such as galaxy and void biases, and noise terms in the power spectra are also included in the fitting process. We find that our theoretical model can correctly extract the cosmological information from the galaxy and void power spectra, which demonstrates its feasibility and effectivity. The joint constraint accuracy of the cosmological parameters can be improved by $\sim20\%$ compared to that from the galaxy power spectrum only. The fitting results of the void density profile and systematical parameters are also well constrained and consistent with the expectation. This indicates that the void clustering measurement can be an effective complement to the galaxy clustering probe, especially for the next generation galaxy surveys., Comment: 12 pages, 5 figures, 2 tables. Accepted for publication in ApJ

We use a galaxy sample derived from the DECaLS DR9 to measure the Baryonic Acoustic Oscillations (BAO). The magnitude-limited sample consists of 10.6 million galaxies in an area of 4974 deg$^2$ over the redshift range of [0.6, 1]. A key novelty of this work is that the true redshift distribution of the photo-$z$ sample is derived from the self calibration method, which determines the true redshift distribution using the clustering information of the photometric data alone. Through the angular correlation function in four tomographic bins, we constrain the BAO scale dilation parameter $\alpha$ to be $1.025\pm 0.033 $, consistent with the fiducial Planck cosmology. Alternatively, the ratio between the comoving angular diameter distance and the sound horizon, $D_{\rm M} / r_{\rm s}$ is constrained to be $18.94 \pm 0.61 $ at the effective redshift of 0.749. We corroborate our results with the true redshift distribution obtained from a weighted spectroscopic sample, finding very good agreement. We have conducted a series of tests to demonstrate the robustness of the measurement. Our work demonstrates that the self calibration method can effectively constrain the true redshift distribution in cosmological applications, especially in the context of photometric BAO measurement., Comment: 13 pages, 10 figures, matched to the published version

Void size function (VSF) contains information of the cosmic large-scale structure (LSS), and can be used to derive the properties of dark energy and dark matter. We predict the VSFs measured from the spectroscopic galaxy survey operated by the China Space Station Telescope (CSST), and study the strength of cosmological constraint. We employ a high-resolution Jiutian simulation to get CSST galaxy mock samples based on an improved semi-analytical model. We identify voids from this galaxy catalog using the watershed algorithm without assuming a spherical shape, and estimate the VSFs at different redshift bins from $z=0.5$ to 1.1. We propose a void selection method based on the ellipticity, and assume the void linear underdensity threshold $\delta_{\rm v}$ in the theoretical model is redshift-dependent and set it as a free parameter in each redshift bin. The Markov Chain Monte Carlo (MCMC) method is adopted to implement the constraints on the cosmological and void parameters. We find that the CSST VSF measurement can constrain the cosmological parameters to a few percent level. The best-fit values of $\delta_{\rm v}$ are ranging from $\sim-0.4$ to $-0.1$ as the redshift increases from 0.5 to 1.1, which has a distinct difference from the theoretical calculation with $\delta_{\rm v}\simeq-2.7$ assuming the spherical evolution and using particles as tracer. Our method can provide a good reference for void identification and selection in the VSF analysis of the spectroscopic galaxy surveys., Comment: 10 pages, 7 figures, 3 tables. Accepted for publication in MNRAS

The reconstruction method has been widely employed to improve the Baryon Acoustic Oscillations (BAO) measurement in spectroscopic survey data analysis. In this study, we explore the reconstruction of the BAO signals in the realm of photometric data. By adapting the Zel'dovich reconstruction technique, we develop a formalism to reconstruct the transverse BAO in the presence of photo-$z$ uncertainties \change{under the plane-parallel approximation}. We access the performance of the BAO reconstruction through comoving $N$-body simulations. The transverse reconstruction potential can be derived by solving a 2D potential equation, with the surface density and the radial potential contribution acting as the source terms. The solution is predominantly determined by the surface density. As is evident in dense samples, such as the matter field, the transverse BAO reconstruction can enhance both the strength of the BAO signals and their cross correlation with the initial conditions. At $z=0$, the cross correlation is increased by a factor of 1.2 at $ k_\perp = 0.2 \, \mathrm{Mpc}^{-1}h $ and 1.4 at $ k_\perp = 0.3 \, \mathrm{Mpc}^{-1}h $, respectively. We contrast the 2D potential results with the 3D Poisson equation solution, wherein we directly solve the potential equation using the position in photo-$z$ space, and find good agreement. Additionally, we examine the impact of various conditions, such as the smoothing scales and the level of photo-$z$ uncertainties, on the reconstruction results. We envision the straightforward application of this method to survey data., Comment: 15 pages, 13 figures, matched to the published version

