research overview
- Achieving quantum computational advantage is the main motivation of building quantum computing. Besides the development of experiments, theoretical studies are also vital to achieve this goal. There are two types of theoretical researches along: 1. finding the useful applications using quantum algorithms which is hard to achieve by classical computers; 2. designing better quantum error correction codes. Along type 1, I focus on quantum machine learning by combining ideas and techniques from statistical physics, quantum foundation and computational complexity theory, such as path integral quantization, quantum contextuality and polynomial hierarchy. I also study variational method for quantum many-body problems based on quantum circuits. Along type 2, I'm working on designing quantum error correction decoder and studying how to improve code performance based statistical mechanical models and algorithms, and tensor network methods. Besides the above research, I'm also studying how to combine 1 and 2 together, namely integrating quantum algorithm design and error correction together. Meanwhile, I'm also working on quantum-inspired algorithms, for example, new exactly solvable models and ansatz inspired from the study of quantum circuits and machine learning models inspired from the principle of quantum mechanics.
