Analog quantum computing maps certain computing tasks into a designed Hamiltonian matrix instead of constructing quantum circuits. The lower resource requirements and higher robustness to imperfections of the quantum system make analog quantum computing a more feasible approach at this stage. Among a variety of physical quantum systems, photons are very suitable for analog quantum computing as its fast speed, a lack of the interaction with the environment, and a high mobility allow for flexible constructions of Hamiltonian structures. Lots of analog quantum algorithms have been raised to speed up various tasks in searching, computing and optimization. Meanwhile, the analog approach is used for quantum simulation, which is to map the Hamiltonian of a quantum system with that of the target system, and produce partial features of the target system. In fact, since Feynman raised the concept of quantum computing, quantum simulation has always been a main part of quantum information science, and has so far been applied to simulating various fields including condensed matter physics, astronomy, chemistry, biology and so on.
In this talk, we shall talk about the progress on a powerful tool for analog quantum computing, the quantum walk, for its first experimental demonstration on large-scale two-dimensional evolution space, its experimental application on fast hitting tasks, and its multi-particle dynamics theoretically studied on the first software of photonic analog quantum computing. We shall also talk about quantum simulation on the integrated photonic chips, including the work of building open quantum systems to simulate energy transport in photosynthesis, constructing periodically-curved arrays to simulate dynamic localization and forming designed structures to simulate targets in a few other subjects. In addition, we shall introduce the work on quantum machine learning, including the crossover in two directions, the quantum-enhanced machine learning techniques and the machine-learning-assisted quantum tasks, and some progresses in other miscellaneous topics related to quantum optics will also be briefly discussed.

Dr. Hao Tang gained a bachelor degree on electronic science and technology in Huangzhong University of Science and Technology in 2010, and a PhD degree on optoelectronic physics in the University of Sheffield in 2014. Whilst in UK, she also took executive program on quantitative finance modelling in London Business School and worked or interned on fixed income products in a few asset management firms. She joined the School of Physics and Astronomy in Shanghai Jiao Tong University as a postdoctoral researcher in mid-2015, and has since then achieved a series of progresses on experimental analog quantum computing and quantum simulation on integrated photonic chips. Especially, her work on the first experimental quantum fast hitting [Tang, H. et al, Nat. Photon, 12, 758 (2018)] was selected as “China’s Top 10 Optical Breakthroughs in 2018”. She has published works in top-rated journals, including Nature Photonics, Science Advances (2 times), Physical Review Letters (4 times), Optica, Physical Review Applied (2 times) and npj Quantum Information, etc.