Local primordial non-Gaussianity (PNG) is a promising observable of the underlying physics of inflation, characterised by $f_{\rm NL}^{\rm loc}$. We present the methodology to measure $f_{\rm NL}^{\rm loc}$ from the Dark Energy Survey (DES) data using the 2-point angular correlation function (ACF) with scale-dependent bias. One of the focuses of the work is the integral constraint. This condition appears when estimating the mean number density of galaxies from the data and is key in obtaining unbiased $f_{\rm NL}^{\rm loc}$ constraints. The methods are analysed for two types of simulations: $\sim 246$ GOLIAT-PNG N-body small area simulations with $f_{\rm NL}$ equal to -100 and 100, and 1952 Gaussian ICE-COLA mocks with $f_{\rm NL}=0$ that follow the DES angular and redshift distribution. We use the ensemble of GOLIAT-PNG mocks to show the importance of the integral constraint when measuring PNG, where we recover the fiducial values of $f_{\rm NL}$ within the $1\sigma$ when including the integral constraint. In contrast, we found a bias of $\Delta f_{\rm NL}\sim 100$ when not including it. For a DES-like scenario, we forecast a bias of $\Delta f_{\rm NL} \sim 23$, equivalent to $1.8\sigma$, when not using the IC for a fiducial value of $f_{\rm NL}=100$. We use the ICE-COLA mocks to validate our analysis in a realistic DES-like setup finding it robust to different analysis choices: best-fit estimator, the effect of IC, BAO damping, covariance, and scale choices. We forecast a measurement of $f_{\rm NL}$ within $\sigma(f_{\rm NL})=31$ when using the DES-Y3 BAO sample, with the ACF in the $1\ {\rm deg}<\theta<20\ {\rm deg}$ range., Comment: Version after MNRAS reviewer comments. Improved discussion in Section 7. 16 pages, 11 figures

China Space Station Telescope (CSST) is a forthcoming powerful Stage IV space-based optical survey equipment. It is expected to explore a number of important cosmological problems in extremely high precision. In this work, we focus on investigating the constraints on neutrino mass and other cosmological parameters under the model of cold dark matter with a constant equation of state of dark energy ($w$CDM), using the mock data from the CSST photometric galaxy clustering and cosmic shear surveys (i.e. 3$\times$2pt). The systematics from galaxy bias, photometric redshift uncertainties, intrinsic alignment, shear calibration, baryonic feedback, non-linear, and instrumental effects are also included in the analysis. We generate the mock data based on the COSMOS catalog considering the instrumental and observational effects of the CSST, and make use of the Markov Chain Monte Carlo (MCMC) method to perform the constraints. Comparing to the results from current similar measurements, we find that CSST 3$\times$2pt surveys can improve the constraints on the cosmological parameters by one order of magnitude at least. We can obtain an upper limit for the sum of neutrino mass $\Sigma m_{\nu} \lesssim 0.36$ (0.56) eV at 68\% (95\%) confidence level, and $\Sigma m_{\nu} \lesssim 0.23$ (0.29) eV at 68\% (95\%) confidence level if ignore the baryonic effect, which is comparable to the {\it Planck} results and much better than the current photometric surveys. This indicates that the CSST photometric surveys can provide stringent constraints on the neutrino mass and other cosmological parameters, and the results also can be further improved by including data from other kinds of CSST cosmological surveys., Comment: 15 pages, 13 figures, 2 tables. Accepted for publication in MNRAS

