arXiv subjects

Zuhui Fan

Publications and source records attributed to Zuhui Fan.

At least 37 records · Page 2Linked to original sources

arXiv2023

Weak lensing peak statistics -- steepness versus height

In weak-lensing cosmological studies, peak statistics is sensitive to nonlinear structures and thus complementary to cosmic shear two-point correlations. In this paper, we explore a new approach, namely, the peak steepness statistics, with the overall goal to understand the cosmological information embedded there in comparison with the commonly used peak height statistics. We perform the analyses with ray-tracing simulations considering different sets of cosmological parameters $Ω_{\rm m}$ and $σ_8$. A theoretical model to calculate the abundance of high peaks based on steepness is also presented, which can well describe the main trend of the peak distribution from simulations. We employ $Δχ^2$ and Fisher analyses to study the cosmological dependence of the two peak statistics using our limited sets of simulations as well as our theoretical model. Within our considerations without including potential systematic effects, the results show that the steepness statistics tends to have higher sensitivities to the cosmological parameters than the peak height statistics and this advantage is diluted with the increase of the shape noise. Using the theoretical model, we investigate the physical reasons accounting for the different cosmological information embedded in the two statistics. Our analyses indicate that the projection effect from large-scale structures plays an important role to enhance the gain from the steepness statistics. The redshift and cosmology dependence of dark matter halo density profiles also contributes to the differences between the two statistics.

astro-ph.CO↗

arXiv2022

Cosmological Studies from HSC-SSP Tomographic Weak Lensing Peak Abundances

We perform weak lensing tomographic peak studies using the first-year shear data from Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) survey. The effective area used in our analyses after field selection, mask and boundary exclusions is $\sim 58 °^2$. The source galaxies are divided into low- and high-redshift bins with $0.2\le z_p\le0.85$ and $0.85\le z_p\le1.5$, respectively. We utilize our halo-based theoretical peak model including the projection effect of large-scale structures to derive cosmological constraints from the observed tomographic high peak abundances with the signal-to-noise ratio in the range of $ν_{\rm N}=[3.5,5.5]$. These high peaks are closely associated with the lensing effects of massive clusters of galaxies. Thus the inclusion of their member galaxies in the shear catalog can lead to significant source clustering and dilute their lensing signals. We account for this systematic effect in our theoretical modelling. Additionally, the impacts of baryonic effects, galaxy intrinsic alignments, as well as residual uncertainties in shear and photometric redshift calibrations are also analyzed. Within the flat $Λ$CDM model, the derived constraint is $S_8=0.758_{-0.076}^{+0.033}$ and $0.768_{-0.057}^{+0.030}$ with the source clustering information measured from the two cluster catalogs, CAMIRA and WZL, respectively. The asymmetric uncertainties are due to the different degeneracy direction of $(Ω_{\rm m}, σ_8)$ from high peak abundances comparing to that from the cosmic shear two-point correlations which give rise approximately the power index $α=0.5$. Fitting to our constraints, we obtain $α\approx 0.38$ and $Σ_8=0.772_{-0.032}^{+0.028}$ (CAMIRA) and $0.781_{-0.033}^{+0.028}$ (WZL). In comparison with the results from non-tomographic peak analyses, the $1σ$ uncertainties on $Σ_8$ are reduced by a factor of $\sim1.3$.

astro-ph.CO↗

arXiv2022

Effects of galaxy intrinsic alignment on weak lensing peak statistics

The galaxy intrinsic alignment (IA) is a dominant source of systematics in weak lensing (WL) studies. In this paper, by employing large simulations with semi-analytical galaxy formation, we investigate the IA effects on WL peak statistics. Different simulated source galaxy samples of different redshift distributions are constructed, where both WL shear and IA signals are included. Convergence reconstruction and peak statistics are then performed for these samples. Our results show that the IA effects on peak abundances mainly consist of two aspects. One is the additional contribution from IA to the shape noise. The other is from the satellite IA that can affect the peak signals from their host clusters significantly. The latter depends on the level of inclusion in a shear sample of the satellite galaxies of the clusters that contribute to WL peaks, and thus is sensitive to the redshift distribution of source galaxies. We pay particular attention to satellite IA and adjust it artificially in the simulations to analyze the dependence of the satellite IA impacts on its strength. This information can potentially be incorporated into the modeling of WL peak abundances, especially for high peaks physically originated from massive clusters of galaxies, and thus to mitigate the IA systematics on the cosmological constraints derived from WL peaks.

