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Xiangkun Liu

Publications and source records attributed to Xiangkun Liu.

At least 37 records · Page 2Linked to original sources

Black hole mass and optical radiation mechanism of the tidal disruption event AT 2023clx

We present the optical light curves of the tidal disruption event (TDE) AT 2023clx in the declining phase, observed with Mephisto. Combining our light curve with the ASAS-SN and ATLAS data in the rising phase, and fitting the composite multi-band light curves with MOSFiT, we estimate black hole mass of AT 2023clx is between $10^{5.67}$--$10^{5.82}~M_{\odot}$. This event may be caused by either a full disruption of a $0.1~M_{\odot}$ star, or a partial disruption of a $0.99~M_{\odot}$ star, depending on the data adopted for the rising phase. Based on those fit results and the non-detection of soft X-ray photons in the first 90 days, we propose that the observed optical radiation is powered by stream-stream collision. We speculate that the soft X-ray photons may gradually emerge in 100--600 days after the optical peak, when the debris is fully circularized into a compact accretion disk.

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Early-phase simultaneous multiband observations of the Type II supernova SN 2024ggi with Mephisto

We present early-phase good-cadence (hour-to-day) simultaneous multiband ($ugi$ and $vrz$ bands) imaging of the nearby supernova SN~2024ggi, which exploded in the nearby galaxy, NGC 3621. A quick follow-up was conducted within less than a day after the explosion and continued $\sim$23 days. The $uvg$ band light curves display a rapid rise ($\sim$1.4 mag day$^{-1}$) to maximum in $\sim$4 days and absolute magnitude $M_{g}\sim$--17.75 mag. The post-peak decay rate in redder bands is $\sim$0.01 mag day$^{-1}$. Different colors (e.g., $u-g$ and $v-r$) of SN~2024ggi are slightly redder than SN 2023ixf. A significant rise ($\sim$12.5 kK) in black-body temperature (optical) was noticed within $\sim$2 days after the explosion, which successively decreased, indicating shock break out inside a dense circumstellar medium (CSM) surrounding the progenitor. Using semianalytical modeling, the ejecta mass and progenitor radius were estimated as 1.2 $M_\odot$ and $\sim$550 $R_\odot$. The archival deep images ($g,r,i and z$ bands) from the Dark Energy Camera Legacy Survey were examined, and a possible progenitor was detected in each band ($\sim$22--22.5 mag) and had a mass range of 14--17 $M_\odot$.

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Multiband Simultaneous Photometry of Type II SN 2023ixf with Mephisto and the Twin 50-cm Telescopes

SN 2023ixf, recently reported in the nearby galaxy M101 at a distance of $6.85~{\rm Mpc}$, was one of the closest and brightest core-collapse supernovae (CCSNe) in the last decade. In this work, we present multi-wavelength photometric observation of SN 2023ixf with the Multi-channel Photometric Survey Telescope (Mephisto) in $uvgr$ bands and with the twin 50-cm telescopes in $griz$ bands. We find that the bolometric luminosity reached the maximum value of $3\times10^{43}~{\rm erg~s^{-1}}$ at 3.9 days after the explosion and fully settled onto the radioactive tail at $\sim90$ days. The effective temperature decreased from $3.2\times10^4~{\rm K}$ at the first observation and approached to a constant of $\sim(3000-4000)~{\rm K}$ after the first two months. The evolution of the photospheric radius is consistent with a homologous expansion with a velocity of $8700~{\rm km~s^{-1}}$ in the first two months, and it shrunk subsequently. Based on the radioactive tail, the initial nickel mass is about $M_{\rm Ni}\sim 0.098M_\odot$. The explosion energy and the ejecta mass are estimated to be $E\simeq(1.0-5.7)\times10^{51}~{\rm erg}$ and $M_{\rm ej}\simeq(3.8-16)M_\odot$, respectively. The peak bolometric luminosity is proposed to be contributed by the interaction between the ejecta and the circumstellar medium (CSM). We find a shocked CSM mass of $M_{\rm CSM}\sim0.013M_\odot$, a CSM density of $ρ_{\rm CSM}\sim2.5\times10^{-13}~{\rm g~cm^{-3}}$ and a mass loss rate of the progenitor of $\dot M\sim0.022M_\odot~{\rm yr^{-1}}$.