Photometric data can be analyzed using the three-dimensional correlation function $\xi_{\rm p}$ to extract cosmological information via e.g., measurement of the Baryon Acoustic Oscillations (BAO). Previous studies modeled $\xi_{\rm p} $ assuming a Gaussian photo-$z$ approximation. In this work we improve the modeling by incorporating realistic photo-$z$ distribution. We show that the position of the BAO scale in $\xi_{\rm p}$ is determined by the photo-$z$ distribution and the Jacobian of the transformation. The latter diverges at the transverse scale of the separation $s_\perp $, and it explains why $\xi_{\rm p } $ traces the underlying correlation function at $s_\perp $, rather than $s$, when the photo-$z$ uncertainty $ \sigma_z / (1+ z) \gtrsim 0.02$. We also obtain the Gaussian covariance for $\xi_{\rm p}$. Due to photo-$z$ mixing, the covariance of $\xi_{\mathrm{p}}$ shows strong off-diagonal elements. The high correlation of the data causes some issues to the data fitting. Nonetheless, we find that either it can be solved by suppressing the largest eigenvalues of the covariance or it is not directly related to the BAO. We test our BAO fitting pipeline using a set of mock catalogs. The data set is dedicated for Dark Energy Survey Year 3 (DES Y3) BAO analyses and includes realistic photo-$z$ distributions. The theory template is in good agreement with mock measurement. Based on the DES Y3 mocks, $\xi_{\rm p}$ statistic is forecast to constrain the BAO shift parameter $\alpha$ to be $1.001 \pm 0.023$, which is well consistent with the corresponding constraint derived from the angular correlation function measurements. Thus $\xi_{\rm p}$ offers a competitive alternative for the photometric data analyses., Comment: 20 pages, 17 figures, match to the published version

We investigate the application of volume statistics to probe the distribution of underdense regions in the large-scale structure of the Universe. This statistic measures the distortion of Eulerian volume elements relative to Lagrangian ones and can be built from tracer particles using tessellation methods. We apply Voronoi and Delaunay tessellation to study the clustering properties of density and volume statistics. Their level of shot-noise contamination is similar, as both methods take into account all available tracer particles in the field estimator. The tessellation causes a smoothing effect in the power spectrum, which can be approximated by a constant window function on large scales. The clustering bias of the volume statistic with respect to the dark matter density field is determined and found to be negative. We further identify the Baryon Acoustic Oscillation (BAO) feature in the volume statistic. Apart from being smoothed out on small scales, the BAO is present in the volume power spectrum as well, without any systematic bias. These observations suggest that the exploitation of volume statistics as a complementary probe of cosmology is very promising., Comment: 20 pages, 13 figures, match to the published version

Cosmic voids are biased tracers of the large-scale structure of the universe. Separate universe simulations (SUS) enable accurate measurements of this biasing relation by implementing the peak-background split (PBS). In this work, we apply the SUS technique to measure the void bias parameters. We confirm that the PBS argument works well for underdense tracers. The response of the void size distribution depends on the void radius. For voids larger (smaller) than the size at the peak of the distribution, the void abundance responds negatively (positively) to a long wavelength mode. The linear bias from the SUS is in good agreement with the cross power spectrum measurement on large scales. Using the SUS, we have detected the quadratic void bias for the first time in simulations. We find that $ b_2 $ is negative when the magnitude of $ b_1 $ is small, and that it becomes positive and increases rapidly when $ |b_1| $ increases. We compare the results from voids identified in the halo density field with those from the dark matter distribution, and find that the results are qualitatively similar, but the biases generally shift to the larger voids sizes., Comment: 16 pages, 11 figures. Match to the published version

We study the large-scale bias parameter of cosmic voids with primordial non-Gaussian (PNG) initial conditions of the local type. In this scenario, the dark matter halo bias exhibits a characteristic scale dependence on large scales, which has been recognized as one of the most promising probes of the local PNG. Using a suite of $N$-body simulations with Gaussian and non-Gaussian initial conditions, we find that the void bias features scale-dependent corrections on large scales, similar to its halo counterpart. We find excellent agreement between the numerical measurement of the PNG void bias and the general peak-background split prediction. Contrary to halos, large voids anti-correlate with the dark matter density field, and the large-scale Gaussian void bias ranges from positive to negative values depending on void size and redshift. Thus, the information in the clustering of voids can be complementary to that of the halos. Using the Fisher matrix formalism for multiple tracers, we demonstrate that including the scale-dependent bias information from voids, constraints on the PNG parameter $f_{\rm NL}$ can be tightened by a factor of two compared to the accessible information from halos alone, when the sampling density of tracers reaches $4 \times 10^{-3} \, h^3 \mathrm{Mpc}^{-3} $., Comment: 7 pages, 4 figures; dn/dlnsigma_8 prediction implemented and excellent agreement with simulation results obtained. Matched to published version

