arXiv subjects

Yu Yu

Publications and source records attributed to Yu Yu.

At least 109 records · Page 6Linked to original sources

arXiv2019

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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arXiv2018

Recovering lost 21 cm radial modes via cosmic tidal reconstruction

21 cm intensity mapping has emerged as a promising technique to map the large-scale structure of the Universe, at redshifts $z$ from 1 to 10. Unfortunately, many of the key cross-correlations with the cosmic microwave background and photo-$z$ galaxies have been thought to be impossible due to the foreground contamination for radial modes with small wave numbers. In this paper, we apply tidal reconstruction to the simulated 21 cm fields and recover the lost large-scale radial modes successfully. We estimate the detectability of the cross-correlation signals and find they can be detected at high significance with current 21 cm experiments. The tidal field reconstruction method opens up a new set of possibilities to probe the Universe and is extremely valuable not only for 21 cm surveys but also for cosmic microwave background and photometric-redshift observations.

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arXiv2018

Verifications of scaling relations useful for the intrinsic alignment self-calibration

The galaxy intrinsic alignment (IA) is a major challenge of weak lensing cosmology. To alleviate this problem, Zhang (2010, MNRAS, 406, L95) proposed a self-calibration method, independent of IA modeling. This proposal relies on several scaling relations between two-point clustering of IA and matter/galaxy fields, which were previously only tested with analytical IA models. In this paper, these relations are tested comprehensively with an $N$-body simulation of $3072^3$ simulation particles and boxsize 600 $h^{-1} \, \mathrm{Mpc}$. They are verified at the accuracy level of $\mathcal{O}(1)\%$ over angular scales and source redshifts of interest. We further confirm that these scaling relations are generic, insensitive to halo mass, weighting in defining halo ellipticities, photo-$z$ error, and misalignment between galaxy ellipticities and halo ellipticities. We also present and verify three new scaling relations on the B-mode IA. These results consolidate and complete the theory side of the proposed self-calibration technique.

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arXiv2018

Accurate determination of halo velocity bias in simulations and its cosmological implications

A long-standing issue in peculiar velocity cosmology is whether the halo/galaxy velocity bias $b_v=1$ at large scale. The resolution of this important issue must resort to high precision cosmological simulations. However, this is hampered by another long-standing `sampling artifact' problem in volume weighted velocity measurement. We circumvent this problem with a hybrid approach. We first measure statistics free of sampling artifact, then link them to volume weighted statistics in theory, finally solve for the velocity bias. $b_v$ determined by our method is not only free of sampling artifact, but also free of cosmic variance. We apply this method to a $Λ$CDM N-body simulation of $3072^3$ particles and $1200 Mpc/{\rm h}$ box size. For the first time, we determine the halo velocity bias to $0.1\%$-$1\%$ accuracy. Our major findings are as follows: (1) $b_v\neq 1$ at $k>0.1 h/{\rm Mpc}$. The deviation from unity ($|b_v-1|$) increases with $k$. Depending on halo mass and redshift, it may reach $\mathcal{O}(0.01)$ at $k=0.2 h/{\rm Mpc}$ and $\mathcal{O}(0.05)$ at $k\sim 0.3 h/{\rm Mpc}$. The discovered $b_v\neq 1$ has statistically significant impact on structure growth rate measurement by spectroscopic redshift surveys, including DESI, Euclid and SKA. (2) Both the sign and the amplitude of $b_v-1$ depend on mass and redshift. These results disagree with the peak model prediction in that $b_v$ has much weaker deviation from unity, varies with redshift, and can be bigger than unity. (3) Most of the mass and redshift dependences can be compressed into a single dependence on the halo density bias. Based on this finding, we provide an approximate two-parameter fitting formula.

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arXiv2018

Weak lensing power spectrum reconstruction by counting galaxies.-- II: Improving the ABS method with the shift parameter

In paper I of this series (Yang et al. 2017, ApJ), we proposed an analytical method of blind separation ({\bf ABS}) to extract the cosmic magnification signal in galaxy number distribution and reconstruct the weak lensing power spectrum. Here we report a new version of the ABS method, with significantly improved performance. This version is characterized by a shift parameter $\mathcal{S}$, with the special case of $\mathcal{S}=0$ corresponding to the original ABS method. We have tested this new version, compared to the previous one, and confirmed its supreme performance in all investigated situations. Therefore it supersedes the previous version. The proof of concept studies presented in this paper demonstrate that it may enable surveys such as LSST and SKA to reconstruct the lensing power spectrum at $z\simeq 1$ with $1\%$ accuracy. We will test with more realistic simulations to verify its applicability in real data.

