• <tr id="yyy80"></tr>
  • <sup id="yyy80"></sup>
  • <tfoot id="yyy80"><noscript id="yyy80"></noscript></tfoot>
  • 99热精品在线国产_美女午夜性视频免费_国产精品国产高清国产av_av欧美777_自拍偷自拍亚洲精品老妇_亚洲熟女精品中文字幕_www日本黄色视频网_国产精品野战在线观看 ?

    Constraints on Dark Energy from the CSST Galaxy Clusters

    2023-05-29 10:13:04YufeiZhangMingjingChenZhonglueWenandWenjuanFang

    Yufei Zhang, Mingjing Chen, Zhonglue Wen, and Wenjuan Fang

    1 CAS Key Laboratory for Research in Galaxies and Cosmology, Department of Astronomy, University of Science and Technology of China, Hefei 230026,China; wjfang@ustc.edu.cn

    2 School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China

    3 National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China; zhonglue@nao.cas.cn

    4 CAS Key Laboratory of FAST, NAOC, Chinese Academy of Sciences, Beijing 100101, China

    Abstract We study the potential of the galaxy cluster sample expected from the Chinese Space Station Telescope (CSST)survey to constrain dark energy properties.By modeling the distribution of observed cluster mass for a given true mass to be log-normal and adopting a selection threshold in the observed mass M200m ≥0.836×1014 h-1 M⊙,we find about 4.1×105 clusters in the redshift range 0 ≤z ≤1.5 can be detected by the CSST.We construct the Fisher matrix for the cluster number counts from CSST, and forecast constraints on dark energy parameters for models with constant(w0CDM)and time dependent(w0waCDM)equation of state.In the self-calibration scheme,the dark energy equation of state parameter w0 of the w0CDM model can be constrained to Δw0=0.036.If wa is added as a free parameter,we obtain Δw0=0.077 and Δwa=0.39 for the w0waCDM model,with a Figure of Merit for(w0,wa) of 68.99.Should we have perfect knowledge of the observable-mass scaling relation (“known SR”scheme),we would obtain Δw0=0.012 for the w0CDM model, and Δw0=0.062 and Δwa=0.24 for the w0waCDM model.The dark energy Figure of Merit of (w0, wa) increases to 343.25.This indicates again the importance of calibrating the observable-mass scaling relation for optically selected galaxy clusters.By extending the maximum redshift of the clusters from zm ax ~ 1.5to zm ax ~ 2,the dark energy Figure of Merit for(w0,wa)increases to 89.72(self-calibration scheme) and 610.97 (“known SR”scheme), improved by a factor of ~1.30 and ~1.78,respectively.We find that the impact of clusters’redshift uncertainty on the dark energy constraints is negligible as long as the redshift error of clusters is smaller than 0.01, achievable by CSST.We also find that the bias in logarithm mass must be calibrated to be 0.30 or better to avoid significant dark energy parameter bias.

    Key words: (cosmology:) dark energy – galaxies: clusters: general – (cosmology:) cosmological parameters

    1.Introduction

    The concordance Λ cold dark matter (ΛCDM) model has proven to provide an accurate description of the universe(Planck Collaboration et al.2020).Nevertheless, the main constituents in the model, namely dark energy (DE) and dark matter (DM), still need explanations from fundamental physics.Questions such as whether DE is indeed the cosmological constant (Zel’dovich 1967, 1968), or whether modified gravity theory rather than DE and DM actually explains the observable universe (Hu & Sawicki 2007;Capozziello & de Laurentis 2011), remain unsolved.These questions provide motivations to look for alternatives to the ΛCDM model.Future high precision cosmological surveys will constrain various such models and clarify many unsolved fundamental questions.

    DE, unlike other known forms of matter or energy, is a component postulated to cause the late time accelerated expansion of the universe with a negative pressure (Riess et al.1998;Perlmutter et al.1999).Multiple observational evidences point to the existence of DE.However, to date there are no compelling theoretical explanations yet.The most popular model of DE is the cosmological constant whose equation of state(EoS)is-1.There are other models in which the EoS of DE is not -1 or even not constant but time-dependent, for example, quintessence (Ratra &Peebles 1988),phantom(Caldwell 2002)and quintom(Feng et al.2005).The accelerated expansion of the universe may even imply that gravity should be described by a modified theory of gravity, rather than the standard theory of General Relativity(Heisenberg 2019).Different models of DE leave different signatures in the expansion rate of the universe and the growth rate of structure.Thus surveys that observe the universe’s supernovae, galaxies, galaxy clusters, etc., can potentially reveal the nature of DE (e.g., Zhao et al.2017).

    In the hierarchical structure formation scenario,small density fluctuations generated in the primordial universe act as the seeds for the formation of the universe’s structure.Overdensities in the early universe grow through gravitational instability and hierarchically form larger and larger structures(Peebles 1980;Colberg et al.1999).Galaxy clusters are the largest virialized objects in the universe.Searches for galaxy clustershave been carried out for decades from multiwavelength data,such as the millimeter wave bands (e.g., de Haan et al.2016;Planck Collaboration et al.2016; Bleem et al.2020), the optical wave bands(e.g.,Wen et al.2009;Rozo et al.2010;Oguri et al.2018;Costanzi et al.2019;DES Collaboration et al.2020;Wen&Han 2021)and the X-ray wave bands(e.g.,Vikhlinin et al.2009;Clerc et al.2012; Rapetti et al.2013; B?hringer et al.2017;Pacaud et al.2018).The abundance and spatial distribution of galaxy clusters are sensitive to the universe’s expansion and growth rate and hence underlying cosmological model (Allen et al.2011; Kravtsov & Borgani 2012; Weinberg et al.2013).Clusters have been used to constrain the matter density parameter Ωmand the present day root mean square (rms) of linear density fluctuations within a sphere of radius 8 h-1Mpc, σ8(e.g., Rozo et al.2007, 2010; Rapetti et al.2013; de Haan et al.2016;Costanzi et al.2019; DES Collaboration et al.2020, 2021).Moreover,since massive neutrinos suppress matter fluctuations on small scales,this impact on the growth of structure manifests itself in cluster observables, which can be used to constrain neutrino mass (Costanzi et al.2013; Mantz et al.2015; Planck Collaboration et al.2016).Clusters have also been demonstrated to provide tight constraints on DE from their abundance (Mantz et al.2010; Rozo et al.2010; Mantz et al.2015; de Haan et al.2016), spatial clustering (Schuecker et al.2003; Abbott et al.2019; DES Collaboration et al.2021) and gas mass fractions(Allen et al.2008; Mantz et al.2014, 2021).However, the precision on cosmological parameters derived from cluster observables is affected by both theoretical and observational systematic uncertainties.