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The Pre-explosion Environments and The Progenitor of SN 2023ixf from the Hobby Eberly Telescope Dark Energy Experiment (HETDEX)

Supernova (SN) 2023ixf was discovered on May 19th, 2023. The host galaxy, M101, was observed by the Hobby Eberly Telescope Dark Energy Experiment (HETDEX) collaboration over the period April 30, 2020 -- July 10, 2020, using the Visible Integral-field Replicable Unit Spectrograph (VIRUS; $3470\lesssimλ\lesssim5540$ Å) on the 10-m Hobby-Eberly Telescope (HET). The fiber filling factor within $\pm$ 30 arcsec of SN 2023ixf is 80% with a spatial resolution of 1 arcsec. The r<5.5 arcsec surroundings are 100% covered. This allows us to analyze the spatially resolved pre-explosion local environments of SN 2023ixf with nebular emission lines. The 2-dimensional (2D) maps of the extinction and the star-formation rate (SFR) surface density ($Σ_{\rm SFR}$) show weak increasing trends in the radial distributions within the r<5.5 arcsec regions, suggesting lower values of extinction and SFR in the vicinity of the progenitor of SN 2023ixf. The median extinction and that of the surface density of SFR within r<3 arcsec are $E(B-V)=0.06\pm0.14$, and $Σ_{\rm SFR}=10^{-5.44\pm0.66}~\rm M_{\odot}\cdot yr^{-1}\cdot arcsec^{-2}$. There is no significant change in extinction before and after the explosion. The gas metallicity does not change significantly with the separation from SN 2023ixf. The metal-rich branch of the $R_{23}$ calculations indicates that the gas metallicity around SN 2023ixf is similar to the solar metallicity ($\sim Z_{\odot}$). The archival deep images from the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) show a clear detection of the progenitor of SN 2023ixf in the $z$-band at $22.778\pm0.063$ mag, but non-detections in the remaining four bands of CFHTLS ($u,g,r,i$). The results suggest a massive progenitor of $\approx$ 22 $M_\odot$.

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A 12.4 day periodicity in a close binary system after a supernova

Neutron stars and stellar-mass black holes are the remnants of massive star explosions. Most massive stars reside in close binary systems, and the interplay between the companion star and the newly formed compact object has been theoretically explored, but signatures for binarity or evidence for the formation of a compact object during a supernova explosion are still lacking. Here we report a stripped-envelope supernova, SN 2022jli, which shows 12.4-day periodic undulations during the declining light curve. Narrow H$α$ emission is detected in late-time spectra with concordant periodic velocity shifts, likely arising from hydrogen gas stripped from a companion and accreted onto the compact remnant. A new Fermi/LAT $γ$-ray source is temporally and positionally consistent with SN 2022jli. The observed properties of SN 2022jli, including periodic undulations in the optical light curve, coherent H$α$ emission shifting, and evidence for association with a $γ$-ray source, point to the explosion of a massive star in a binary system leaving behind a bound compact remnant. Mass accretion from the companion star onto the compact object powers the light curve of the supernova and generates the $γ$-ray emission.

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Void Lensing in Cubic Galileon Gravity

Weak lensing studies via cosmic voids are a promising probe of Modified Gravity (MG). Excess surface mass density (ESD) is widely used as a lensing statistic in weak lensing research. In this paper, we use the ray-tracing method to study the ESD around voids in simulations based on Cubic Galileon (CG) gravity. With the compilation of N-body simulation and ray-tracing method, changes in structure formation and deflection angle resulting from MG can both be considered, making the extraction of lensing signals more realistic. We find good agreements between the measurement and theoretical prediction of ESD for CG gravity. Meanwhile, the lensing signals are much less affected by the change of the deflection angle than the change of the structure formation, indicating a good approximation of regarding ESD (statistics) as the projection of 3D dark matter density field. Finally, we demonstrate that it is impossible to distinguish CG and General Relativity in our simulation, however, in the next-generation survey, thanks to the large survey area and the increased galaxy number density, detecting the differences between these two models is possible. The methodology employed in this paper that combines N-body simulation and ray-tracing method can be a robust way to measure the lensing signals from simulations based on the MGs, and especially on that which significantly modifies the deflection angle.

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Forecast of cross-correlation of CSST cosmic shear tomography with AliCPT-1 CMB lensing

