报告题目：Quantum Computing and Quantum Embedding for Large-scale Electronic Structure problem
At present, Moore's Law is gradually failing, and various new computing architectures are emerging one after another. Quantum computing is likely to be a revolutionary technology in the future and has recently exhibited great potential in predicting chemical properties for various applications in drug discovery, material design, and catalyst optimization. However, quantum computing is in the era of noise intermediate-scale (NISQ), with the number of qubits up to (50-1000), limited coherence time, and gate fidelity. Progress has been made in simulating small molecules with no more than 20 qubits, by using quantum algorithms such as variational quantum eigensolver (VQE). Yet, originating from limitations of the size and the fidelity of near-term quantum hardware, how to accurately simulate large scale molecules and materials remains a challenge. In this talk, we shall present our work towards the larger scale and realistic chemistry simulation. Particularly, combined with quantum embedding theory, density matrix embedding theory as an example, we have greatly enhanced the ability of the current quantum device to simulate complex transition oxygen systems such as NiO which only requires 20 qubits which may require almost 10k qubits and vice versa. Besides, I will also briefly discuss other theoretical research in quantum chemistry simulation, the experimental realization of mainstream quantum systems, and future research trends and difficulties.
Dr. Dingshun Lv , Ph.D, works at ByteDance Research, technical leader of quantum computational chemistry team. I pursue my PhD under the internationally renowned ion trap experiment expert Kihwan Kim and engaged in research in quantum simulation and quantum optics in IIIS, Tsinghua University. So far, I have been working in quantum computing and quantum simulation for more than 10+years. After Ph.D. in 2018, I joined 2012 Lab in Huawei as a quantum computing and quantum algorithm researcher, specializing in and focusing on near-term quantum algorithm and software. While working at Huawei, I mainly focused on quantum many-body simulation (quantum chemistry simulation, Hubbard model, Schwinger model, Heisenberg model simulation) based on variational quantum eigensolver (VQE) and quantum approximation algorithm research (QAOA). In April 2021, I joined ByteDance Research and continued to focus on research in quantum computational chemistry. During these years, more than 10+ papers have been published in internationally renowned journals such as Nature Physics, Nature Communication, PRX, PRL, Chemical Science, npj Computational Materials, JCTC, QST, PRA, etc., with a Hindex of 10, and Google Scholar citation 1,000 times. I have also applied for 10+ patents. My current research interests: Quantum computational chemistry, large-scale quantum chemistry simulation, simulation of strongly correlated systems, etc.