    Table 1 Key Parameters of the CSST Photometric Imaging Survey and Spectroscopic Survey (Zhan 2021)

    Forthcoming large surveys, for example the Vera Rubin Observatory (LSST Science Collaboration et al.2009;Ivezi? 2019), Euclid space mission (Laureijs et al.2011) and Chinese Space Station Telescope(CSST)(Zhan 2011;Cao et al.2018; Gong et al.2019), have the potential to find a large number of clusters.Specifically, the CSST is a 2 m space telescope planned to be launched in the early 2020s.It will operate in the same orbit as the China Manned Space Station.The CSST aims at surveying 17,500 deg2of sky area over 10 yr of operation.Both photometric imaging and slitless grating spectroscopic observations will be conducted.With the unique combination of a large field of view (~1 deg2), high-spatial resolution(~0 15),faint magnitude limits and wide wavelength coverage, CSST has great potential to investigate many fundamental problems, such as properties of DE and DM,validity of General Relativity on cosmic scales,etc.(Zhan 2011).In particular,CSST will detect a large number of clusters through photometric imaging, spectroscopic observation and weak gravitational lensing, thanks to its large sky coverage and wide redshift range, which will be valuable for cosmological studies.

    We list the key parameters of the CSST survey in Table 1.There are seven photometric and three spectroscopic bands from near-ultraviolet (near-UV) to near-infrared (near-IR), namely,NUV, u, g, r, i, z and y bands for the photometric survey, and GU, GV and GI bands for the spectroscopic survey.The CSST photometric survey can reach a 5σ magnitude limit of ~26 AB mag for point sources, while for spectroscopic survey, the magnitude limit can reach ~23 AB mag.The 4000 ? break,Lyman break and 1.6 μm bump are distinct features to determine photometric redshifts of galaxies.The photometric redshifts of galaxies can be well determined up to the redshift of z ~1.4,at which the 4000 ? break moves to the y band.At higher redshifts,the Lyman break begins to move into the CSST filters.Considering the relatively shallow survey depth in the NUV band, it is expected that the photometric redshifts have a larger bias and uncertainty at 1.4 <z <2.5 (even with the presence of NUV, the photometric redshift is not much improved in the redshift range,Rafelski et al.2015).They can be improved with the help of other surveys whose band coverage extends to midinfrared and near-IR bands, such as Wide-field Infrared Survey Explorer (WISE, Wright et al.2010) and Euclid (Laureijs et al.2011; Sartoris et al.2016).

    In this paper, we explore the power of the CSST cluster sample in constraining DE parameters.We consider two DE models.The first one is the model in which the EoS parameter w of DE is allowed to deviate from -1 in a time independent fashion (w0CDM).In the second model, the EoS of DE is varying with time (w0waCDM), with the phenomenological parameterization w(a)=w0+(1-a)wa, where a is the scale factor of the universe (Chevallier & Polarski 2001; Linder &Jenkins 2003).We estimate the abundance of galaxy clusters expected from CSST and forecast its constraints on cosmological parameters by using the Fisher matrix technique.To calculate galaxy cluster number counts, we first compute the halo mass function by adopting the fitting function from Tinker et al.(2008).Then the number counts in an observed mass bin can be computed once the probability to assign an observed mass to a cluster’s true mass is given.Finally, we can evaluate cluster number counts as a function of the estimated mass and redshift.By combining the number of clusters in bins of estimated mass and redshift, we construct the Fisher matrix and then derive the forecasted constraints on cosmological parameters.

    This paper is organized as follows.In Section 2, we detail our estimation for the galaxy cluster abundance expected for the CSST, and present the Fisher matrix we use to forecast parameter constraints.In Section 3, we give our results and discuss the effects of several systematics.Finally,we conclude in Section 4.

    2.Calculational Methods

    2.1.Mass Estimation for CSST Clusters

    Cluster mass is of fundamental importance for studies on cluster properties and cluster cosmology.Regardless of how clusters are detected at different wavelengths,the main concern is that halo mass is not directly observable,so we have to employ a suitable observable quantity that scales with mass.In the case of optical surveys, a commonly used mass proxy is the optical richness λ,which corresponds to the count or total luminosity of member galaxies above some luminosity threshold in a given cluster(Rozo et al.2009;Wen et al.2012).The calibration of the relation between richness and halo mass for optically selected clusters can be performed through cluster number counts,clustering and stacked weak-lensing measurements (e.g., Murata et al.2018; Costanzi et al.2019; Murata et al.2019; Chiu et al.2020a,2020b;DES Collaboration et al.2020;Wen&Han 2021).

    For the CSST survey,each galaxy cluster is identified with an optical richness estimated.Mean mass of clusters can be measured directly through weak lensing for a sample of stacked clusters within a given richness and redshift bin.Then, one can get an“accurate”richness-mass scaling relation and its evolution with redshift.In the regime where the weak lensing method is not applicable, e.g., very high redshifts, cluster mass can be estimated according to the derived richness-mass relation.

    2.2.Calculation for Cosmological Constraints

    A fundamental quantity for cluster cosmology is the halo mass function, which is defined as the differential number density of halos.In this paper,we adopt the halo mass function obtained by Tinker et al.(2008)

    where f(σ) is the fitting function given by Equation (3) in Tinker et al.(2008), ρmis the present matter density of the universe and σ is the rms of linear matter fluctuation within a sphere of radius R that contains mass M given mean density of

    In the above expression, P(zob|z) is the probability distribution function to assign a galaxy cluster at true redshift z to the observed photometric redshift zob, which we model as a Gaussian distribution with expectation value z and scatter σz.

    The comoving space number density of clusters〈n|Mob,z〉is related to halo mass function by

    where P(Mob|M, z) is the probability distribution function to assign a galaxy cluster with true mass M and at true redshift z to the observed mass Mob.

    The survey volume element dV/(dzdΩ) is given by

    where H(z) is the Hubble parameter and χ(z) is the comoving radial distance to redshift z.

    The key ingredient in our analysis is the probability distribution function of the observed mass for halos with a given true mass M and redshift z, P(Mob|M, z).Following Sartoris et al.(2016), we assume a log-normal distribution function, namely

    HerelnMbiasandσlnMare the bias and scatter of mass estimation in logarithm space, respectively.Following Sartoris et al.(2016), we parameterize the bias as

    We assume the following parameterization for the variance oflnM

    Here the first term comes from the fact that cluster mass commonly scales with optical richness.The variance of lnλis composed of a constant intrinsic scatter Dλand a Poisson-like term (Costanzi et al.2021)

    where the term 1/〈λ〉is a function of cluster mass and redshift.The fiducial values ofσlnλand B can be obtained from the scaling relation fitted by Costanzi et al.(2021)

    Here,A is the normalization,B is the slope with respect to halo mass and Bzdescribes the evolution with redshift.The constants Mpivotand zpivotare pivot halo mass and redshift respectively.We emphasize that Equation (10) is not used for cluster mass estimation, but for the scatter of mass estimation.

