In the noisy intermediate-scale quantum era (NISQ), we are likely to achieve practical quantum advantage using near-term programmable quantum hardware. We focus on the variational quantum algorithm paradigm and make progress in circuit structure design automation and circuit parameter optimization. In this talk, I will discuss how to design quantum circuit structures by various quantum architecture search methods and how to accelerate variational quantum algorithms training by novel optimization strategies. Besides, I will also introduce the high-performance quantum software framework for the NISQ era – TensorCircuit, which supports these research works by efficient numerical simulation and powerful quantum hardware connection. These works together pave the way to better understanding and investigating the power of NISQ devices.
Shi-Xin Zhang is currently a senior research scientist at Tencent Quantum Lab. He obtained his PhD in physics from Institute for Advanced Study, Tsinghua University, in 2021, supervised by Prof. Hong Yao. He graduated with an outstanding PhD and outstanding thesis award at Tsinghua University. Before this, he obtained his bachelor’s degree in physics from the Department of Physics at Tsinghua University in 2016. His main research interests include quantum algorithm design, quantum non-equilibrium physics, quantum simulation, quantum software, and machine learning application in quantum physics.