Modes with wavelengths larger than the survey window can have significant impact on the covariance within the survey window. The supersample covariance has been recognized as an important source of covariance for the power spectrum on small scales, and it can potentially be important for the bispectrum covariance as well. In this paper, using the response function formalism, we model the supersample covariance contributions to the bispectrum covariance and the cross covariance between the power spectrum and the bispectrum. The supersample covariances due to the long wavelength density and tidal perturbations are investigated, and the tidal contribution is a few orders of magnitude smaller than the density one because in configuration space the bispectrum estimator involves angular averaging and the tidal response function is anisotropic. The impact of the super-survey modes is quantified using numerical measurements with periodic box and subbox setups. For the matter bispectrum, the ratio between the supersample covariance correction and the small scale covariance, which can be computed using a periodic box, is roughly an order of magnitude smaller than that for the matter power spectrum. This is because for the bispectrum, the small scale non-Gaussian covariance is significantly larger than that for the power spectrum. For the cross covariance, the supersample covariance is as important as for the power spectrum covariance. The supersample covariance prediction with the halo model response function is in good agreement with numerical results., Comment: 24 pages, 12 figures, previous Eq 50 corrected, an appendix on the tidal effects added, match to the published version

Shot noise is an important ingredient to any measurement or theoretical modeling of discrete tracers of the large scale structure. Recent work has shown that the shot noise in the halo power spectrum becomes increasingly sub-Poissonian at high mass. Interestingly, while the halo model predicts a shot noise power spectrum in qualitative agreement with the data, it leads to an unphysical white noise in the cross halo-matter and matter power spectrum. In this work, we show that absorbing all the halo model sources of shot noise into the halo fluctuation field leads to meaningful predictions for the shot noise contributions to halo clustering statistics and remove the unphysical white noise from the cross halo-matter statistics. Our prescription straightforwardly maps onto the general bias expansion, so that the renormalized shot noise terms can be expressed as combinations of the halo model shot noises. Furthermore, we demonstrate that non-Poissonian contributions are related to volume integrals over correlation functions and their response to long-wavelength density perturbations. This leads to a new class of consistency relations for discrete tracers, which appear to be satisfied by our reformulation of the halo model. We test our theoretical predictions against measurements of halo shot noise bispectra extracted from a large suite of numerical simulations. Our model reproduces qualitatively the observed sub-Poissonian noise, although it underestimates the magnitude of this effect., Comment: 20 pages, 3 figures, to be submitted to PRD (v2): clarifications and references added, typo in eq.(49) fixed, in press PRD

The protohalo patches from which halos form are defined by a number of constraints imposed on the Lagrangian dark matter density field. Each of these constraints contributes to biasing the spatial distribution of the protohalos relative to the matter. We show how measurements of this spatial distribution -- linear combinations of protohalo bias factors -- can be used to make inferences about the physics of halo formation. Our analysis exploits the fact that halo bias factors satisfy consistency relations which encode this physics, and that these relations are the same even for sub-populations in which assembly bias has played a role. We illustrate our methods using a model in which three parameters matter: a density threshold, the local slope and the curvature of the smoothed density field. The latter two are nearly degenerate; our approach naturally allows one to build an accurate effective two-parameter model for which the consistency relations still apply. This, with an accurate description of the smoothing window, allows one to describe the protohalo-matter cross-correlation very well, both in Fourier and configuration space. We then use our determination of the large scale bias parameters together with the consistency relations, to estimate the enclosed density and mean slope on the Lagrangian radius scale of the protohalos. Direct measurements of these quantities, made on smaller scales than those on which the bias parameters are typically measured, are in good agreement., Comment: 17 pages, 19 figures, match the published version

