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Chi Zhang 张弛
CV

Astrophysics · Cosmology · Dark Matter

About Me

I am Chi Zhang, a Ph.D. student at the Purple Mountain Observatory (PMO) and the University of Science and Technology of China (USTC), supervised by Prof. Yi-Zhong Fan and Yue-Lin Sming Tsai. I was born and raised in Ulanqab, Inner Mongolia—a small, chill city in northern China. I received my B.S. from the Department of Physics and Technology at Inner Mongolia University. My research focuses on investigating the nature of dark matter using numerical simulations and cosmological large-scale surveys, including weak gravitational lensing and the Lyman-alpha forest.

Dark Matter Cosmology Numerical Simulations Large-scale structure
Portrait of Chi Zhang

Education

Purple Mountain Observatory, Chinese Academy of Science
Ph.D. Student
2021–Present
University of Science and Technology of China
Ph.D. Student
2021–Present
Scuola Internazionale Superiore di Studi Avanzati (SISSA)
Visitor
2024–2025
Inner Mongolia University, Department of Physics and Technology
B.S., Physics
2017–2021

Research

I study how dark-matter microphysics shapes cosmic structure and how these effects can be tested with simulations and cosmological surveys.

Numerical simulations figure
Numerical simulations connect fundamental physics to observable signatures.

Numerical simulations

Cosmological simulations are essential for testing dark matter physics because they are the only practical way to model the nonlinear, multi-physics process of structure formation, while enabling controlled comparisons where only the dark matter model is changed. I analyze state-of-the-art suites such as AIDA-TNG to quantify how alternative dark matter scenarios modify haloes, galaxies, and their surrounding gas and HI. By comparing matched samples across mass and redshift, I try to differentiate the impact of dark matter microphysics from baryonic physics, and quantify where (and on what scales) these models deviate from CDM.

  • Alternative dark-matter models (e.g., self-interactions, warm dark matter)
  • Halo/galaxy environment statistics (visulisations, density profiles, mass function ...)
  • HPC workflows for large simulation datasets

Lyman-alpha Forest

Neutral hydrogen in the IGM absorbs quasar light at the Lyα transition at many redshifts, creating a sequence of absorption features — the Lyman-alpha forest — which is an ideal method to trace the IGM’s density, temperature, and ionization state across cosmic time. Alternative dark-matter physics can alter the distribution and thermodynamic state of the IGM, and these changes can be captured by the Lyman-alpha forest. To quantify this, I use hydrodynamical simulations to model the IGM and then extract mock Lyman-alpha spectra along large ensembles of sightlines through the simulated volume. From these spectra, I measure Lyman-alpha absorption statistics and galaxy–IGM correlations to identify and characterize model-dependent signatures.

  • Mock spectra and line-of-sight pipelines
  • Galaxy–IGM cross-correlations
  • H I distribution and the thermal state of the IGM
Lyman-alpha forest figure
Lyman-alpha absorption encodes the density and temperature structure of the intergalactic medium.
Weak gravitational lensing figure
Weak gravitational lensing probes the projected matter distribution across cosmic time.

Weak Gravitational Lensing

Weak gravitational lensing by large scale structure, namely the cosmic shear, measures the subtle, coherent distortions in galaxy shapes induced by the cumulative matter distribution along the line of sight. Because dark-matter microphysics can change how structure grows and clusters, it can leave characteristic imprints on the shear signal, making cosmic shear a powerful probe of dark-matter models. I then use cosmic-shear data to constrain dark-matter and cosmological parameters via Bayesian inference. To make this feasible with accurate nonlinear predictions, I build simulation-based emulators of the matter power spectrum that enable rapid likelihood evaluations during parameter sampling.

  • Cosmic shear statistics and Bayesian inference
  • Constraints on beyond-CDM dark matter models
  • Simulation emulators for nonlinear structure formation

Contact

Email
chizhanpmo@gmail.com
Address
Purple Mountain Observatory, CAS, No.10 Yuanhua Road, Nanjing, China

Travel & Photography

Apart from my research, I love traveling and exploring different cultures. I also enjoy capturing moments and scenery with my camera—feel free to browse my interactive gallery and experience these memories through my lens.