I work on Theoretical Astrophysics and Cosmology with close ties to data, especially astronomical surveys like SDSS, DESI, and LSST. I am particularly interested in learning galaxy formation physics using the spatial clusetering and the weak gravitational lensing of galaxies, constraining theories of cosmic acceleartion using galaxy kinematics and galaxy clusters, and measuring Supermassive Blackhole masses from the flickering of gas clouds above their accretion disks.
The following highlights my most recent research either in figures and/or YouTube videos (click icons below). You can also click ADS for my full publication list.


Galaxy Infall Kinematics as a Test of Modified Gravity

Zu, Y., Weinberg, D. H., Jennings, E., Li, B., & Wyman, M. 2014, MNRAS, 445, 1885

Infrared modifications of General Relativity (GR) can be revealed by comparing the mass of galaxy clusters estimated from weak lensing to that from infall kinematics. We measure the 2D galaxy velocity distribution in the cluster infall region by applying the galaxy infall kinematics (GIK) model developed by Zu and Weinberg (2013) to two suites of f(R) and Galileon modified gravity simulations.

Despite having distinct screening mechanisms, the f(R) and Galileon clusters exhibit very similar deviations in their GIK profiles from GR (Figure on the left). In combination with the stacked weak lensing measurements, this will provide powerful diagnostics of modified gravity theories and the origin of cosmic acceleration.

[on astro-ph][on ADS] [back to Top]

Redshift-Space Cluster-Galaxy Cross-Correlation: I. Modeling Galaxy Infall onto Millennium Simulation Clusters and SDSS Groups

Zu, Y., & Weinberg D. H., 2013, MNRAS, 431, 3319

We develop and test a method to recover galaxy infall kinematics (GIK) from measurements of the redshift-space cluster-galaxy cross-correlation function xi_cg, by calibrating an analytic model of the galaxy kinematic profiles comprised of a virialized component and an infall component. We show that convolving the real-space cross-correlation function with this velocity distribution accurately predicts the redshift-space xi_cg, and that measurements of xi_cg can be inverted to provide diagnostics of cluster mass profiles.

As a proof of concept we measure xi_cg for rich galaxy groups in the Sloan Digital Sky Survey and recover GIK profiles for groups in bins of central galaxy stellar mass. The figure on the left compares the best-fit (dashed contours) to the measurement of xi_cg (color contours) for one of the bins.

[on astro-ph] [on ADS] [back to Top]

Cosmological Constraints from the Large Scale Weak Lensing of SDSS MaxBCG Clusters

Zu, Y., Weinberg D. H., Rozo, Eduardo, Sheldon, E. S., Tinker, J. L., Becker, M. R., 2014, MNRAS, 439, 1628

We derive constraints on the matter density Omega_m and the amplitude of matter clustering sigma_8 from measurements of large scale weak lensing by clusters in the SDSS MaxBCG catalog. The weak lensing signal is proportional to the product of Omega_m and the cluster-mass correlation function xi_cm, breaking the degeneracies between cosmological and nuisance parameters.

We find sigma_8(Omega_m/0.325)^0.501=0.828 +/- 0.049 (beige contours) and the constraint is consistent with and orthogonal to the one inferred from WMAP CMB data (red contours), reflecting agreement with the structure growth predicted by GR for an LCDM cosmological model. A joint constraint assuming LCDM yields Omega_m=0.298 +/- 0.020 and sigma_8=0.831 +/- 0.020 (blue contours).

[on astro-ph] [on ADS] [back to Top]

Galaxy Formation and Galaxy-Dark Matter Connection

On the Level of Cluster Assembly Bias in SDSS

Zu, Y., Mandelbaum, R., Simet, M., Rozo, E., & Rykoff, E.S. 2017, MNRAS, 551, 560

Recently, several studies discovered a strong discrepancy between the clustering biases of two cluster subsamples at the same halo mass, split by their concentration. After a careful examination of the redMaPPer clusters, we concluded that this strong signal was caused by projection effects in the concentration. After using a better concentration estimator, we found that the level of assembly bias is perfectly consistent with LCDM.