The covariance matrix of the matter and halo power spectrum and bispectrum are studied. Using a large suite of simulations, we find that the non-Gaussianity in the covariance is significant already at mildly nonlinear scales. We compute the leading disconnected non-Gaussian correction to the matter bispectrum covariance using perturbation theory, and find that the corrections result in good agreement in the mildly nonlinear regime. The shot noise contribution to the halo power spectrum and bispectrum covariance is computed using the Poisson model, and the model yields decent agreement with simulation results. However, when the shot noise is estimated from the individual realization, which is usually done in reality, we find that the halo covariance is substantially reduced and gets close to the Gaussian covariance. This is because most of the non-Gaussianity in the covariance arises from the fluctuations in the Poisson shot noise. We use the measured non-Gaussian covariance to access the information content of the power spectrum and bispectrum. The signal-to-noise ratio, S/N, of the matter and halo power spectrum levels off in the mildly nonlinear regime, $k \sim 0.1 - 0.2 \,\mathrm{Mpc} h^{-1}$. In the nonlinear regime the S/N of the matter and halo bispectrum increases but much slower than the Gaussian results suggest. We find that both the S/N for power spectrum and bispectrum are overestimated by the Gaussian covariances, but the problem being much more serious for the bispectrum. Because the bispectrum is affected strongly by nonlinearity and shot noise, inclusion of the bispectrum only adds modest amount of S/N compared to that of the power spectrum., Comment: 37 pages, 25 figures, minor changes to match the published version

We study the halo-matter cross bispectrum in the presence of primordial non-Gaussianity of the local type. We restrict ourselves to the squeezed limit, for which the calculation are straightforward, and perform the measurements in the initial conditions of N-body simulations, to mitigate the contamination induced by nonlinear gravitational evolution. Interestingly, the halo-matter cross bispectrum is not trivial even in this simple limit as it is strongly sensitive to the scale-dependence of the quadratic and third-order halo bias. Therefore, it can be used to test biasing prescriptions. We consider three different prescription for halo clustering: excursion set peaks (ESP), local bias and a model in which the halo bias parameters are explicitly derived from a peak-background split. In all cases, the model parameters are fully constrained with statistics other than the cross bispectrum. We measure the cross bispectrum involving one halo fluctuation field and two mass overdensity fields for various halo masses and collapse redshifts. We find that the ESP is in reasonably good agreement with the numerical data, while the other alternatives we consider fail in various cases. This suggests that the scale-dependence of halo bias also is a crucial ingredient to the squeezed limit of the halo bispectrum.

The window function for protohalos in Lagrangian space is often assumed to be a tophat in real space. We measure this profile directly and find that it is more extended than a tophat but less extended than a Gaussian; its shape is well-described by rounding the edges of the tophat by convolution with a Gaussian that has a scale length about 5 times smaller. This effective window $W_{\rm eff}$ is particularly simple in Fourier space, and has an analytic form in real space. Together with the excursion set bias parameters, $W_{\rm eff}$ describes the scale-dependence of the Lagrangian halo-matter cross correlation up to $kR_{\rm Lag} \sim 10 $, where $R_{\rm Lag}$ is the Lagrangian size of the protohalo. Moreover, with this $W_{\rm eff}$, all the spectral moments of the power spectrum are finite, allowing a straightforward estimate of the excursion set peak mass function. This estimate requires a prescription of the critical overdensity enclosed within a protohalo if it is to collapse, which we calibrate from simulations. We find that the resulting estimate of halo abundances is only accurate to about 20%, and we discuss why: A tophat in `infall time' towards the protohalo center need not correspond to a tophat in the initial spatial distribution, so models in which infall rather than smoothed overdensity is the relevant variable may be more accurate., Comment: 15 pages, 14 figures, matched the published version, discussion and presentation significantly improved, conclusions unchanged

We propose a simple model that elucidates the generation of halo velocity bias. The fluid equation approximation is often adopted in modelling the evolution of the halo density field. In this approach, halos are often taken to be point particles even though in reality they are finite-sized objects. In this paper, we generalize the fluid equation approximation to halos to include the finite extent of halos by taking into account the halo profile. We compute the perturbation of the halo density and velocity field to second order and find that the profile correction gives rise to $k^2$ correction terms in Fourier space. These corrections are more important for velocity than for density. In particular, the profile correction generates $k^2$ correction term in the velocity bias and the correction terms do not decay away in the long term limit, but it is not constant. We model the halo profile evolution using the spherical collapse model. We also measure the evolution of proto-halo profile at various redshifts numerically. We find that the spherical collapse model gives a reasonable description of the numerical profile evolution. Static halo profile is often adopted in modelling halos in theories such as the excursion set theory. Our work highlights the importance of including the profile evolution in the calculations., Comment: 20 pages, 15 figures

