Zekang Zhang
Zekang Zhang - Cosmology & AI
PhD student at the University Observatory Munich, LMU, in the Astrophysics, Cosmology and Artificial Intelligence group with Daniel Gruen. I work on photometric galaxy surveys — galaxy clustering, weak lensing, and the systematics that limit how precisely they can be read together.
Research
I work on photometric galaxy surveys: galaxy images, colours, positions, redshift distributions, selections, weak lensing, shear calibration, galaxy clustering, statistics, machine learning, and analytical modeling for cosmology.
- Image simulation and forward modeling: blending, PSF, noise, detection, photometry, and selection effects.
- Redshift calibration: photometric redshift distributions, n(z), SOM-based colour-redshift calibration, and 4C3R2.
- Shear estimation: weak-lensing shear response, PSF systematics, FORKLENS, and deep learning.
- Statistics and inference: two-point statistics, selection functions, uncertainty budgets, and clustering bias.
Selected Publications
- Emulating redshift mixing due to blending in weak gravitational lensing
- FORKLENS: Accurate weak-lensing shear measurement with deep learning
- HybPSF: Hybrid PSF reconstruction for the observed JWST NIRCam image
- Impact of the turnover in the high-z galaxy luminosity function on the 21-cm signal during Cosmic Dawn and Epoch of Reionization
More: NASA ADS, Google Scholar, GitHub.
Contact
Email: zekang.zhang@physik.lmu.de
Address: University Observatory Munich (USM), Scheinerstr. 1, 81679 Munich. Room 222.