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Fuyu Dong

Publications and source records attributed to Fuyu Dong.

29 records · Page 2Linked to original sources

Cross-correlation of Planck CMB lensing with DESI galaxy groups

We measure the cross-correlation between galaxy groups constructed from DESI Legacy Imaging Survey DR8 and \emph{Planck} CMB lensing, over overlapping sky area of 16876 $\rm deg^2$. The detections are significant and consistent with the expected signal of the large-scale structure of the universe, over group samples of various redshift, mass, richness $N_{\rm g}$ and over various scale cuts. The overall S/N is 40 for a conservative sample with $N_{\rm g}\geq 5$, and increases to $50$ for the sample with $N_{\rm g}\geq 2$. Adopting the \emph{Planck} 2018 cosmology, we constrain the density bias of groups with $N_{\rm g}\geq 5$ as $b_{\rm g}=1.31\pm 0.10$, $2.22\pm 0.10$, $3.52\pm 0.20$ at $0.1<z\leq 0.33$, $0.33<z\leq 0.67$, $0.67<z\leq1$ respectively. The group catalog provides the estimation of group halo mass and therefore allows us to detect the dependence of bias on group mass with high significance. It also allows us to compare the measured bias with the theoretically predicted one using the estimated group mass. We find excellent agreement for the two high redshift bins. However, it is lower than the theory by $\sim 3σ$ for the lowest redshift bin. Another interesting finding is the significant impact of the thermal Sunyaev Zel'dovich (tSZ). It contaminates the galaxy group-CMB lensing cross-correlation at $\sim 30\%$ level, and must be deprojected first in CMB lensing reconstruction.

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Detection of cross-correlation between CMB Lensing and low-density points

Low Density Points (LDPs, \citet{2019ApJ...874....7D}), obtained by removing high-density regions of observed galaxies, can trace the Large-Scale Structures (LSSs) of the universe. In particular, it offers an intriguing opportunity to detect weak gravitational lensing from low-density regions. In this work, we investigate tomographic cross-correlation between Planck CMB lensing maps and LDP-traced LSSs, where LDPs are constructed from the DR8 data release of the DESI legacy imaging survey, with about $10^6$-$10^7$ galaxies. We find that, due to the large sky coverage (20,000 deg$^2$) and large redshift depth ($z\leq 1.2$), a significant detection ($10σ$--$30σ$) of the CMB lensing-LDP cross-correlation in all six redshift bins can be achieved, with a total significance of $\sim 53σ$ over $ \ell\le1024$. Moreover, the measurements are in good agreement with a theoretical template constructed from our numerical simulation in the WMAP 9-year $Λ$CDM cosmology. A scaling factor for the lensing amplitude $A_{\rm lens}$ is constrained to $A_{\rm lens}=1\pm0.12$ for $z<0.2$, $A_{\rm lens}=1.07\pm0.07$ for $0.2<z<0.4$ and $A_{\rm lens}=1.07\pm0.05$ for $0.4<z<0.6$, with the r-band absolute magnitude cut of $-21.5$ for LDP selection. A variety of tests have been performed to check the detection reliability, against variations in LDP samples and galaxy magnitude cuts, masks, CMB lensing maps, multipole $\ell$ cuts, sky regions, and photo-z bias. We also perform a cross-correlation measurement between CMB lensing and galaxy number density, which is consistent with the CMB lensing-LDP cross-correlation. This work therefore further convincingly demonstrates that LDP is a competitive tracer of LSS.