    The second term κ(1+z)2in Equation (8) characterizes the projection effects that depend on redshift.The reason for the chosen form of the projection effects is as follows.The photometric redshift error of galaxies usually increases with redshift.In the algorithms of cluster identification,the width of color cut or photometric redshift slice increases with redshift for both the color-based and photometric redshift-based methods (Wen et al.2009; Rykoff et al.2014).As is wellknown, the dispersion of photometric redshift generally increases with redshift in the form of 1+z (Cao et al.2018).From the perspective of identifying galaxy clusters,in order to obtain the majority of member galaxies, the width of the photometric redshift slice used to find galaxy clusters also increases as 1+z, resulting in the corresponding increase of field galaxies projecting into cluster regions as member galaxies.In Wen et al.(2009), the authors adopted a photometric redshift slice of z±0.04(1+z) for the Sloan Digital Sky Survey(SDSS)clusters and found a contamination rate of ~20%for member galaxies due to the projection effect.The CSST will have a more accurate photometric redshift than the SDSS (Cao et al.2018), which will enable us to set a narrower photometric redshift slice for selecting member galaxies of clusters.In addition, the slitless spectroscopic survey provides accurate redshifts for bright galaxies.It is possible to have a contamination rate of about 10% at low redshift for massive clusters.Therefore,we assume κ=0.12as a fiducial choice.

    We forecast the constraints on cosmological parameters using the Fisher matrix technique, which is based on a Gaussian approximation of the likelihood function around the maximum (Tegmark et al.1997).The Fisher matrix is defined as

    where pα, pβrepresent model parameters,L is the likelihood function and angle brackets represent ensemble average.The marginalized 1σ constraint on parameter pαcan then be obtained by

    In our analysis we choose the galaxy cluster number counts Nm,ias observable.The likelihood of Nm,ican be modeled as a Poisson distribution with the expectation valueNˉm,i,

    Thus the Fisher matrix for cluster number counts is

    Here, the sums over m and i run over mass and redshift bins,respectively.

    We adopt the Figure of Merit(FoM,Albrecht et al.2006)for DE to quantify the information gains from given probes and experiments, which is inversely proportional to the area encompassed by an ellipse representing the 68.3 percent confidence level

    where Cov(w0, wa) is the marginalized covariance matrix for the DE EoS parameters w0and wa.

    In our Fisher matrix analysis, both cosmological parameters and the parameters modeling bias and scatter in the scaling relation between the observed and true cluster masses are treated as free parameters, and are constrained simultaneously.We assume a flat universe and choose our cosmological parameter set as: {h, Ωbh2, Ωch2, σ8, ns, w0, wa}.Fiducial values of these parameters are listed in Table 2, which are the best-fit values from Planck 2018 results (Planck Collaboration et al.2020).We marginalize over the set of scaling relation parameters {BM,0, α, A, B, Bz, Dλ, κ} given above, referred to as nuisance parameters henceforth, whose fiducial values are listed in Table 2.The values of BM,0and α are chosen according to Sartoris et al.(2016),while the values of A,B,Bzand Dλare the best-fit values obtained in Costanzi et al.(2021).The pivot values for halo mass and redshift(Mpivotand zpivot)inEquation (10) are taken to be 3×1014h-1M⊙a(bǔ)nd 0.45,respectively, following Costanzi et al.(2021).

    Table 2 The Fiducial Values of Cosmological Parameters (Upper Section) and Nuisance Parameters (Lower Section) Adopted in this Work

    3.Results and Discussions

    In this section, we present the main results of this paper:constraints on the DE EoS parameters from galaxy cluster number counts of CSST, forecasted with the Fisher matrix formalism.Several systematics are also discussed simultaneously.We consider DE models with constant (w0CDM) and time dependent(w0waCDM)DE EoS.We assume that CSST is capable of detecting clusters up to z ~1.5 by either the redshiftbased method (e.g., Wen & Han 2021; Yang et al.2021) or color-based method (e.g., Rykoff et al.2014).We divide the CSST cluster sample into bins both in redshift and halo mass.For redshift, we consider equal-sized bins of width Δz=0.05 in the range 0 ≤z ≤1.5.For observed halo mass, we take equal-sized logarithmic bins of width Δln (MobM⊙) =0.2.We ignore the covariance between different redshift and mass bins.We assume 17,500 deg2sky coverage for the CSST optical wide survey.Most CSST galaxies will have photometric redshift uncertainties of about 0.02 (Gong et al.2019).Moreover, CSST will perform a slitless grating spectroscopic survey for bright sources in addition to a photometric imaging survey.Taking into account that clusters have multiple bright member galaxies whose spectroscopic redshifts are probably available from CSST slitless or existing spectroscopic surveys,we expect CSST clusters will have an accurate redshift.In this work, we assume CSST clusters’redshift uncertainty to be σz/(1+z)=0.001.

    Figure 1.Redshift distribution of galaxy clusters expected for CSST; mass threshold is set to M200m ≥0.836×1014 h-1 M⊙(M500c ≥0.7×1014 M⊙).

    3.1.Mass Limit and Number Counts

    The lower limit of cluster mass corresponds to a given detection threshold in the observed quantity.The limit is adopted to ensure that the cluster sample obtained has a high completeness and also a high purity.According to the analysis based on mock galaxy redshift survey data (Yang et al.2021),we adopt a lower mass limit of M200m≥0.836×1014h-1M⊙for the CSST cluster sample in order to get a completeness of≥90% and a purity of ≥90%.This mass limit roughly corresponds to an equivalent mass limit of M500c≥0.7×1014M⊙(Wen & Han 2021).

    In Figure 1,we plot the expected number of clusters that can be detected by CSST as a function of redshift, obtained by adopting the observed halo mass limit M200m≥0.836×1014h-1M⊙a(bǔ)nd assuming the fiducial values of cosmological and nuisance parameters.We find that CSST can detect~414,669 clusters in total in the redshift range 0 ≤z ≤1.5,with a peak at z ~0.6, and there are ~103,069 clusters at z ≥1.0.These high redshift clusters are sensitive to the growth rate of perturbations and DE properties.A catalog of uniformly selected high-redshift clusters will be ideal to study structure growth and the underlying cosmological model.

    3.2.Constraints from Cluster Number Counts

    Since besides cosmological parameters, there are also nuisance parameters which model bias and scatter in the scaling relation between the observed and true cluster masses,we forecast constraints on DE EoS parameters from galaxy cluster number counts of CSST with two schemes: a selfcalibration scheme in which we take both cosmological parameters and nuisance parameters as parameter entries for the Fisher matrix(Majumdar&Mohr 2004),and the ideal caseNote.The column labeled“Self-calibration”corresponds to the self-calibration scheme without any priors on the nuisance parameters.The column “Known SR”refers to the ideal case in which the nuisance parameters are perfectly known.Constraints shown are the marginalized 1σ errors.The DE FoM is presented in the last row.in which the nuisance parameters are fixed, which means that scaling relations are perfectly known in advance(referred to as the “known SR”scheme in the following).

    Table 3 Constraints on the Cosmological Parameters and Nuisance Parameters from the Number Counts of CSST Galaxy Clusters

    It is challenging to constrain the cosmological parameters and nuisance parameters simultaneously by using the number counts of galaxy clusters alone.In the following analysis we include the Gaussian priors on the Hubble parameter and the cosmic baryon density from the Planck collaboration (Planck Collaboration et al.2020) to help break parameter degeneracies.