astro-ph.CO↗

arXiv2022

Galaxy-galaxy lensing in the VOICE deep survey

The multi-band photometry of the VOICE imaging data, overlapping with 4.9 deg$^2$ of the Chandra Deep Field South (CDFS) area, enables both shape measurement and photometric redshift estimation to be the two essential quantities for weak lensing analysis. The depth of $mag_{AB}$ is up to 26.1 (5$σ$ limiting) in $r$-band. We estimate the Excess Surface Density (ESD; $ΔΣ$) based on galaxy-galaxy measurements around galaxies at lower redshift (0.10<$z_l$<0.35) while we select the background sources to be at higher redshift ranging from 0.3 to 1.5. The foreground galaxies are divided into two major categories according to their colour (blue/red), each of which has been further divided into high/low stellar mass bins. Then the halo masses of the samples are estimated by modelling the signals, and the posterior of the parameters are samples via Mote Carlo Markov Chain (MCMC) process. We compare our results with the existing Stellar-to-Halo Mass Relation (SHMR) and find that the blue low stellar mass bin (median $M_*=10^{8.31}M_\odot$) deviates from the SHMR relation whereas all other three samples agrees well with empirical curves. We interpret this discrepancy as the effect of a low star formation efficiency of the low-mass blue dwarf galaxy population dominated in the VOICE-CDFS area.

astro-ph.CO↗

arXiv2022

Forecast of Neutrino Cosmology from the CSST Photometric Galaxy Clustering and Cosmic Shear Surveys

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 $Σm_ν \lesssim 0.36$ (0.56) eV at 68\% (95\%) confidence level, and $Σm_ν \lesssim 0.23$ (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.

astro-ph.CO↗

arXiv2022

Dark Matter Halos in Interacting Dark Energy Models: Formation History, Density Profile, Spin and Shape

The interacting dark energy (IDE) model, which considers the interaction between dark energy and dark matter, provides a natural mechanism to alleviate the coincidence problem and can also relieve the observational tensions under the $Λ$CDM model. Previous studies have put constraints on IDE models by observations of cosmic expansion history, cosmic microwave background and large-scale structures. However, these data are not yet enough to distinguish IDE models from $Λ$CDM effectively. Because the non-linear structure formation contains rich cosmological information, it can provide additional means to differentiate alternative models. In this paper, based on a set of $N$-body simulations for IDE models, we investigate the formation histories and properties of dark matter halos, and compare with their $Λ$CDM counterparts. For the model with dark matter decaying into dark energy and the parameters being the best-fit values from previous constraints, the structure formation is markedly slowed down, and the halos have systematically lower mass, looser internal structure, higher spin and anisotropy. This is inconsistent with the observed structure formation, and thus this model can be safely ruled out from the perspective of non-linear structure formation. Moreover, we find that the ratio of halo concentrations between IDE and $Λ$CDM counterparts depends sensitively on the interaction parameter and is independent of halo mass. This can act as a powerful probe to constrain IDE models. Our results concretely demonstrate that the interaction of the two dark components can affect the halo formation considerably, and therefore the constraints from non-linear structures are indispensable.

astro-ph.CO↗

arXiv2021

Lenses In VoicE (LIVE): Searching for strong gravitational lenses in the VOICE@VST survey using Convolutional Neural Networks