We study the clustering of voids using $N$-body simulations and simple theoretical models. The excursion-set formalism describes fairly well the abundance of voids identified with the watershed algorithm, although the void formation threshold required is quite different from the spherical collapse value. The void cross bias $b_{\rm c} $ is measured and its large-scale value is found to be consistent with the peak background split results. A simple fitting formula for $b_{\rm c} $ is found. We model the void auto-power spectrum taking into account the void biasing and exclusion effect. A good fit to the simulation data is obtained for voids with radii $\gtrsim$ 30 Mpc/$h$, especially when the void biasing model is extended to 1-loop order. However, the best-fit bias parameters do not agree well with the peak-background split results. Being able to fit the void auto-power spectrum is particularly important not only because it is the direct observable in galaxy surveys, but also our method enables us to treat the bias parameters as nuisance parameters, which are sensitive to the techniques used to identify voids., Comment: 20 pages, 14 figures, minor changes to match published version

We investigate nonlocal Lagrangian bias contributions involving gradients of the linear density field, for which we have predictions from the excursion set peak formalism. We begin by writing down a bias expansion which includes all the bias terms, including the nonlocal ones. Having checked that the model furnishes a reasonable fit to the halo mass function, we develop a 1-point cross-correlation technique to measure bias factors associated with 2-distributed quantities. We validate the method with numerical realizations of peaks of Gaussian random fields before we apply it to N-body simulations. We focus on the lowest (quadratic) order nonlocal contributions. We can reproduce our measurement of \chi_{10} if we allow for an offset between the Lagrangian halo center-of-mass and the peak position. The sign and magnitude of \chi_{10} is consistent with Lagrangian haloes sitting near linear density maxima. The resulting contribution to the halo bias can safely be ignored for M = 10^13 Msun/h, but could become relevant at larger halo masses. For the second nonlocal bias \chi_{01} however, we measure a much larger magnitude than predicted by our model. We speculate that some of this discrepancy might originate from nonlocal Lagrangian contributions induced by nonspherical collapse., Comment: (v2): presentation clarified. agreement with the simulation improved. accepted for publication. 11 pages, 8 figures

Lagrangian displacement field $\Psi$ is the central object in Lagrangian perturbation theory (LPT). LPT is very successful at high redshifts, but it performs poorly at low redshifts due to severe shell crossing. To understand and quantify the effects of shell crossing, we extract $\Psi$ from N-body simulation and decompose it into scalar and vector parts. We find that at late time the power spectrum of the scalar part agrees with 1-loop results from LPT at large scales, while the power in small scales is much suppressed due to shell crossing. At z=0, the power spectrum of $\Psi$ is 10% lower than the 1-loop results at k = 0.1 h/Mpc. Shell crossing also generates the vector contribution in $\Psi$, although its effect is subdominant in comparison with the power suppression in the scalar part. At z=0, the vector part contributes 10% to the total power spectrum of $\Psi$ at k = 1 h/Mpc, while only 1% is expected from the vector contribution in LPT. We also examine the standard LPT recipes and some of its variants. In one of the variants, we include a power suppression factor in the displacement potential to take into account the power suppression in small scales after shell crossing. However, these simple phenomenological approaches are found to yield limited improvement compared to the standard LPT after the onset of shell crossing., Comment: 18 pages, 20 figures, match the published version

We explore the scale dependence of halo bias using real space cross-correlation measurements in N-body simulations and in Pinocchio, an algorithm based on Lagrangian Perturbation Theory. Recent work has shown how to interpret such real space measurements in terms of k-dependent bias in Fourier space, and how to remove the k-dependence to reconstruct the k-independent peak-background split halo bias parameters. We compare our reconstruction of the linear bias, which requires no free parameters, with previous estimates from N-body simulations which were obtained directly in Fourier space at large scales, and find very good agreement. Our reconstruction of the quadratic bias is similarly parameter-free, although in this case there are no previous Fourier space measurements to compare with. Our analysis of N-body simulations explicitly tests the predictions of the excursion set peaks (ESP) formalism of Paranjape et al. (2013) for the scale dependence of bias; we find that the ESP predictions accurately describe our measurements. In addition, our measurements in Pinocchio serve as a useful, successful consistency check between Pinocchio and N-body simulations that is not accessible to traditional measurements., Comment: 13 pages, 9 figures; v3 -- Matches published version