    The constraints on the cosmological parameters from CSST galaxy cluster number counts are presented in Table 3 for the two schemes.In the self-calibration scheme, the DE EoS parameters can be constrained to Δw0=0.036 for the w0CDM model, and Δw0=0.077 and Δwa=0.39 for the w0waCDM model,corresponding to a DE FoM for(w0,wa)of 68.99.In the“known SR”scheme,cluster mass has no bias and the scatter of cluster mass is known.The constraint on w0is as good as Δw0=0.012 for the w0CDM model, an improvement by a factor of ~3 compared to the results of the self-calibration scheme, while for the w0waCDM model, we obtain Δw0=0.062 and Δwa=0.24.The DE FoM is as high as 343.25, an improvement by a factor of ~5 compared to the results of the self-calibration scheme.It is apparent that knowledge of the observable-mass scaling relation is essential to get tighter cosmological parameter constraints.The analysis here highlights the importance of the calibration of the observable-mass scaling relation for optically selected galaxy clusters in order to obtain tight DE constraints.We postpone a comparison with other optical cluster surveys to Section 3.6.

    It is known that besides DE parameters, clusters can also place tight constraints on DM related parameters.The 1σ uncertainties on Ωch2and σ8are about 1%~2%with the selfcalibration scheme, while 0.1%–0.2% with the “known SR”scheme.The improvements from better knowledge of the observable-mass scaling relation are more pronounced for constraints on Ωch2and σ8than for w0and wa.Comparing the constraints from the self-calibration scheme and those from the“known SR”scheme, the constraint on Ωch2is improved by a factor of 12.5 for the w0CDM model and a factor of 6.4 for the w0waCDM model, while the constraint on σ8is improved by a factor of 20 for the w0CDM model and a factor of 12 for the w0waCDM model.Thus better calibration of the observablemass scaling relation is more helpful to tighten the constraints on DM related parameters than DE parameters.We show contours of constraints(1σ)on cosmological parameters for the w0waCDM model in the Appendix.

    We point out that in this analysis we assume a possible configuration of CSST.In the following we analyze the impact of two key parameters on our derived constraints, i.e., the maximum redshift and the clusters’redshift uncertainty.We also compute the requirement for the calibration of bias in cluster mass.

    3.3.Increasing zmax of CSST Clusters

    In the above analysis for the CSST clusters,we have adopted a maximum redshift ofzmax~ 1.5.Higher redshift is potentially achievable with an improved cluster selection algorithm, better data quality or joint analysis with the Euclid survey by the European Space Agency (Laureijs et al.2011),which can detect clusters up to redshift as high as ~2 thanks to the use of near-IR bands (Sartoris et al.2016).

    In this section, we study the impact of including higher redshift clusters in our forecast by increasing the maximum redshift of the CSST cluster sample.Specifically, when we extend zmaxto ~2, we find that 28,492 clusters between 1.5 ?z ?2 can be additionally detected, ~7% more than before.The DE constraints obtained by extending the maximum redshift of the clusters tozmax~ 2are presented in Table 4.By extending the maximum redshift of the survey fromzmax~ 1.5tozmax~ 2, the DE constraints are tightened for both the w0CDM model and w0waCDM model.The constraint on w0for the w0CDM model is improved by a factor of ~1.06 for the self-calibration scheme,and a factor of ~1.28 for the “known SR”scheme.While for the w0waCDM model,the DE FoM is improved by a factor of ~1.30 for the selfcalibration scheme, and a factor of ~1.78 for the “known SR”scheme.As can be seen,even moderate detection of clusters at high redshift can tighten the constraints by an appreciable amount.The reason is that the behavior of DE deviates morefrom the ΛCDM model in the earlier universe.Therefore if the survey can cover a large redshift range, a comparison of the behavior of DE at different redshifts helps to break parameter degeneracies.

    Table 4 Constraints on DE EoS Parameters by Extending the Maximum Redshift of the CSST Clusters tozm ax ~2

    In Figure 2,we show how the FoM for DE parameters in the w0waCDM model changes as the maximum redshift of the CSST clusters increases continuously.For both the self-calibration and“known SR”schemes,the DE FoM increases steadily with zmax.Thus it is important to search for clusters at high redshift for stringent constraints on DE properties.It is also interesting to note that the FoM obtained from the “known SR”scheme increases more rapidly than that from the self-calibration scheme.Thus high redshift clusters are more helpful to constrain DE if clusters have a well calibrated scaling relation.

    3.4.The Impact of Redshift Uncertainty

    The constraints above are obtained by assuming a somewhat optimistic redshift uncertainty of σz/(1+z)=0.001, which we expect to be achievable under the assumption that spectroscopic redshifts are available for all clusters from CSST.In this section,we study the impact of less accurate redshifts for clusters on the cosmological constraints by assuming the CSST clusters have redshift accuracy of σz/(1+z)=0.03, 0.02 and 0.01.In Figures 3 and 4, we show how the constraints on DE EoS parameters change with respect to clusters’redshift accuracy.The error ellipses in Figure 3 are obtained with the selfcalibration scheme, while those in Figure 4 are obtained by the“known SR”scheme.In both figures, the DE constraints get tighter as CSST clusters’redshift uncertainty becomes smaller.However, the improvement in DE constraints is tiny from σz/(1+z)=0.01 to σz/(1+z)=0.001.For the self-calibration scheme, the DE FoM improves from 68.44 to 68.99, while for the “known SR”scheme, the FoM improves from 340.09 to 343.25.In both cases, the improvement is less than 1 per cent.We conclude that the impact of CSST clusters’redshift uncertainty is negligible as long as the rms of redshift uncertainties is better than 0.01.According to Wen & Han(2022),the redshift uncertainty of DES clusters is about 0.013 at redshifts z ≤0.9.Since CSST has two more wave bands than DES, we expect σz/(1+z)=0.01 is achievable by the CSST optical survey.We also find that if the clusters’redshift error degrades further to 0.03,FoM decreases only by a small amount of ~9%for both the self-calibration and “known SR”schemes.

    Figure 2.The DE FoM as a function of the maximum redshift zmax of the CSST clusters.Orange line stands for constraints obtained by the selfcalibration scheme.Red line represents constraints obtained by the “known SR”scheme.

    Figure 3.Impact on DE constraints from the CSST clusters’redshift uncertainty.The contours are obtained with the self-calibration scheme.Orange, blue, black and red lines are for σz/(1+z) equating 0.03, 0.02, 0.01 and 0.001, respectively.

    3.5.Mass Bias Calibration

    In our analysis,the fiducial value of bias in observed mass is set to zero.However,if the observed cluster mass is biased,the derived DE parameter constraints will also be biased.It is interesting to ask that given the statistical accuracy achievable by the CSST clusters, what is the requirement for the calibration of bias in cluster mass.

    Figure 4.Impact on the DE constraints from the CSST clusters’redshift uncertainty.The contours are obtained with the “known SR”scheme.Orange,blue, black and red lines are for σz/(1+z) equating to 0.03, 0.02, 0.01 and 0.001, respectively.