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The clustering of galaxies in the DESI imaging legacy surveys DR8: I. the luminosity and color dependent intrinsic clustering

In a recent study, we developed a method to model the impact of photometric redshift uncertainty on the two-point correlation function (2PCF). In this method, we can obtain both the intrinsic clustering strength and the photometric redshift errors simultaneously by fitting the projected 2PCF with two integration depths along the line-of-sight. Here we apply this method to the DESI Legacy Imaging Surveys Data Release 8 (LS DR8), the largest galaxy sample currently available. We separate galaxies into 20 samples in 8 redshift bins from $z=0.1$ to $z=1.0$, and a few $\rm z$-band absolute magnitude bins, with $M_{\rm z} \le -20$. These galaxies are further separated into red and blue sub-samples according to their $M^{0.5}_{\rm r}-M^{0.5}_{\rm z}$ colors. We measure the projected 2PCFs for all these galaxy (sub-)samples, and fit them using our photometric redshift 2PCF model. We find that the photometric redshift errors are smaller in red sub-samples than the overall population. On the other hand, there might be some systematic photometric redshift errors in the blue sub-samples, so that some of the sub-samples show significantly enhanced 2PCF at large scales. Therefore, focusing only on the red and all (sub-)samples, we find that the biases of galaxies in these (sub-)samples show clear color, redshift and luminosity dependencies, in that red brighter galaxies at higher redshift are more biased than their bluer and low redshift counterparts. Apart from the best fit set of parameters, $σ_{z}$ and $b$, from this state-of-the-art photometric redshift survey, we obtain high precision intrinsic clustering measurements for these 40 red and all galaxy (sub-)samples. These measurements on large and small scales hold important information regarding the cosmology and galaxy formation, which will be used in our subsequent probes in this series.

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Towards a Bias-Free Selection Function in Shear Measurement

Sample selection is a necessary preparation for weak lensing measurement. It is well-known that selection itself may introduce bias in the measured shear signal. Using image simulation and the Fourier_Quad shear measurement pipeline, we quantify the selection bias in various commonly used selection function (signal-to-noise-ratio, magnitude, etc.). We proposed a new selection function defined in the power spectrum of the galaxy image. This new selection function has low selection bias, and it is particularly convenient for shear measurement pipelines based on Fourier transformation.

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Measuring the integrated Sachs-Wolfe effect from the low-density regions of the universe

The integrated Sachs-Wolfe (ISW) effect is caused by the decay of cosmological gravitational potential, and is therefore a unique probe of dark energy. However, its robust detection is still problematic. Various tensions between different data sets, different large scale structure (LSS) tracers, and between data and the $Λ$CDM theory prediction, exist. We propose a novel method of ISW measurement by cross correlating CMB and the LSS traced by "low-density-position" (LDP, \citet{2019ApJ...874....7D}). It isolates the ISW effect generated by low-density regions of the universe, but insensitive to selection effects associated with voids. We apply it to the DR8 galaxy catalogue of the DESI Legacy imaging surveys, and obtain the LDPs at $z\leq 0.6$ over $\sim$ 20000 $deg^2$ sky coverage. We then cross correlate with the Planck temperature map, and detect the ISW effect at $3.2σ$. We further compare the measurement with numerical simulations of the concordance $Λ$CDM cosmology, and find the ISW amplitude parameter $A_{ISW}=1.14\pm0.38$ when we adopt a LDP definition radius $R_s=3^{'}$, fully consistent with the prediction of the standard $Λ$CDM cosmology ($A_{ISW}=1$). This agreement with $Λ$CDM cosmology holds for all the galaxy samples and $R_s$ that we have investigated. Furthermore, the S/N is comparable to that of galaxy ISW measurement. These results demonstrate the LDP method as a competitive alternative to existing ISW measurement methods, and provide independent checks to existing tensions.

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Towards a Model-Independent Measurement of the Halo Mass Function with Observables

In the CDM paradigm, the halo mass function is a sensitive probe of the cosmic structure. In observations, halo mass is typically estimated from its relation with other observables. The resulting halo mass function is subject to systematic bias, such as the Eddington bias, due to the scatter or uncertainty in the observable - mass relation. Exact correction for the bias is not easy, as predictions for the observables are typically model-dependent in simulations. In this paper, we point out an interesting feature in the halo mass function of the concordence $Λ$CDM model: the total halo mass within each evenly-spaced logarithmic mass bin is approximately the same over a large mass range. We show that this property allows us to construct an almost bias-free halo mass function using only an observable (as a halo mass estimator) and stacked weak lensing measurements as long as the scatter between the true halo mass and the observable-inferred mass has a stable form in logarithmic units. The method is not sensitive to the form of the mass-observable relation. We test the idea using cosmological simulations, and show that the method performs very well for realistic observables.

