Experimental Quantum Optics
We are exploring fundamentals in the field of atomic, molecular, and optical (AMO) physics and their applications. Current research activities focus on quantum networks, all-optical neural networks, and applied optical microscopy.
- Quantum Networks (QN)
In align with "A Strategic Vision for America's Quantum Networks" released by the White House in February 2020, we are building a complex quantum network based on photon-matter interactions, and investigate quantum information transmission, storage, and processing. Different from classical communication networks, a quantum network provides services for quantum nodes connection, quantum state or information transmission and processing. Such a quantum network comprises of local quantum nodes (processors, made of neutral atoms, ions, molecules, quantum dots, superconducting circuits, etc.) and the quantum connections (flying photons) between the nodes. Currently except for the well-developed techniques of quantum key distribution, the existing research of quantum networks is still very fundamental. We aim to bridge the gap from fundamental physics to applied engineering, particularly in efficient quantum interface, entanglement distribution, quantum routing, and distributed quantum information processing. Prof. Du's previous researches along this line include generation and manipulation of narrowband entangled photon pairs (biphotons) [Optica 4, 388 (2017); Nat. Commun. 7, 12783 (2016); Phys. Rev. A 93, 033815 (2016); Phys. Rev. Lett. 115, 193601 (2015); Phys. Rev. Lett. 114, 010401 (2015); Phys. Rev. Lett. 113, 133601 (2014); Optica 1, 84 (2014); Phys. Rev. Lett. 104, 183604 (2010); J. Opt. Soc. Am. B 25, C98 (2008)], realizatdion of efficient quantum memory for photonic qubits [Nat. Photon. 13, 346 (2019); Opt. Express 20, 24124 (2012); Opt. Lett. 36, 4530 (2011)], and nonlinear interactions between light and atoms [Phys. Rev. Lett. 124, 010509 (2020); Phys. Rev. Lett. 123, 193604 (2019); Phys. Rev. Lett. 119, 150406 (2017); Phys. Rev. Lett. 119, 050602 (2017)].
- All-Optical Neural Networks (AONN)
Machine learning based on artificial neural networks (ANN) has found wide applications in many fields, such as image recognition, medical diagnosis, machine translation, and scientific research such as finding new materials. Most of these artificial intelligence (AI) implementations are computer software based, which are typically resource driving and power consuming and run slowly. In spite of the effort for developing AI chips with electronic architecture, optical implementation recently attracted interest because of its intrinsic parallelism and high speed. We aim at developing all-optical implementation of ANN basing on linear and nonlinear optics and finding their practical applications. In 2019, we demonstrated the world-first multi-layer AONN with nonlinear optical activation functions [Optica 6, 1132 (2019); see OSA News Release: "Researchers Demonstrate All-Optical Neural Network for Deep Learning"].
- Optical Microscopy
We are interested in developing advanced optical microscopy imaging techniques and applying them to study various problems in life science, biomedical engineering, and material science, through strong interdisciplinary and cross-field collaborations. We have invented a user-friendly multi-color super-resolution localization microscope [Opt. Express 23, 1879 (2015)], the line-Bessel sheet (LBS) light-sheet fluorescent microscopy for 5D live-cell imaging [Opt. Commun. 450, 166 (2019); Sci. Rep. 6, 26159 (2016)], and the dual beam-shear differential interference microscopy for full-field surface deformation gradient characterization [ J. Mech. Phys. Solid 145, 104162 (2020); J. Mech. Phys. Solids 124, 102 (2019)] - These technologies have been successfully commercialized by Light Innovation technology Ltd., a spin-off company from Prof. Du's previous group in Hong Kong.