    Consider data vectorD={Dα} with covariance matrix C.The data bias ΔD induces bias in the ith parameter pias(Bernstein & Huterer 2010)

    The bias calibration requirement is set by requiring the induced parameter bias to be smaller than the expected statistical variation in the cosmological parameters.The likelihood of the bias for a subset of interested parameters ΔpAis determined by Bernstein & Huterer (2010)

    3.6.Comparison with Other Optical Cluster Surveys

    In this section,we make a comparison between our results of CSST and those of other optical cluster surveys,such as LSST and Euclid.First,we compare our results for the CSST clusters to those of LSST clusters by Fang&Haiman(2007)utilizing a shear-selected cluster sample.The halo mass definition adopted by Fang & Haiman (2007) is based on identification of DM halos as spherical regions with a mean overdensity of 180 with respect to the background matter density at the time of identification.With a sky coverage of 18,000 deg2,they found that LSST can detect 276,794 clusters in the redshift range 0.1 ≤z ≤1.4,above the limiting halo mass of ~(0.6–4)×1014M⊙.This number count is less than our result, since Fang &Haiman (2007) do not take into account uncertainties in the observable-mass scaling relation.Using cluster number counts alone, the forecasted FoM of DE EoS parameters (w0, wa) is 14.1,weaker than our result.This is due to less cluster number count obtained by Fang & Haiman (2007), and the WMAP priors adopted by them are much weaker than the Planck priors we adopt.

    We also compare our results for the CSST to those of Euclid by Sartoris et al.(2016).The detection threshold of Euclid clusters is chosen such that N500,c/σfield, the ratio between the number of cluster galaxies N500,cand the rms of field galaxies σfield, is greater than 3 (or 5).The lowest limiting cluster mass for N500,c/σfield=3 is M200c~8×1013M⊙.With selection threshold N500,c/σfield=5,Euclid can detect ~2×105clusters up to redshift z ~2, with about ~4×104objects at z ≥1.By lowering the detection threshold down to N500,c/σfield=3, the total number of clusters rises up to ~2×106, with ~4×105objects at z ≥1.Our total number of clusters is between their estimated results for these two cases.Using cluster number counts alone, Euclid obtained DE FoM of ~30 for N500,c/σfield≥3 in the self-calibration scheme.Though the abundance of Euclid clusters is greater than ours, the constraints we obtained are more competitive than theirs,since Sartoris et al.(2016) also include curvature parameter Ωkin their Fisher matrix analysis.We also note that the parameterization for the mass scatter in Sartoris et al.(2016) is different from ours.

    Finally, we notice that during the preparation of this paper,another result on DE constraints forecasted using the CSST galaxy clusters appeared in Miao et al.(2022).The cluster redshift range adopted by them is the same as ours.However,the limiting mass of clusters adopted by them (M ≥1014h-1M⊙) is higher than ours, and they do not take into account uncertainties in the observable-mass scaling relation, resulting in less clusters (~170,000) than ours.They obtain the forecasted DE constraints of Δw0=0.13 and Δwa=0.46 using the CSST cluster number counts, which are worse than ours, due to their much lower number of clusters and the fact that no Planck priors on the Hubble parameter and the cosmic baryon density are adopted in their analysis.

    4.Conclusions

    In this paper, we perform a comprehensive analysis of the constraints on DE for both constant (w0CDM) and timedependent (w0waCDM) EoS expected from the CSST galaxy clusters.We make our forecast by adopting the Fisher matrix formalism tailored for measurements of cluster abundance.In the self-calibration scheme, we consider 14 parameters, seven of which characterize the cosmological model, while the remaining seven model bias and scatter in the scaling relation between the observed and true cluster masses for optically selected clusters.With the selection threshold in the observed halo mass of M200m≥0.836×1014h-1M⊙, 414,669 clusters in the redshift range 0 ≤z ≤1.5 can be detected by the CSST,whose distribution peaks at z ~0.6.There are 103,069 clusters at z ≥1.0.The DE can be constrained to Δw0=0.036 for the w0CDM model, and Δw0=0.077 and Δwa=0.39 for the w0waCDM model, with a FoM of 68.99.

    The self-calibration procedure would largely benefit from the fixed scaling relation.By fixing the seven nuisance parameters in our analysis, we get much tighter cosmological parameter constraints.We find that for the w0CDM model, the constraint on w0is as good as Δw0=0.012, an improvement by a factor of ~3 compared to the self-calibration scheme.If wais added as a free parameter, we obtain Δw0=0.062 and Δwa=0.24 for the w0waCDM model.The DE FoM for (w0,wa) is as high as 343.25,a great improvement by a factor of ~5 compared to the result of the self-calibration scheme.These results again highlight the importance of securing good knowledge of the observable-mass scaling relation.

    We investigate the possibility of tightening the DE constraints further by increasing the redshift extension of the CSST clusters.We extend the maximum redshift of the CSST clusters out toz2 max~ and find that an extra 28,492 clusters between 1.5 ?z ?2 can be detected.The DE FoM for(w0,wa)increases to 89.72 and 610.97, for the self-calibration and“known SR”schemes, respectively, approximately improved by a factor of ~1.30 and ~1.78 from the results ofzmax~ 1.5.Thus,a small number of clusters at high redshift can tighten the cosmological constraints considerably, and high redshift clusters are more helpful to constrain DE with a better calibrated observable-mass scaling relation.

    We find that the impact of the redshift uncertainty of clusters on the constraints of DE is negligible as long as the accuracy of redshift is better than 0.01, achievable by the current DES survey.If the clusters’redshift error degrades further to 0.03,FoM decreases only by a small amount of 9%.We also find that the logarithm mass bias must be calibrated to|BM,0|<0.30 or better to avoid significant DE parameter bias.

    In this work, we have focused on constraining DE parameters using cluster number counts alone.One can surely add in other cluster statistics to tighten the constraints with complementary information or better knowledge of systematics, for example the cluster power spectrum and the stacked lensing of clusters.On the other hand, various other fundamental problems can be investigated by using the CSST cluster sample,e.g.,neutrino mass,primordial non-Gaussianity or modified gravity.We plan to investigate these prospects in future study.

    Acknowledgments

    This work is supported by the National Key R&D Program of China grants Nos.2022YFF0503404 and 2021YFC2203102,by the National Natural Science Foundation of China (NSFC,Grant Nos.12173036, 11773024, 11653002, 11421303 and 12073036),by the China Manned Space Project grant No.CMSCSST-2021-B01, by the Fundamental Research Funds for Central Universities Grant Nos.WK3440000004 and WK3440000005, and by the CAS Interdisciplinary Innovation Team.

    Appendix

    Constraints on Cosmological Parameters

    In this Appendix, for completeness and comparison with other work, we display the constraint contours for all cosmological parameters for the w0waCDM model, see Figure A1.We do not show the contours for the Hubble parameter or the cosmic baryon density since we have used the Planck priors on these two parameters.The constraints are obtained by the self-calibration scheme(blue)and“known SR”scheme (red), respectively, assumingzmax~ 1.5and clusters’redshift uncertainty of 0.001.It is clear from these contours that the constraining power from the CSST galaxy cluster survey will become much more powerful if the scaling relation sector is better understood.The improvements from better knowledge of the observable-mass scaling relation are more pronounced for constraints on other cosmological parameters(Ωch2,σ8and ns) than for w0and wa.The degeneracy directions of some cosmological parameters are different for the two schemes since the inclusion of observable-mass scaling relation parameters in the self-calibration scheme will alter the degeneracy directions of the cosmological parameters in the“known SR”scheme.