The top panel compares the weak lensing profiles of the two subsample of clusters split by our new concentration. The two subsamples exhibit the same lensing mass and similar clustering biases, whose ratio is consistent with the LCDM expectation (blue line in the bottom).

[on astro-ph] [on ADS] [back to Top]

Mapping stellar content to dark matter haloes II. Halo mass is the main driver of galaxy quenching

Zu, Y., & Mandelbaum. R., 2016, MNRAS, 457:4360–4383

We developed a simple yet comprehensive model to identify the most dominant driver for galaxy quenching, i.e., the relatively abrupt color transformation of galaxies from blue to red, using the spatial clustering and the galaxy-galaxy lensing of the red and blue galaxies in SDSS. We found halo mass to be the main statistical driver for galaxy quenching, rather than galaxy stellar mass or halo formation time.

Our model successfully predicts the strong bimodality in the host halo mass between red and blue central galaxies, shown by the figure on the left.

[on astro-ph] [on ADS] [back to Top]

Mapping stellar content to dark matter haloes using galaxy clustering and galaxy-galaxy lensing in the SDSS DR7

Zu, Y., & Mandelbaum. R., 2015, MNRAS, 454(2), 1161-1191

We developed a noval statistical model, called the iHOD model, to interpret the spatial clustering and the galaxy-galaxy lensing of galaxies observed in SDSS. The model allows us to include more than 80 per cent more galaxies than the traditional methods, and takes into account the stellar mass incompleteness in a self-consistent way, therefore providing one of the most stringent constraint on the stellar mass vs. dark matter mass connections to date.

This figure compares our best-fit predictions for the clustering (top) and lensing (bottom) of two stellar mass samples (left and right) to the measurements. Each mdoel prediction is decomposed into various separate components underneath.

[on astro-ph] [on ADS] [back to Top]


Reverberation Mapping With Photometry

Zu, Y., Kochanek, C. S., Kozlowski, Szymon & Peterson, B. M. 2016, ApJ, 819, 122

Using both simulated and real quasar light curves we explore the feasibility of one and two--band photometric reverberation mapping (RM) and compare to the results for spectroscopic RM. We find that two-band photometric RM can be competitive with spectroscopic RM for strong lines like H\alpha and H\beta, and that the one-band method is feasible, but requires very small photometric uncertainties.

Our approach is directly applicable to the time-domain programs within ongoing and future wide-field imaging surveys. Figure on the left shows the lag detection significance (three colors representing 1, 2, and 3 sigma leves) as a function of line strength for simulated LSST quasar light curves with different variability parameters (marked on top right of each panel).

[on astro-ph] [on ADS] [back to Top]

Is Quasar Optical Variability a Damped Random Walk?

Zu, Y., Kochanek, C. S., Kozlowski, S., Udalski A. 2013, ApJ, 765, 106

Using a sample of OGLE quasar light curves, we consider four modifications to the DRW model by introducing additional parameters into the covariance function to search for deviations from the DRW model on both short and long timescales. We find good agreement with the DRW model on timescales that are well sampled by the data (from a month to a few years), possibly with some intrinsic scatter in the additional parameters, but this conclusion depends on the statistical test employed and is sensitive to whether the estimates of the photometric errors are correct to within ~10%.

Figure on the left illustrates the four different covariance functions we employed in the paper.

[on astro-ph] [on ADS] [back to Top]

An Alternative Approach to Measuring Reverberation Lags in Active Galactic Nuclei

Zu, Y., Kochanek, C. S., & Peterson, B. M. 2010, ApJ, 735, 80

We developed a new reverberation mapping technique to infer lags in the AGN emission lines. Assuming the emission light curves are lagged, smoothed, and scaled versions of the continuum light curve, and the quasar variability can be well described by a damped random walk, we can statistical interpolate the observed light curves and align each other to find the best-fit parameters for the transfer functions of emissoin lines.

Figure on the left compares the new lag estimates from our method JAVELIN (formerly known as SPEAR) and from correlation based methods. We recovered lags from all the measured light curves and removed some old outliers from the lag-luminosity relationship. JAVELIN is an open source software hosted on bitbucket. Please feel free to download or simply check out the documents.

[on astro-ph] [on ADS] [back to Top]