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arXiv2018

An Investigation of intra-cluster light evolution using cosmological hydro-dynamical simulations

The intra-cluster light (ICL) in observations is usually identified through the surface brightness limit method. In this paper, for the first time we produce the mock images of galaxy groups and clusters using a cosmological hydro- dynamical simulation, to investigate the ICL fraction and focus on its dependence on observational parameters, e.g., the surface brightness limit (SBL), the effects of cosmological redshift dimming, point spread function and CCD pixel size. Detailed analyses suggest that the width of point spread function has a significant effect on the measured ICL fraction, while the relatively small pixel size shows almost no influence. It is found that the measured ICL fraction depends strongly on the SBL. At a fixed SBL and redshift, the measured ICL fraction decreases with increasing halo mass, while with a much faint SBL, it does not depend on halo mass at low redshifts. In our work, the measured ICL fraction shows clear dependence on the cosmological redshift dimming effect. It is found that there are more mass locked in ICL component than light, suggesting that the use of a constant mass-to-light ratio at high surface brightness levels will lead to an underestimate of ICL mass. Furthermore, it is found that the radial profile of ICL shows a characteristic radius which is almost independent of halo mass. The current measurement of ICL from observations has a large dispersion due to different methods, and we emphasize the importance of using the same definition when observational results are compared with the theoretical predictions.

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arXiv2018

Nonlinear reconstruction of redshift space distortions

We apply nonlinear reconstruction to the dark matter density field in redshift space and solve for the nonlinear mapping from the initial Lagrangian position to the final redshift space position. The reconstructed anisotropic field inferred from the nonlinear displacement correlates with the linear initial conditions to much smaller scales than the redshift space density field. The number of linear modes in the density field is improved by a factor of 30-40 after reconstruction. We thus expect this reconstruction approach to substantially expand the cosmological information including baryon acoustic oscillations and redshift space distortions for dense low-redshift large scale structure surveys including for example SDSS main sample, DESI BGS, and 21 cm intensity mapping surveys.

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arXiv2017

Cosmic tidal reconstruction

The gravitational coupling of a long-wavelength tidal field with small-scale density fluctuations leads to anisotropic distortions of the locally measured small-scale matter correlation function. Since the local correlation function is known to be statistically isotropic in the absence of such tidal interactions, the tidal distortions can be used to reconstruct the long-wavelength tidal field and large-scale density field in analogy with the cosmic microwave background lensing reconstruction. In this paper we present the theoretical framework of cosmic tidal reconstruction and test the reconstruction in numerical simulations. We find that the density field on large scales can be reconstructed with good accuracy and the cross-correlation coefficient between the reconstructed density field and the original density field is greater than 0.9 on large scales $(k\lesssim0.1\ h/\mathrm{Mpc})$, with the filter scale $\sim1.25\ \mathrm{Mpc}/h$. This is useful in the 21cm intensity mapping survey, where the long-wavelength radial modes are lost due to a foreground subtraction process.

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arXiv2017

Nonlinear reconstruction

We present a direct approach to nonparametrically reconstruct the linear density field from an observed nonlinear map. We solve for the unique displacement potential consistent with the nonlinear density and positive definite coordinate transformation using a multigrid algorithm. We show that we recover the linear initial conditions up to the nonlinear scale ($r_{δ_rδ_L}>0.5$ for $k\lesssim1\ h/\mathrm{Mpc}$) with minimal computational cost. This reconstruction approach generalizes the linear displacement theory to fully nonlinear fields, potentially substantially expanding the baryon acoustic oscillations and redshift space distortions information content of dense large scale structure surveys, including for example SDSS main sample and 21cm intensity mapping initiatives.

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arXiv2017

Non-negative matrix factorization for self-calibration of photometric redshift scatter in weak lensing surveys

Photo-z error is one of the major sources of systematics degrading the accuracy of weak lensing cosmological inferences. Zhang et al. (2010) proposed a self-calibration method combining galaxy-galaxy correlations and galaxy-shear correlations between different photo-z bins. Fisher matrix analysis shows that it can determine the rate of photo-z outliers at a level of 0.01-1% merely using photometric data and do not rely on any prior knowledge. In this paper, we develop a new algorithm to implement this method by solving a constrained nonlinear optimization problem arising in the self-calibration process. Based on the techniques of fixed-point iteration and non-negative matrix factorization, the proposed algorithm can efficiently and robustly reconstruct the scattering probabilities between the true-z and photo-z bins. The algorithm has been tested extensively by applying it to mock data from simulated stage IV weak lensing projects. We find that the algorithm provides a successful recovery of the scatter rates at the level of 0.01-1%, and the true mean redshifts of photo-z bins at the level of 0.001, which may satisfy the requirements in future lensing surveys.

