Yuanyuan Zhang's personal site

Parallel Computing and Software Development

I have a lot of enthusasim for using high-performance computing methods in my astronomical research analysis. My engagements with wide field imaging processing often involves using parallel computing methods on high-performance machines (I will try to parallelize anything if there is a chance to do so :-). Most recently, as part of my low-surface brightness imaging studies, I have ve been running a lot of image processing code on the Open Science Grid (OSG), in a "scavenging" mode utilizing thousands of parallel processes on spare machines available through the OSG network. At times I have dealt with issues such as generating too much data, or that I have reached the database's parallel connection capabilities, but it has been a very exicting and rewarding experience.

Efficient computing algorithm for astronomy and cosmology is another topic I am deeply curious about. I've undertaken a couple of software development efforts, including working on image processing methods, and developing efficient cluster cosmology analysis pipelines. Efficiency, parallelizability, and reproducibility are my top concerns in these efforts. My most recent news on this front is that my collaborators and I have received a ~ $498,000 grant from Fermilab to integrate simulation-based inference and machine learning methods into cosmology analysis software. Super excited to start on this new project and the journey of being a co-PI!

Related Published papers:

Dark Energy Survey Year 3 Results: Measuring the Survey Transfer Function with Balrog, Everett, S. and 99 colleagues including Y.Zhang, submitted to ApJs, arXiv:2012.12825

Crowded Cluster Cores: Algorithms for Deblending in Dark Energy Survey Images, Y. Zhang, T. A. McKay, E. Bertin et al., 2015, PASP, 127, 1183, arXiv:1409.2885.

Dark Energy

I am invoved in dark energy studies based on the galaxy cluster abundance methods. I was an analysis lead for the Dark Energy Survey's cluster cosmology team for two years, and currently a co-convener of the LSST Dark Energy Science Collaboration's (LSST-DESC) cluster working group.

Galaxy clusters have been studied for cosmological constraints for decades, but ongoing and upcoming large scale structure surveys like DES and LSST can significantly improve the resulting cosmological constraints. I contribute to this topic through my expertise on (1) quantifying cluster cosmology systematic effects, and (2) developing analysis pipelines.

The right side figure shows the cosmological constraints from DES Year 1 data which I contributed to.

Related Published papers:

Dark Energy Survey Year 1 Results: Cosmological constraints from cluster abundances and weak lensing,
(Alphabetical author list) T. M.C., Abbott, and 136 colleagues including Y. Zhang, 2020, Physical Review D, 102, 023509, arXiv: 2002.11124

Dark Energy Survey Year 1 Results: Calibration of Cluster Mis-centering in the redMaPPer Cat- alogs,
Y. Zhang et al. 2019, MNRAS, 487, 2578, arXiv: 1901.07119

Orientation Bias of Optically Selected Galaxy Clusters and its Impact on Stacked Weak Lensing Analyses, J. P. Dietrich, Y. Zhang, J. Song et al., 2014, MNRAS, 443, 1713, arXiv:1405.2923.

Methods for cluster cosmology and application to the SDSS in preparation for DES Year 1 release, M. Costanzi, E. Rozo, M. Simet, Y. Zhang, et al. 2019, MNRAS, 488, 4779, arXiv: 1810.09456

Low Surfarce Brightness (LSB) Measurements from Wide-Field Survey Images

Making LSB measurements is my most recent focus in the extragalactic galaxy studies front. I worked on using Dark Energy Survey (DES) images to tease out the LSB signals in galaxy clusters and around bright galaxies. I also use the cosmological capabilities of DES, incuding weak lensign shear measurements, high quality galaxy and galaxy cluster catalogs, and galaxy cluster mass indicators, to study the connection between LSB measurements and the underlining dark matter halo properties . There are many challenges in LSB measurements due to various astrophysical and detector effects, which my collaborators and I try to solve by leveraging the wide sky coverage of DES. The work can get a bit tedious (at one point we spotted an astroid while scanning a few thousdands of images to figure out possible causes of contaminations), but exiciting meanwhile, especially after our measurement methods passed checks. The efforts also brought me opportuniuties to work with a few junior collaborators including undergrads, graduate students, and postdocs.

Related Published papers:

(Mentored student publication)Is diffuse intracluster light a good tracer of the galaxy cluster matter distribution?,
H. Sampaio-Santos, Y. Zhang, et al. 2021, MNRAS,501, 1, arXiv: 2005.12275

(Mentored student publication)The Diffuse Light Envelope of Luminous Red Galaxies, Y. Leung, Y. Zhang, et al. 2020, Research Note of AAS, arXiv: 2005.13467

Dark Energy Survey Year 1 results: Detection of Intra-cluster Light at Redshift ∼ 0.25, Y. Zhang, B. Yanny, et al., 2019, ApJ, 874, 165, arXiv: 1812.04004

Dark Energy Survey Year 1 Results: The effect of intra-cluster light on photometric redshifts for weak gravitational lensing,
D. Gruen, Y. Zhang, et al. 2019, MNRAS, 488, 4389, arXiv:1809.04599

Cluster Galaxy Studies Using Cosmic Survey Data

I have developed an interest in cluster galaxy evolution since the years as a graduate student. My interest is focused on studying the central galaxies of galaxy clusters, and in particular, their evolution and relation to the host dark matter halo properties. I aim to harvest the data power of cosmic surveys to construct the statistical evolution history of cluster galaxies. Along the way, I've also made related findings such as a few ultra-compact dwarf and compact elliptical galaxies in intermediate redshift galaxy clusters using archival data from the Hubble Space Telescope (shown in the figure below).

Related Published papers:

Galaxies in X-ray Selected Clusters and Groups in Dark Energy Survey Data II: Hierarchical Bayesian Modeling of Red-Sequence Galaxy Luminosity Function, Y. Zhang, C. Miller, et al. 2019, MNRAS,488, 1, arXiv: 1710.05908

M32 Analogs? A Population of Massive Ultra-compact Dwarf and Compact Elliptical Galaxies in Intermediate-redshift Clusters,
Y. Zhang and E. F. Bell, 2017, ApJ, 835, L2, arXiv: 1610.06174

Galaxies in X-ray Selected Clusters and Groups in Dark Energy Survey Data I: Stellar Mass Growth of Bright Central Galaxies Since z ∼ 1.2,
Y. Zhang, C. Miller, T. A. McKay et al., 2016, 816, 98, ApJ, arXiv:1504.02983

Studying Inter-Cluster Galaxy Filaments Through Stacking GMBCG Galaxy Cluster Pairs, Y. Zhang , J. P. Dietrich, T. A. McKay, et al., 2013, ApJ, 773, 115, arXiv:1304.6696.