Halos are biased tracers of the dark matter distribution. It is often assumed that the patches from which halos formed are locally biased with respect to the initial fluctuation field, meaning that the halo-patch fluctuation field can be written as a Taylor series in that of the dark matter. If quantities other than the local density influence halo formation, then this Lagrangian bias will generically be nonlocal; the Taylor series must be performed with respect to these other variables as well. We illustrate the effect with Monte-Carlo simulations of a model in which halo formation depends on the local shear (the quadrupole of perturbation theory), and provide an analytic model which provides a good description of our results. Our model, which extends the excursion set approach to walks in more than one dimension, works both when steps in the walk are uncorrelated, as well as when there are correlations between steps. For walks with correlated steps, our model includes two distinct types of nonlocality: one is due to the fact that the initial density profile around a patch which is destined to form a halo must fall sufficiently steeply around it -- this introduces k-dependence to even the linear bias factor, but otherwise only affects the monopole of the clustering signal. The other is due to the surrounding shear field; this affects the quadratic and higher order bias factors, and introduces an angular dependence to the clustering signal. In both cases, our analysis shows that these nonlocal Lagrangian bias terms can be significant, particularly for massive halos; they must be accounted for in analyses of higher order clustering such as the halo bispectrum in Lagrangian or Eulerian space. Although we illustrate these effects using halos, our analysis and conclusions also apply to the other constituents of the cosmic web -- filaments, sheets and voids., Comment: 13 pages, 6 figures; new section shows agreement with bispectrum measurements in simulations

We develop a new test of local bias, by constructing a locally biased halo density field from sampling the dark matter-halo distribution. Our test differs from conventional tests in that it preserves the full scatter in the bias relation and it does not rely on perturbation theory. We put forward that bias parameters obtained using a smoothing scale R can only be applied to computing the halo power spectrum at scales k ~ 1/R. Our calculations can automatically include the running of bias parameters and give vanishingly small loop corrections at low-k. Our proposal results in much better agreement of the sampling and perturbation theory results with simulations. In particular, unlike the standard interpretation of local bias in the literature, our treatment of local bias does not generate a constant power in the low-k limit. We search for extra noise in the Poisson corrected halo power spectrum at wavenumbers below its turn-over and find no evidence of significant positive noise (as predicted by the standard interpretation) while we find evidence of negative noise coming from halo exclusion for very massive halos. Using perturbation theory and our non-perturbative sampling technique we also demonstrate that nonlocal bias effects discovered recently in simulations impact the power spectrum only at the few percent level in the weakly nonlinear regime., Comment: 25 pages, 14 figures; V2: significant revision including more details about halo exclusion and low-k noise. Conclusions unchanged

The relationship between galaxy and matter overdensities, bias, is most often assumed to be local. This is however unstable under time evolution, we provide proofs under several sets of assumptions. In the simplest model galaxies are created locally and linearly biased at a single time, and subsequently move with the matter (no velocity bias) conserving their comoving number density (no merging). We show that, after this formation time, the bias becomes unavoidably non-local and non-linear at large scales. We identify the non-local gravitationally induced fields in which the galaxy overdensity can be expanded, showing that they can be constructed out of the invariants of the deformation tensor (Galileons). In addition, we show that this result persists if we include an arbitrary evolution of the comoving number density of tracers. We then include velocity bias, and show that new contributions appear, a dipole field being the signature at second order. We test these predictions by studying the dependence of halo overdensities in cells of fixed matter density: measurements in simulations show that departures from the mean bias relation are strongly correlated with the non-local gravitationally induced fields identified by our formalism. The effects on non-local bias seen in the simulations are most important for the most biased halos, as expected from our predictions. The non-locality seen in the simulations is not fully captured by assuming local bias in Lagrangian space. Accounting for these effects when modeling galaxy bias is essential for correctly describing the dependence on triangle shape of the galaxy bispectrum, and hence constraining cosmological parameters and primordial non-Gaussianity. We show that using our formalism we remove an important systematic in the determination of bias parameters from the galaxy bispectrum, particularly for luminous galaxies. (abridged), Comment: 26 pages, 9 figures. v2: improved appendix A