We present a sample of 16 likely strong gravitational lenses identified in the VST Optical Imaging of the CDFS and ES1 fields (VOICE survey) using Convolutional Neural Networks (CNNs). We train two different CNNs on composite images produced by superimposing simulated gravitational arcs on real Luminous Red Galaxies observed in VOICE. Specifically, the first CNN is trained on single-band images and more easily identifies systems with large Einstein radii, while the second one, trained on composite RGB images, is more accurate in retrieving systems with smaller Einstein radii. We apply both networks to real data from the VOICE survey, taking advantage of the high limiting magnitude (26.1 in the r-band) and low PSF FWHM (0.8" in the r-band) of this deep survey. We analyse $\sim21,200$ images with $mag_r<21.5$, identifying 257 lens candidates. To retrieve a high-confidence sample and to assess the accuracy of our technique, nine of the authors perform a visual inspection. Roughly 75% of the systems are classified as likely lenses by at least one of the authors. Finally, we assemble the LIVE sample (Lenses In VoicE) composed by the 16 systems passing the chosen grading threshold. Three of these candidates show likely lensing features when observed by the Hubble Space Telescope. This work represents a further confirmation of the ability of CNNs to inspect large samples of galaxies searching for gravitational lenses. These algorithms will be crucial to exploit the full scientific potential of forthcoming surveys with the Euclid satellite and the Vera Rubin Observatory

astro-ph.GA↗

arXiv2021

Detection of Cosmic Magnification via Galaxy Shear -- Galaxy Number Density Correlation from HSC Survey Data

We propose a novel method to detect cosmic magnification signals by cross-correlating foreground convergence fields constructed from galaxy shear measurements with background galaxy positional distributions, namely shear-number density correlation. We apply it to the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) survey data. With 27 non-independent data points and their full covariance, $χ_0^2\approx 34.1$ and $χ_T^2\approx 24.0$ with respect to the null and the cosmological model with the parameters from HSC shear correlation analyses in Hamana et al. 2020 (arXiv:1906.06041), respectively. The Bayes factor of the two is $\log_{10}B_{T0}\approx 2.2$ assuming equal model probabilities of null and HSC cosmology, showing a clear detection of the magnification signals. Theoretically, the ratio of the shear-number density and shear-shear correlations can provide a constraint on the effective multiplicative shear bias $\bar m$ using internal data themselves. We demonstrate the idea with the signals from our HSC-SSP mock simulations and rescaling the statistical uncertainties to a survey of $15000°^2$. For two-bin analyses with background galaxies brighter than $m_{lim}=23$, the combined analyses lead to a forecasted constraint of $σ(\bar m) \sim 0.032$, $2.3$ times tighter than that of using the shear-shear correlation alone. Correspondingly, $σ(S_8)$ with $S_8=σ_8(Ω_\mathrm{m}/0.3)^{0.5}$ is tightened by $\sim 2.1$ times. Importantly, the joint constraint on $\bar m$ is nearly independent of cosmological parameters. Our studies therefore point to the importance of including the shear-number density correlation in weak lensing analyses, which can provide valuable consistency tests of observational data, and thus to solidify the derived cosmological constraints.

astro-ph.CO↗

arXiv2021

Spectroscopic and Photometric Redshift Estimation by Neural Networks For the China Space Station Optical Survey (CSS-OS)

The estimation of spectroscopic and photometric redshifts (spec-z and photo-z) is crucial for future cosmological surveys. It can directly affect several powerful measurements of the Universe, e.g. weak lensing and galaxy clustering. In this work, we explore the accuracies of spec-z and photo-z that can be obtained in the China Space Station Optical Surveys (CSS-OS), which is a next-generation space survey, using neural networks. The 1-dimensional Convolutional Neural Networks (1-d CNN) and Multi-Layer Perceptron (MLP, one of the simplest forms of Artificial Neural Network) are employed to derive the spec-z and photo-z, respectively. The mock spectral and photometric data used for training and testing the networks are generated based on the COSMOS catalog. The networks have been trained with noisy data by creating Gaussian random realizations to reduce the statistical effects, resulting in similar redshift accuracy for both high-SNR (signal to noise ratio) and low-SNR data. The probability distribution functions (PDFs) of the predicted redshifts are also derived via Gaussian random realizations of the testing data, and then the best-fit redshifts and 1-sigma errors also can be obtained. We find that our networks can provide excellent redshift estimates with accuracies ~0.001 and 0.01 on spec-z and photo-z, respectively. Compared to existing photo-z codes, our MLP has similar accuracy but is more efficient in the training process. The fractions of catastrophic redshifts or outliers can be dramatically suppressed comparing to the ordinary template-fitting method. This indicates that the neural network method is feasible and powerful for spec-z and photo-z estimations in future cosmological surveys.