We present a forecast study on the cross-correlation between cosmic shear tomography from the Chinese Survey Space Telescope (CSST) and CMB lensing from Ali CMB Polarization Telescope (AliCPT-1) in Tibet. The correlated galaxy and CMB lensing signals were generated from Gaussian realizations based on inputted auto- and cross-spectra. To account for the error budget, we considered the CMB lensing reconstruction noise based on the AliCPT-1 lensing reconstruction pipeline; shape noise of the galaxy lensing measurement; CSST photo-$z$ error; photo-$z$ bias; intrinsic alignment effect, and multiplicative bias. The AliCPT-1 CMB lensing mock data were generated according to two experimental stages, namely the ``4 modules*yr'' and ``48 modules*yr'' cases. We estimate the cross-spectra in 4 tomographic bins according to the CSST photo-$z$ distribution in the range of $z\in[0,4)$. After reconstructing the pseudo-cross-spectra from the realizations, we calculate the signal-to-noise ratio (SNR). By combining the 4 photo-$z$ bins, the total cross-correlation SNR$\approx15$ (AliCPT-1 ``4 modules*yr'') and SNR$\approx22$ (AliCPT-1 ``48 modules*yr''). Finally, we study the cosmological application of this cross-correlation signal. Excluding intrinsic alignment (IA) in the template fitting would lead to roughly a $0.6σ$ increment in $σ_8$ due to the negative IA contribution to the galaxy lensing data. For AliCPT-1 first and second stages, the cross-correlation of CSST cosmic shear with CMB lensing gives errors on the clustering amplitude $σ_{σ_8}=^{+0.043}_{-0.038}$ or $σ_{S_8}=\pm 0.031$ and $σ_{σ_8}=^{+0.030}_{-0.027}$ or $σ_{S_8}=\pm 0.018$, respectively.

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KiDS-1000: cross-correlation with Planck cosmic microwave background lensing and intrinsic alignment removal with self-calibration

Galaxy shear - cosmic microwave background (CMB) lensing convergence cross-correlations contain additional information on cosmology to auto-correlations. While being immune to certain systematic effects, they are affected by the galaxy intrinsic alignments (IA). This may be responsible for the reported low lensing amplitude of the galaxy shear $\times$ CMB convergence cross-correlations, compared to the standard Planck $Λ$CDM (cosmological constant and cold dark matter) cosmology prediction. In this work, we investigate how IA affects the Kilo-Degree Survey (KiDS) galaxy lensing shear - Planck CMB lensing convergence cross-correlation and compare it to previous treatments with or without IA taken into consideration. More specifically, we compare marginalization over IA parameters and the IA self-calibration (SC) method (with additional observables defined only from the source galaxies) and prove that SC can efficiently break the degeneracy between the CMB lensing amplitude $A_{\rm lens}$ and the IA amplitude $A_{\rm IA}$. We further investigate how different systematics affect the resulting $A_{\rm IA}$ and $A_{\rm lens}$, and validate our results with the MICE2 simulation. We find that by including the SC method to constrain IA, the information loss due to the degeneracy between CMB lensing and IA is strongly reduced. The best-fit values are $A_{\rm lens}=0.84^{+0.22}_{-0.22}$ and $A_{\rm IA}=0.60^{+1.03}_{-1.03}$, while different angular scale cuts can affect $A_{\rm lens}$ by $\sim10\%$. We show that appropriate treatment of the boost factor, cosmic magnification, and photometric redshift modeling is important for obtaining the correct IA and cosmological results.

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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.

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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 $\sim1.3$.

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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.

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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.

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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.

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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.

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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.

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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 $σ_{\rm ph}$.

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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.

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Weak Lensing Study in VOICE Survey I: Shear Measurement

The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey is a Guaranteed Time program carried out with the ESO/VST telescope to provide deep optical imaging over two 4 deg$^2$ patches of the sky centred on the CDFS and ES1 pointings. We present the cosmic shear measurement over the 4 deg$^2$ covering the CDFS region in the $r$-band using LensFit. Each of the four tiles of 1 deg$^2$ has more than one hundred exposures, of which more than 50 exposures passed a series of image quality selection criteria for weak lensing study. The $5σ$ limiting magnitude in $r$- band is 26.1 for point sources, which is $\sim$1 mag deeper than other weak lensing survey in the literature (e.g. the Kilo Degree Survey, KiDS, at VST). The photometric redshifts are estimated using the VOICE $u,g,r,i$ together with near-infrared VIDEO data $Y,J,H,K_s$. The mean redshift of the shear catalogue is 0.87, considering the shear weight. The effective galaxy number density is 16.35 gal/arcmin$^2$, which is nearly twice the one of KiDS. The performance of LensFit on such a deep dataset was calibrated using VOICE-like mock image simulations. Furthermore, we have analyzed the reliability of the shear catalogue by calculating the star-galaxy cross-correlations, the tomographic shear correlations of two redshift bins and the contaminations of the blended galaxies. As a further sanity check, we have constrained cosmological parameters by exploring the parameter space with Population Monte Carlo sampling. For a flat $Λ$CDM model we have obtained $Σ_8$ = $σ_8(Ω_m/0.3)^{0.5}$ = $0.68^{+0.11}_{-0.15}$.

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