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arXiv2017

Halo nonlinear reconstruction

We apply the nonlinear reconstruction method to simulated halo fields. For halo number density $2.77\times 10^{-2}$ $(h^{-1} {\rm Mpc})^{-3}$ at $z=0$, corresponding to the SDSS main sample density, we find the scale where the noise saturates the linear signal is improved to $k\gtrsim0.36\ h {\rm Mpc}^{-1}$, a factor of $2.29$ improvement in scale, or $12$ in number of linear modes. The improvement is less for higher redshift or lower halo density. We expect this to substantially improve the BAO accuracy of dense, low redshift surveys, including the SDSS main sample, 6dFGS and 21cm intensity mapping initiatives.

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arXiv2017

Weak lensing power spectrum reconstruction by counting galaxies.-- I: the ABS method

We propose an Analytical method of Blind Separation (ABS) of cosmic magnification from the intrinsic fluctuations of galaxy number density in the observed galaxy number density distribution. The ABS method utilizes the different dependences of the signal (cosmic magnification) and contamination (galaxy intrinsic clustering) on galaxy flux, to separate the two. It works directly on the measured cross galaxy angular power spectra between different flux bins. It determines/reconstructs the lensing power spectrum analytically, without assumptions of galaxy intrinsic clustering and cosmology. It is unbiased in the limit of infinite number of galaxies. In reality the lensing reconstruction accuracy depends on survey configurations, galaxy biases, and other complexities, due to finite number of galaxies and the resulting shot noise fluctuations in the cross galaxy power spectra. We estimate its performance (systematic and statistical errors) in various cases. We find that, stage IV dark energy surveys such as SKA and LSST are capable of reconstructing the lensing power spectrum at $z\simeq 1$ and $\ell\la 5000$ accurately. This lensing reconstruction only requires counting galaxies, and is therefore highly complementary to the cosmic shear measurement by the same surveys.

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arXiv2017

Isobaric Reconstruction of the Baryonic Acoustic Oscillation

In this paper, we report a significant recovery of the linear baryonic acoustic oscillation (BAO) signature by applying the isobaric reconstruction algorithm to the non-linear matter density field. Assuming only the longitudinal component of the displacement being cosmologically relevant, this algorithm iteratively solves the coordinate transform between the Lagrangian and Eulerian frames without requiring any specific knowledge of the dynamics. For dark matter field, it produces the non-linear displacement potential with very high fidelity. The reconstruction error at the pixel level is within a few percent, and is caused only by the emergence of the transverse component after the shell-crossing. As it circumvents the strongest non-linearity of the density evolution, the reconstructed field is well-described by linear theory and immune from the bulk-flow smearing of the BAO signature. Therefore this algorithm could significantly improve the measurement accuracy of the sound horizon scale. For a perfect large-scale structure survey at redshift zero without Poisson or instrumental noise, the fractional error is reduced by a factor of 2.7, very close to the ideal limit with linear power spectrum and Gaussian covariance matrix.

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arXiv2017

Kriging interpolating cosmic velocity field. II. Taking anistropies and multistreaming into account

Measuring the volume-weighted peculiar velocity statistics from inhomogeneously and sparsely distributed galaxies/halos, by existing velocity assignment methods, suffers from a significant sampling artifact. As an alternative, the Kriging interpolation based on Gaussian processes was introduced and evaluated [Y. Yu, J. Zhang, Y. Jing, and P. Zhang, Phys. Rev. D 92, 083527 (2015)]. Unfortunately, the most straightforward application of Kriging does not perform better than the existing methods in the literature. In this work, we investigate two physically motivated extensions. The first takes into account of the anisotropic velocity correlations. The second introduces the nugget effect, on account of multi-streaming of the velocity field. We find that the performance is indeed improved. For sparsely sampled data [$n_P\lesssim 6\times 10^{-3}(h^{-1} {\rm Mpc})^{-3}$] where the sampling artifact is the most severe, the improvement is significant and is two-fold: 1) The scale of reliable measurement of the velocity power spectrum is extended by a factor $\sim 1.6$, and 2) the dependence on the velocity correlation prior is weakened by a factor of $\sim 2$. We conclude that such extensions are desirable for accurate velocity assignment by Kriging.

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arXiv2016

Fast generation of weak lensing maps by the inverse-Gaussianization method

To take full advantage of the unprecedented power of upcoming weak lensing surveys, understanding the noise, such as cosmic variance and geometry/mask effects, is as important as understanding the signal itself. Accurately quantifying the noise requires a large number of statistically independent mocks for a variety of cosmologies. This is impractical for weak lensing simulations, which are costly for simultaneous requirements of large box size (to cover a significant fraction of the past light cone) and high resolution (to robustly probe the small scale where most lensing signal resides). Therefore fast mock generation methods are desired and are under intensive investigation. We propose a new fast weak lensing map generation method, named the inverse-Gaussianization method, based on the finding that a lensing convergence field can be Gaussianized to excellent accuracy by a local transformation [Yu et al, Phys. Rev. D 84, 023523 (2011)]. Given a simulation, it enables us to produce as many as infinite statistically independent lensing maps as fast as producing the simulation initial conditions. The proposed method is tested against simulations for each tomography bin centered at lens redshift $z \sim 0.5$, 1, and 2, with various statistics. We find that the lensing maps generated by our method have reasonably accurate power spectra, bispectra, and power spectrum covariance matrix. Therefore, it will be useful for weak lensing surveys to generate realistic mocks. As an example of application, we measure the probability distribution function of the lensing power spectrum, from 16384 lensing maps produced by the inverse-Gaussianization method.