astro-ph.CO↗

arXiv2020

Deep Learning for Strong Lensing Search: Tests of the Convolutional Neural Networks and New Candidates from KiDS DR3

Convolutional Neutral Networks have been successfully applied in searching for strong lensing systems, leading to discoveries of new candidates from large surveys. On the other hand, systematic investigations about their robustness are still lacking. In this paper, we first construct a neutral network, and apply it to $r$-band images of Luminous Red Galaxies (LRGs) of the Kilo Degree Survey (KiDS) Data Release 3 to search for strong lensing systems. We build two sets of training samples, one fully from simulations, and the other one using the LRG stamps from KiDS observations as the foreground lens images. With the former training sample, we find 48 high probability candidates after human-inspection, and among them, 27 are newly identified. Using the latter training set, about 67\% of the aforementioned 48 candidates are also found, and there are 11 more new strong lensing candidates identified. We then carry out tests on the robustness of the network performance with respect to the variation of PSF. With the testing samples constructed using PSF in the range of 0.4 to 2 times of the median PSF of the training sample, we find that our network performs rather stable, and the degradation is small. We also investigate how the volume of the training set can affect our network performance by varying it from 0.1 millions to 0.8 millions. The output results are rather stable showing that within the considered range, our network performance is not very sensitive to the volume size.

astro-ph.CO↗

arXiv2020

An accurate analytic mass model for lensing galaxies

We develop an analytic mass model for lensing galaxies, based on a broken power-law (BPL) density profile, which is a power-law profile with a mass deficit or surplus in the central region. Under the assumption of an elliptically symmetric surface mass distribution, the deflection angle and magnification can be evaluated analytically for this new model. We compute the theoretical prediction for various quantities, including the volume and surface mass density profiles of the galaxies, and the aperture and luminosity-weighted line-of-sight velocity dispersions, and compare them to those measured from the Illustris simulation. We find an excellent agreement between our model prediction and the simulation, which validates our modeling. The high efficiency and accuracy of our model manifests itself as a promising tool for studying properties of galaxies with strong lensing.

astro-ph.GA↗

arXiv2020

Black hole shadow as a standard ruler in cosmology

Advancements in the black hole shadow observations may allow us not only to investigate physics in the strong gravity regime, but also to use them in cosmological studies. In this paper, we propose to use the shadow of supermassive black holes as a standard ruler for cosmological applications assuming the black hole mass can be determined independently. First, observations at low redshift distances can be used to constrain the Hubble constant independently. Secondly, the angular size of shadows of high redshift black holes is increased due to cosmic expansion and may also be reachable with future observations. This would allow us to probe the cosmic expansion history for the redshift range elusive to other distance measurements. Additionally, shadow can be used to estimate the mass of black holes at high redshift, assuming that cosmology is known.

gr-qc↗

arXiv2020

Variability and transient search in the SUDARE-VOICE field: a new method to extract the light curves

The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey, in synergy with the SUDARE survey, is a deep optical $ugri$ imaging of the CDFS and ES1 fields using the VLT Survey Telescope (VST). The observations for the CDFS field comprise about 4.38 deg$^2$ down to $r\sim26$ mag. The total on-sky time spans over four years in this field, distributed over four adjacent sub-fields. In this paper, we use the multi-epoch $r$-band imaging data to measure the variability of the detected objects and search for transients. We perform careful astrometric and photometric calibrations and point spread function (PSF) modeling. A new method, referring to as differential running-average photometry, is proposed to measure the light curves of the detected objects. With the method, the difference of PSFs between different epochs can be reduced, and the background fluctuations are also suppressed. Detailed uncertainty analysis and detrending corrections on the light curves are performed. We visually inspect the light curves to select variable objects, and present some objects with interesting light curves. Further investigation of these objects in combination with multi-band data will be presented in our forthcoming paper.