    Figure A1.The contours of constraints (1σ) on cosmological parameters for the w0waCDM model obtained by the self-calibration scheme (blue) and “known SR”scheme (red), respectively.

    另类精品久久| 欧美国产精品va在线观看不卡| 最近手机中文字幕大全| 亚洲美女搞黄在线观看| 另类亚洲欧美激情| 国产精品 国内视频| 国产成人91sexporn| 免费久久久久久久精品成人欧美视频| 老司机亚洲免费影院| 熟妇人妻不卡中文字幕| 蜜桃在线观看..| 中文字幕另类日韩欧美亚洲嫩草| 国产精品国产三级专区第一集| 久久性视频一级片| 男女国产视频网站| 曰老女人黄片| 成年动漫av网址| 美女脱内裤让男人舔精品视频| 欧美精品人与动牲交sv欧美| 国产精品免费大片| 欧美精品亚洲一区二区| 精品人妻在线不人妻| 国产av精品麻豆| 99精品久久久久人妻精品| 久久久久人妻精品一区果冻| 韩国av在线不卡| 美女午夜性视频免费| 精品国产一区二区三区久久久樱花| 男人操女人黄网站| www.熟女人妻精品国产| 在线观看国产h片| av在线播放精品| 久久97久久精品| 成人漫画全彩无遮挡| 成人影院久久| 成人18禁高潮啪啪吃奶动态图| 人人澡人人妻人| 中文字幕高清在线视频| 色婷婷久久久亚洲欧美| 在线免费观看不下载黄p国产| 不卡av一区二区三区| 91老司机精品| 丁香六月欧美| 咕卡用的链子| 中文字幕最新亚洲高清| www.精华液| 成人国产av品久久久| 99久国产av精品国产电影| 国产精品一区二区在线不卡| 成人国产av品久久久| 亚洲国产精品一区二区三区在线| 国产一区二区激情短视频 | 国产激情久久老熟女| 国产精品秋霞免费鲁丝片| 精品国产乱码久久久久久小说| 精品免费久久久久久久清纯 | 性少妇av在线| 久久久久久久久久久久大奶| 久久毛片免费看一区二区三区| 晚上一个人看的免费电影| 欧美日韩亚洲高清精品| 亚洲精品第二区| 精品少妇一区二区三区视频日本电影 | 天天操日日干夜夜撸| 久久久亚洲精品成人影院| 91国产中文字幕| av免费观看日本| 欧美日本中文国产一区发布| 午夜福利一区二区在线看| 国产精品国产av在线观看| 国产一区二区激情短视频 | 下体分泌物呈黄色| 欧美精品高潮呻吟av久久| av卡一久久| 成人影院久久| 亚洲色图综合在线观看| 中文字幕精品免费在线观看视频| 国产精品免费视频内射| 伊人久久国产一区二区| 一区福利在线观看| 亚洲七黄色美女视频| 18禁裸乳无遮挡动漫免费视频| av国产久精品久网站免费入址| 韩国精品一区二区三区| 欧美xxⅹ黑人| 久久久精品94久久精品| 另类精品久久| 人人妻人人澡人人爽人人夜夜| 日本一区二区免费在线视频| 亚洲精品国产av成人精品| 国产日韩欧美亚洲二区| 亚洲七黄色美女视频| 成人三级做爰电影| 99热全是精品| 国产精品二区激情视频| 亚洲一卡2卡3卡4卡5卡精品中文| 亚洲欧美一区二区三区久久| 男人添女人高潮全过程视频| 18在线观看网站| 中文字幕最新亚洲高清| 亚洲专区中文字幕在线 | 精品一区在线观看国产| 另类精品久久| 色网站视频免费| 一级毛片 在线播放| 一本久久精品| 男女无遮挡免费网站观看| 男女下面插进去视频免费观看| 国产乱来视频区| 午夜精品国产一区二区电影| 人体艺术视频欧美日本| 中文精品一卡2卡3卡4更新| 国产片特级美女逼逼视频| h视频一区二区三区| 久久免费观看电影| 日韩大片免费观看网站| 日韩制服骚丝袜av| 麻豆乱淫一区二区| 女人爽到高潮嗷嗷叫在线视频| 国产精品女同一区二区软件| av国产久精品久网站免费入址| 久久人人爽人人片av| 中文字幕制服av| 免费看av在线观看网站| 97人妻天天添夜夜摸| 亚洲四区av| 欧美国产精品va在线观看不卡| 少妇 在线观看| www.自偷自拍.com| 久久国产精品男人的天堂亚洲| 欧美黄色片欧美黄色片| 成年美女黄网站色视频大全免费| 免费在线观看黄色视频的| 国产1区2区3区精品| 狠狠精品人妻久久久久久综合| 在线天堂中文资源库| 国产 一区精品| 免费观看性生交大片5| 亚洲精品国产av蜜桃| 国产精品二区激情视频| www.av在线官网国产| 亚洲精品成人av观看孕妇| 自线自在国产av| 午夜福利乱码中文字幕| 天堂中文最新版在线下载| bbb黄色大片| av一本久久久久| 午夜福利影视在线免费观看| 亚洲精品中文字幕在线视频| 久久国产精品男人的天堂亚洲| 五月开心婷婷网| 丝袜人妻中文字幕| av又黄又爽大尺度在线免费看| 少妇猛男粗大的猛烈进出视频| 一级a爱视频在线免费观看| av在线app专区| 久久久久精品人妻al黑| 男女边摸边吃奶| 亚洲精品乱久久久久久| 中文字幕av电影在线播放| 一二三四在线观看免费中文在| 国产成人系列免费观看| 国产免费现黄频在线看| 91aial.com中文字幕在线观看| 午夜久久久在线观看| 丰满少妇做爰视频| 国产爽快片一区二区三区| 亚洲第一av免费看| 国产探花极品一区二区| 久久久久久久久久久久大奶| 极品人妻少妇av视频| 国产片内射在线| 亚洲国产精品成人久久小说| 亚洲成人免费av在线播放| 女性生殖器流出的白浆| 亚洲人成电影观看| svipshipincom国产片| 日本欧美国产在线视频| 男女午夜视频在线观看| 亚洲精华国产精华液的使用体验| 久久精品国产亚洲av高清一级| 日韩一卡2卡3卡4卡2021年| 啦啦啦中文免费视频观看日本| 亚洲欧美日韩另类电影网站| 久久精品熟女亚洲av麻豆精品| 国产av精品麻豆| 亚洲欧美成人综合另类久久久| 久久人人爽av亚洲精品天堂| 亚洲精品第二区| 无遮挡黄片免费观看| 亚洲av电影在线进入| 亚洲欧洲国产日韩| 久久ye,这里只有精品| 女人爽到高潮嗷嗷叫在线视频| 亚洲伊人久久精品综合| 日韩大码丰满熟妇| 亚洲国产av新网站| 亚洲国产欧美网| 麻豆乱淫一区二区| 老熟女久久久| 九草在线视频观看| av.