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arXiv2016

Measurement of Neutrino Masses from Relative Velocities

We present a new technique to measure neutrino masses using their flow field relative to dark matter. Present day streaming motions of neutrinos relative to dark matter and baryons are several hundred km/s, comparable with their thermal velocity dispersion. This results in a unique dipole anisotropic distortion of the matter-neutrino cross power spectrum, which is observable through the dipole distortion in the cross correlation of different galaxy populations. Such a dipole vanishes if not for this relative velocity and so it is a clean signature for neutrino mass. We estimate the size of this effect and find that current and future galaxy surveys may be sensitive to these signature distortions.

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arXiv2015

Kriging Interpolating Cosmic Velocity Field

[abridged] Volume-weighted statistics of large scale peculiar velocity is preferred by peculiar velocity cosmology, since it is free of uncertainties of galaxy density bias entangled in mass-weighted statistics. However, measuring the volume-weighted velocity statistics from galaxy (halo/simulation particle) velocity data is challenging. For the first time, we apply the Kriging interpolation to obtain the volume-weighted velocity field. Kriging is a minimum variance estimator. It predicts the most likely velocity for each place based on the velocity at other places. We test the performance of Kriging quantified by the E-mode velocity power spectrum from simulations. Dependences on the variogram prior used in Kriging, the number $n_k$ of the nearby particles to interpolate and the density $n_P$ of the observed sample are investigated. First, we find that Kriging induces $1\%$ and $3\%$ systematics at $k\sim 0.1h{\rm Mpc}^{-1}$ when $n_P\sim 6\times 10^{-2} ({\rm Mpc}/h)^{-3}$ and $n_P\sim 6\times 10^{-3} ({\rm Mpc}/h)^{-3}$, respectively. The deviation increases for decreasing $n_P$ and increasing $k$. When $n_P\lesssim 6\times 10^{-4} ({\rm Mpc}/h)^{-3}$, a smoothing effect dominates small scales, causing significant underestimation of the velocity power spectrum. Second, increasing $n_k$ helps to recover small scale power. However, for $n_P\lesssim 6\times 10^{-4} ({\rm Mpc}/h)^{-3}$ cases, the recovery is limited. Finally, Kriging is more sensitive to the variogram prior for lower sample density. The most straightforward application of Kriging on the cosmic velocity field does not show obvious advantages over the nearest-particle method (Zheng et al. 2013) and could not be directly applied to cosmology so far. However, whether potential improvements may be achieved by more delicate versions of Kriging is worth further investigation.

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arXiv2015

The source-lens clustering effect in the context of lensing tomography and its self-calibration

Cosmic shear can only be measured where there are galaxies. This source-lens clustering (SLC) effect has two sources, intrinsic source clustering and cosmic magnification (magnification/size bias). Lensing tomography can suppress the former. However, this reduction is limited by the existence of photo-z error and nonzero redshift bin width. Furthermore, SLC induced by cosmic magnification cannot be reduced by lensing tomography. Through N-body simulations, we quantify the impact of SLC on the lensing power spectrum in the context of lensing tomography. We consider both the standard estimator and the pixel-based estimator. We find that none of them can satisfactorily handle both sources of SLC. (1) For the standard estimator, SLC induced by both sources can bias the lensing power spectrum by O(1)-O(10)%. Intrinsic source clustering also increases statistical uncertainties in the measured lensing power spectrum. However, the standard estimator suppresses intrinsic source clustering in the cross-spectrum. (2) In contrast, the pixel-based estimator suppresses SLC through cosmic magnification. However, it fails to suppress SLC through intrinsic source clustering and the measured lensing power spectrum can be biased low by O(1)-O(10)%. In short, for typical photo-z errors (sigma_z/(1+z)=0.05) and photo-z bin sizes (Delta_z^P=0.2), SLC alters the lensing E-mode power spectrum by 1-10%, with ell~10^3$ and z_s~1 being of particular interest to weak lensing cosmology. Therefore the SLC is a severe systematic for cosmology in Stage-IV lensing surveys. We present useful scaling relations to self-calibrate the SLC effect.

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