astro-ph.IM↗

arXiv2020

The Weak Lensing Peak Statistics in the Mocks by the inverse-Gaussianization Method

We apply the inverse-Gaussianization method proposed in \citealt{arXiv:1607.05007} to fast produce weak lensing convergence maps and investigate the peak statistics, including the peak height counts and peak steepness counts, in these mocks. We find that the distribution of peak height and steepness is in good agreement with the simulation. The difference is $\lesssim 20\%$ for these peak statistics in the maps at source redshift $z_s=1$. Besides, the loss of off-diagonal elements in peak covariance motivates us to consider the super sample variance in weak lensing peak statistics. We propose correction methods to effectively recover the (anti-)correlation among different bins by adding scatters in the mean value of these mocks. Finally, as an example of the application, we adopt the improved inverse-Gaussianization method with the above improvement to fast generate 40,000 mocks to calculate precision matrices between the power spectrum and peak statistics.

astro-ph.CO↗

arXiv2019

Cosmological studies from tomographic weak lensing peak abundances and impacts of photo-z errors

Weak lensing peak abundance analyses have been applied in different surveys and demonstrated to be a powerful statistics in extracting cosmological information complementary to cosmic shear two-point correlation studies. Future large surveys with high number densities of galaxies enable tomographic peak analyses. Focusing on high peaks, we investigate quantitatively how the tomographic redshift binning can enhance the cosmological gains. We also perform detailed studies about the degradation of cosmological information due to photometric redshift (photo-z) errors. We show that for surveys with the number density of galaxies $\sim40\,{\rm arcmin^{-2}}$, the median redshift $\sim1$, and the survey area of $\sim15000\,{\rm deg^{2}}$, the 4-bin tomographic peak analyses can reduce the error contours of $(Ω_{\rm m},σ_{8})$ by a factor of $5$ comparing to 2-D peak analyses in the ideal case of photo-z error being absent. More redshift bins can hardly lead to significantly better constraints. The photo-z error model here is parametrized by $z_{\rm bias}$ and $σ_{\rm ph}$ and the fiducial values of $z_{\rm bias}=0.003$ and $σ_{\rm ph}=0.02$ is taken. We find that using tomographic peak analyses can constrain the photo-z errors simultaneously with cosmological parameters. For 4-bin analyses, we can obtain $σ(z_{\rm bias})/z_{\rm bias}\sim10\%$ and $σ(σ_{\rm ph})/σ_{\rm ph}\sim5\%$ without assuming priors on them. Accordingly, the cosmological constraints on $Ω_{\rm m}$ and $σ_{8}$ degrade by a factor of $\sim2.2$ and $\sim1.8$, respectively, with respect to zero uncertainties on photo-z parameters. We find that the uncertainty of $z_{\rm bias}$ plays more significant roles in degrading the cosmological constraints than that of $σ_{\rm ph}$.

astro-ph.CO↗

arXiv2019

Cosmology from the Chinese Space Station Optical Survey (CSS-OS)