在线天堂| 免费高清在线观看视频在线观看| 自线自在国产av| 在线观看www视频免费| 国产xxxxx性猛交| 久热这里只有精品99| 国产av精品麻豆| 菩萨蛮人人尽说江南好唐韦庄| 亚洲 欧美一区二区三区| 一边摸一边做爽爽视频免费| 日韩欧美一区视频在线观看| 亚洲欧美精品自产自拍| 久久青草综合色| 国产日韩欧美在线精品| 婷婷色综合大香蕉| 国产精品免费视频内射| 美女脱内裤让男人舔精品视频| 国产亚洲最大av| 九九爱精品视频在线观看| 满18在线观看网站| 好男人视频免费观看在线| 少妇被粗大的猛进出69影院| 日韩精品有码人妻一区| 亚洲欧美激情在线| 男女下面插进去视频免费观看| xxxhd国产人妻xxx| 国产日韩欧美在线精品| 在线观看免费午夜福利视频| 亚洲精品第二区| 一边亲一边摸免费视频| 久久久久国产精品人妻一区二区| 免费高清在线观看日韩| 我的亚洲天堂| 久久精品aⅴ一区二区三区四区| 99精品久久久久人妻精品| 亚洲一区中文字幕在线| 国产男女超爽视频在线观看| 综合色丁香网| 亚洲国产精品国产精品| 亚洲精品美女久久久久99蜜臀 | 日韩成人av中文字幕在线观看| 99久久综合免费| 老司机影院成人| 日韩制服丝袜自拍偷拍| 看免费成人av毛片| 精品国产乱码久久久久久小说| 啦啦啦视频在线资源免费观看| 老汉色∧v一级毛片| 久久鲁丝午夜福利片| 免费在线观看黄色视频的| 国产精品久久久久久精品电影小说| 黄色一级大片看看| 青青草视频在线视频观看| 国产日韩欧美在线精品| 免费不卡黄色视频| 熟妇人妻不卡中文字幕| 波多野结衣一区麻豆| 亚洲欧美中文字幕日韩二区| 中文字幕另类日韩欧美亚洲嫩草| 日日摸夜夜添夜夜爱| 一区二区日韩欧美中文字幕| 各种免费的搞黄视频| 亚洲精品中文字幕在线视频| 国产精品国产三级专区第一集| 欧美人与性动交α欧美软件| 黑丝袜美女国产一区| 欧美久久黑人一区二区| 一区福利在线观看| 亚洲国产欧美在线一区| 丁香六月天网| 99热国产这里只有精品6| 午夜激情av网站| 亚洲人成77777在线视频| 久久热在线av| 国产不卡av网站在线观看| 女人精品久久久久毛片| 自线自在国产av| 大香蕉久久成人网| 国产精品一区二区精品视频观看| 免费观看av网站的网址| av国产久精品久网站免费入址| 中文字幕人妻丝袜一区二区 | 免费黄频网站在线观看国产| 男女免费视频国产| 亚洲av日韩精品久久久久久密 | 中文字幕色久视频| 9热在线视频观看99| 久久亚洲国产成人精品v| 久久精品久久久久久噜噜老黄| 欧美日韩国产mv在线观看视频| 秋霞伦理黄片| 亚洲熟女精品中文字幕| 丝袜美足系列| 亚洲第一av免费看| 黄片无遮挡物在线观看| 又黄又粗又硬又大视频| 欧美老熟妇乱子伦牲交| 精品一区二区免费观看| 免费日韩欧美在线观看| 热99久久久久精品小说推荐| 欧美日韩视频精品一区| 国产免费视频播放在线视频| 国产精品久久久久久精品古装| 在线天堂中文资源库| 久久精品久久久久久噜噜老黄| 亚洲精品日本国产第一区| 亚洲人成网站在线观看播放| 日韩人妻精品一区2区三区| 国产免费视频播放在线视频| 欧美变态另类bdsm刘玥| 亚洲av成人精品一二三区| 国产激情久久老熟女| 亚洲欧美激情在线| 午夜福利,免费看| 又大又黄又爽视频免费| 久久久久精品性色| 黄片小视频在线播放| 亚洲国产av影院在线观看| 亚洲欧美中文字幕日韩二区| 大香蕉久久网| 最新在线观看一区二区三区 | 自拍欧美九色日韩亚洲蝌蚪91| a级毛片黄视频| 熟女av电影| 人人妻人人澡人人看| 亚洲国产最新在线播放| 男女无遮挡免费网站观看| av网站免费在线观看视频| 成人三级做爰电影| a级毛片黄视频| 亚洲第一av免费看| 国产精品av久久久久免费| 一级毛片 在线播放| 亚洲欧美一区二区三区久久| 伊人久久国产一区二区| 成人亚洲精品一区在线观看| 国产国语露脸激情在线看| av国产精品久久久久影院| 超碰97精品在线观看| 欧美激情 高清一区二区三区| 久久性视频一级片| 丰满乱子伦码专区| 美女国产高潮福利片在线看| 日本欧美视频一区| 大陆偷拍与自拍| 成人国语在线视频| 老司机深夜福利视频在线观看 | 好男人视频免费观看在线| 午夜福利一区二区在线看| 久久久精品国产亚洲av高清涩受| 午夜激情av网站| 国产精品一区二区在线观看99| 国产男人的电影天堂91| 飞空精品影院首页| 最近中文字幕2019免费版| 成人影院久久| 久久久久久人妻| 亚洲欧美精品自产自拍| 日本av手机在线免费观看| 久久久国产欧美日韩av| 色精品久久人妻99蜜桃| 久久久久久久精品精品| 亚洲图色成人| 纵有疾风起免费观看全集完整版| svipshipincom国产片| 一区二区三区激情视频| 国产成人一区二区在线| 极品人妻少妇av视频| 中文字幕最新亚洲高清| 天天躁日日躁夜夜躁夜夜| av视频免费观看在线观看| 日本午夜av视频| 亚洲精品国产av成人精品| 亚洲国产看品久久| 亚洲av中文av极速乱| 丝袜美足系列| 在线观看免费视频网站a站| 一区二区三区精品91| 国产av国产精品国产| 老熟女久久久| 麻豆av在线久日| 国产av国产精品国产| 午夜影院在线不卡| 在线观看免费日韩欧美大片| av在线播放精品| 麻豆精品久久久久久蜜桃| 久久精品国产亚洲av涩爱| 亚洲熟女精品中文字幕| 卡戴珊不雅视频在线播放| 久久国产精品男人的天堂亚洲| 操出白浆在线播放| 亚洲五月色婷婷综合| 成年美女黄网站色视频大全免费| 黄色毛片三级朝国网站| 亚洲欧美色中文字幕在线| 日本午夜av视频| 青春草国产在线视频| 天堂中文最新版在线下载| 在线观看免费高清a一片| 国产精品香港三级国产av潘金莲 | a级毛片在线看网站| 日韩免费高清中文字幕av| 高清视频免费观看一区二区| 午夜av观看不卡| 