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Constraining Dark Energy With Stacked Concave Lenses

Low density regions are less affected by the nonlinear structure formation and baryonic physics. They are ideal places for probing the nature of dark energy, a possible explanation for the cosmic acceleration. Unlike void lensing, which requires identifications of individual voids, we study the stacked lensing signals around the low-density-positions (LDP), defined as places that are devoid of foreground bright galaxies in projection. The method allows a direct comparison with numerical results by drawing correspondence between the bright galaxies with halos. It leads to lensing signals that are significant enough for differentiating several dark energy models. In this work, we use the CFHTLenS catalogue to define LDPs, as well as measuring their background lensing signals. We consider several different definitions of the foreground bright galaxies (redshift range \& magnitude cut). Regarding the cosmological model, we run six simulations: the first set of simulations have the same initial conditions, with $\rm{w_{de}=-1,-0.5,-0.8,-1.2}$; the second set of simulations include a slightly different $Λ$CDM model and a w(z) model from \cite{2017NatAs...1..627Z}. The lensing results indicate that the models with $\rm{w_{de}=-0.5,-0.8}$ are not favored, and the other four models all achieve comparable agreement with the data.

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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.

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Removing the Impact of Correlated PSF Uncertainties in Weak Lensing

Accurate reconstruction of the spatial distributions of the Point Spread Function (PSF) is crucial for high precision cosmic shear measurements. Nevertheless, current methods are not good at recovering the PSF fluctuations of high spatial frequencies. In general, the residual PSF fluctuations are spatially correlated, therefore can significantly contaminate the correlation functions of the weak lensing signals. We propose a method to correct for this contamination statistically, without any assumptions on the PSF and galaxy morphologies or their spatial distribution. We demonstrate our idea with the data from the W2 field of CFHTLenS.

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An accurate centroid algorithm for PSF reconstruction

In this work, we present a novel centroiding method based on Fourier space Phase Fitting(FPF) for Point Spread Function(PSF) reconstruction. We generate two sets of simulations to test our method. The first set is generated by GalSim with elliptical Moffat profile and strong anisotropy which shifts the center of the PSF. The second set of simulation is drawn from CFHT i band stellar imaging data. We find non-negligible anisotropy from CFHT stellar images, which leads to $\sim$0.08 scatter in unit of pixels using polynomial fitting method Vakili and Hogg (2016). And we apply FPF method to estimate the centroid in real space, this scatter reduces to $\sim$0.04 in SNR=200 CFHT like sample. In low SNR (50 and 100) CFHT like samples, the background noise dominates the shifting of the centroid, therefore the scatter estimated from different methods are similar. We compare polynomial fitting and FPF using GalSim simulation with optical anisotropy. We find that in all SNR$\sim$50, 100 and 200) samples, FPF performs better than polynomial fitting by a factor of $\sim$3. In general, we suggest that in real observations there are anisotropy which shift the centroid, and FPF method is a better way to accurately locate it.

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Testing PSF Interpolation In Weak Lensing With Real Data

Reconstruction of the point spread function (PSF) is a critical process in weak lensing measurement. We develop a real-data based and galaxy-oriented pipeline to compare the performances of various PSF reconstruction schemes. Making use of a large amount of the CFHTLenS data, the performances of three classes of interpolating schemes - polynomial, Kriging, and Shepard - are evaluated. We find that polynomial interpolations with optimal orders and domains perform the best. We quantify the effect of the residual PSF reconstruction error on shear recovery in terms of the multiplicative and additive biases, and their spatial correlations using the shear measurement method of Zhang et al. (2015). We find that the impact of PSF reconstruction uncertainty on the shear-shear correlation can be significantly reduced by cross correlating the shear estimators from different exposures. It takes only 0.2 stars (SNR > 100) per square arcmin on each exposure to reach the best performance of PSF interpolation, a requirement that is generally satisfied in the CFHTlenS data.

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