The Chinese Space Station Optical Survey (CSS-OS) is a planned full sky survey operated by the Chinese Space Station Telescope (CSST). It can simultaneously perform the photometric imaging and spectroscopic slitless surveys, and will probe weak and strong gravitational lensing, galaxy clustering, individual galaxies and galaxy clusters, active galactic nucleus (AGNs), and so on. It aims to explore the properties of dark matter and dark energy and other important cosmological problems. In this work, we focus on two main CSS-OS scientific goals, i.e. the weak gravitational lensing (WL) and galaxy clustering surveys. We generate the mock CSS-OS data based on the observational COSMOS and zCOSMOS catalogs. We investigate the constraints on the cosmological parameters from the CSS-OS using the Markov Chain Monte Carlo (MCMC) method. The intrinsic alignments, galaxy bias, velocity dispersion, and systematics from instrumental effects in the CSST WL and galaxy clustering surveys are also included, and their impacts on the constraint results are discussed. We find that the CSS-OS can improve the constraints on the cosmological parameters by a factor of a few (even one order of magnitude in the optimistic case), compared to the current WL and galaxy clustering surveys. The constraints can be further enhanced when performing joint analysis with the WL, galaxy clustering, and galaxy-galaxy lensing data. Therefore, the CSS-OS is expected to be a powerful survey for exploring the Universe. Since some assumptions may be still optimistic and simple, it is possible that the results from the real survey could be worse. We will study these issues in details with the help of simulations in the future.

astro-ph.CO↗

arXiv2019

Testing Shear Recovery with Field Distortion

The tilt, rotation, or offset of each CCD with respect to the focal plane, as well as the distortion of the focal plane itself, cause shape distortions to the observed objects, an effect typically known as field distortion (FD). We point out that FD provides a unique way of quantifying the accuracy of cosmic shear measurement. The idea is to stack the shear estimators from galaxies that share similar FD-induced shape distortions. Given that the latter can be calculated with parameters from astrometric calibrations, the accuracy of the shear estimator can be directly tested on real images. It provides a way to calibrate the multiplicative and additive shear recovery biases within the scientific data itself, without requiring simulations or any external data sets. We use the CFHTLenS images to demonstrate the accuracy of the Fourier_Quad shear recovery method. We highlight some details in our image processing pipeline, including background removal, source identification and deblending, astrometric calibration, star selection for PSF reconstruction, noise reduction, etc.. We show that in the shear ranges of -0.005 < g_1 < 0.005 and -0.008 < g_2 < 0.008, the multiplicative biases are at the level of < 0.04. Slight additive biases on the order of 5E-4 (6 sigma) are identified for sources provided by the official CFHTLenS catalog (not using its shear catalog), but are minor (4 sigma) for source catalog generated by our Fourier_Quad pipeline.

astro-ph.CO↗

arXiv2018

Deep CFHT Y-band imaging of VVDS-F22 field: I. data products and photometric redshifts

We present our deep $Y$-band imaging data of a two square degree field within the F22 region of the VIMOS VLT Deep Survey. The observations were conducted using the WIRCam instrument mounted at the Canada--France--Hawaii Telescope (CFHT). The total on-sky time was 9 hours, distributed uniformly over 18 tiles. The scientific goals of the project are to select faint quasar candidates at redshift $z>2.2$, and constrain the photometric redshifts for quasars and galaxies. In this paper, we present the observation and the image reduction, as well as the photometric redshifts that we derived by combining our $Y$-band data with the CFHTLenS $u^*g'r'i'z'$ optical data and UKIDSS DXS $JHK$ near-infrared data. With $J$-band image as reference total $\sim$80,000 galaxies are detected in the final mosaic down to $Y$-band $5σ$ point source limiting depth of 22.86 mag. Compared with the $\sim$3500 spectroscopic redshifts, our photometric redshifts for galaxies with $z<1.5$ and $i'\lesssim24.0$ mag have a small systematic offset of $|Δ{z}|\lesssim0.2$, 1$σ$ scatter $0.03<σ_{Δz} < 0.06$, and less than 4.0% of catastrophic failures. We also compare to the CFHTLenS photometric redshifts, and find that ours are more reliable at $z\gtrsim0.6$ because of the inclusion of the near-infrared bands. In particular, including the $Y$-band data can improve the accuracy at $z\sim 1.0-2.0$ because the location of the 4000Å-break is better constrained. The $Y$-band images, the multi-band photometry catalog and the photometric redshifts are released at \url{http://astro.pku.edu.cn/astro/data/DYI.html}.

astro-ph.GA↗