人人澡人人妻人| 久久久久久人人人人人| 国产在线免费精品| 日韩一卡2卡3卡4卡2021年| 午夜福利影视在线免费观看| 在线观看一区二区三区激情| 久久精品国产亚洲av高清一级| 制服人妻中文乱码| 在线观看www视频免费| 亚洲精品美女久久av网站| 一区二区av电影网| 一本大道久久a久久精品| 国产色婷婷99| 十八禁人妻一区二区| av不卡在线播放| a级片在线免费高清观看视频| 亚洲一码二码三码区别大吗| 丰满迷人的少妇在线观看| 老熟女久久久| 美女大奶头黄色视频| xxxhd国产人妻xxx| 精品亚洲成a人片在线观看| 交换朋友夫妻互换小说| 日韩欧美精品免费久久| 亚洲视频免费观看视频| 一级片'在线观看视频| 高清在线视频一区二区三区| 国产精品偷伦视频观看了| 夜夜骑夜夜射夜夜干| 久久亚洲国产成人精品v| 精品午夜福利在线看| 少妇 在线观看| 成人亚洲欧美一区二区av| 国产高清国产精品国产三级| 在线亚洲精品国产二区图片欧美| 欧美精品人与动牲交sv欧美| 国产1区2区3区精品| 天天躁夜夜躁狠狠躁躁| 免费女性裸体啪啪无遮挡网站| 精品一区二区三区av网在线观看 | 丰满迷人的少妇在线观看| videos熟女内射| 大香蕉久久成人网| 好男人视频免费观看在线| 巨乳人妻的诱惑在线观看| 亚洲激情五月婷婷啪啪| 黄色怎么调成土黄色| 久热爱精品视频在线9| 国产探花极品一区二区| 日韩大片免费观看网站| 一级片免费观看大全| 满18在线观看网站| 日韩成人av中文字幕在线观看| 91成人精品电影| 电影成人av| 久久99热这里只频精品6学生| 免费黄频网站在线观看国产| 中文字幕人妻熟女乱码| 久久久久国产精品人妻一区二区| 黑丝袜美女国产一区| 亚洲国产精品一区三区| 伊人久久国产一区二区| 亚洲av国产av综合av卡| 国产成人a∨麻豆精品| 午夜免费男女啪啪视频观看| 少妇人妻久久综合中文| 狂野欧美激情性bbbbbb| 伦理电影大哥的女人| 亚洲欧洲精品一区二区精品久久久 | 国产亚洲午夜精品一区二区久久| 性色av一级| 黑丝袜美女国产一区| 久久综合国产亚洲精品| 波多野结衣av一区二区av| 国产极品粉嫩免费观看在线| 99热全是精品| 国产成人精品无人区| 99久久综合免费| 国产一区二区三区综合在线观看| 欧美中文综合在线视频| 天天躁狠狠躁夜夜躁狠狠躁| 久久久久精品久久久久真实原创| 亚洲五月色婷婷综合| 国产免费福利视频在线观看| 欧美日韩国产mv在线观看视频| 国产精品二区激情视频| 亚洲免费av在线视频| 超碰97精品在线观看| 久久99一区二区三区| 制服人妻中文乱码| 在线观看人妻少妇| 日本午夜av视频| 老司机在亚洲福利影院| 亚洲中文av在线| 丰满乱子伦码专区| 亚洲欧美色中文字幕在线| 免费在线观看黄色视频的| 亚洲欧美一区二区三区国产| av.在线天堂| 亚洲精品av麻豆狂野| 日本欧美视频一区| 丝袜人妻中文字幕| 欧美人与性动交α欧美软件| 中文字幕人妻丝袜一区二区 | 久久人人97超碰香蕉20202| 国产一区二区激情短视频 | 亚洲欧美一区二区三区久久| 亚洲男人天堂网一区| 国产男女内射视频| 91成人精品电影| 99香蕉大伊视频| 亚洲三区欧美一区| 亚洲一码二码三码区别大吗| 99久久综合免费| 91精品三级在线观看| 黑人猛操日本美女一级片| 在线观看人妻少妇| 精品一区二区免费观看| 纯流量卡能插随身wifi吗| 大香蕉久久成人网| 亚洲五月色婷婷综合| 一级片免费观看大全| 久久久久精品性色| 亚洲国产精品一区二区三区在线| 丰满少妇做爰视频| 大香蕉久久网| 人人妻人人添人人爽欧美一区卜| 国产又色又爽无遮挡免| 欧美中文综合在线视频| av在线老鸭窝| 七月丁香在线播放| 亚洲专区中文字幕在线 | 九色亚洲精品在线播放| 久久精品国产亚洲av高清一级| 高清欧美精品videossex| 天天添夜夜摸| 国产免费视频播放在线视频| 叶爱在线成人免费视频播放| 丝袜美足系列| 欧美激情高清一区二区三区 | 久久久精品免费免费高清| 亚洲一级一片aⅴ在线观看| 狠狠精品人妻久久久久久综合| 大香蕉久久成人网| 丝袜脚勾引网站| 黄频高清免费视频| 男男h啪啪无遮挡| 尾随美女入室| 欧美日韩亚洲国产一区二区在线观看 | 十八禁高潮呻吟视频| 日韩伦理黄色片| 老汉色∧v一级毛片| 大香蕉久久成人网| 成年人午夜在线观看视频| 亚洲欧美一区二区三区黑人| 日韩免费高清中文字幕av| 亚洲人成77777在线视频| 咕卡用的链子| 男女之事视频高清在线观看 | 伦理电影免费视频| 亚洲精品一二三| 成人漫画全彩无遮挡| 深夜精品福利| 亚洲精品久久午夜乱码| 女人久久www免费人成看片| 久久韩国三级中文字幕| 欧美最新免费一区二区三区| av电影中文网址| 国产av码专区亚洲av| 超碰成人久久| 纵有疾风起免费观看全集完整版| 777久久人妻少妇嫩草av网站| 亚洲国产欧美一区二区综合| 欧美成人午夜精品| 丝袜人妻中文字幕| 五月天丁香电影| 亚洲国产精品一区二区三区在线| 欧美国产精品va在线观看不卡| 成年美女黄网站色视频大全免费| 无限看片的www在线观看| 大话2 男鬼变身卡| 又黄又粗又硬又大视频| 人人妻人人澡人人爽人人夜夜| 国产99久久九九免费精品| 午夜福利,免费看| 伦理电影免费视频| 人妻一区二区av| 欧美日韩视频高清一区二区三区二| 99re6热这里在线精品视频| 青青草视频在线视频观看| 久久精品国产亚洲av涩爱| 99久久99久久久精品蜜桃| 国产伦人伦偷精品视频| 色婷婷久久久亚洲欧美| 久久免费观看电影| 最近的中文字幕免费完整| 欧美亚洲 丝袜 人妻 在线| 一区二区三区激情视频| 中文欧美无线码| 飞空精品影院首页| 国产成人91sexporn| 精品一区二区三卡| svipshipincom国产片| 久久天堂一区二区三区四区| av天堂久久9| 深夜精品福利| 看免费av毛片| 国产在线免费精品| 精品卡一卡二卡四卡免费| 一级毛片黄色毛片免费观看视频|