I am Zheng Che, an M.Sc. student in chemical physics at the University of Science and Technology of China.
Note: I am open to PhD opportunities for Fall 2027. If our research interests align, feel free to reach out at wsmxcz@gmail.com
Research Interests#
My research aims to develop simple concepts, unified representations, rigorous theory, and efficient algorithms for quantum chemistry and quantum many-body systems.
- Parameterized wavefunctions: Tensor networks, neural quantum states, and quantum circuits, with a focus on representational efficiency, variational geometry, and symmetry.
- Stochastic theory: Stochastic and semi-stochastic methods that exploit sparsity, hierarchy, and importance structure in quantum many-body problems.
- Hamiltonian representations: Real-space discretization, adaptive basis construction, and compact operator representations for electronic systems.
- Quantum algorithms: Many-body quantum algorithms and coherent dynamics, including the conditions required for a practical quantum advantage.
- Chemical theory: Abstract and effective models grounded in electronic structure, designed to yield clear and transferable chemical concepts.
Education#
- University of Science and Technology of China — M.Sc. student in Chemical Physics, 2024–present
- Lanzhou University, Cuiying Honors College — B.Sc. Honors in Chemistry, 2020–2024
Publications#
- Z. Che, “Importance-Reweighted Fock-Space Variational Monte Carlo,” arXiv:2608.22925 (2026). DOI
- Z. Che, “A Deterministic Framework for Neural Network Quantum States in Quantum Chemistry,” Journal of Chemical Theory and Computation (2026). DOI
- J.-F. Wu, L.-Y. Liang, Z. Che, Y.-T. Miao, and L. Chou, “Bimetallic Oxide Catalysts for CO₂ Hydrogenation to Methanol: Recent Advances and Challenges,” Chinese Journal of Catalysis 73, 62–78 (2025). DOI
- P.-Y. Liang et al., “Organocatalytic Synthesis of Chiral Allene Catalyzed by Chiral Phosphoric Acid via Asymmetric 1,8-Addition of Indole Imine Methide,” Molecular Catalysis 530, 112648 (2022). DOI
Open Source#
FockVMC is a research codebase for Fock-space variational Monte Carlo. (Now in active development)