BibTex format

author = {Yu, S and Zhong, Z-P and Fang, Y and Patel, RB and Li, Q-P and Liu, W and Li, Z and Xu, L and Sagona-Stophel, S and Mer, E and Thomas, SE and Meng, Y and Li, Z-P and Yang, Y-Z and Wang, Z-A and Guo, N-J and Zhang, W-H and Tranmer, GK and Dong, Y and Wang, Y-T and Tang, J-S and Li, C-F and Walmsley, IA and Guo, G-C},
doi = {10.1038/s43588-023-00526-y},
journal = {Nat Comput Sci},
pages = {839--848},
title = {A universal programmable Gaussian boson sampler for drug discovery.},
url = {},
volume = {3},
year = {2023}

RIS format (EndNote, RefMan)

AB - Gaussian boson sampling (GBS) has the potential to solve complex graph problems, such as clique finding, which is relevant to drug discovery tasks. However, realizing the full benefits of quantum enhancements requires large-scale quantum hardware with universal programmability. Here we have developed a time-bin-encoded GBS photonic quantum processor that is universal, programmable and software-scalable. Our processor features freely adjustable squeezing parameters and can implement arbitrary unitary operations with a programmable interferometer. Leveraging our processor, we successfully executed clique finding on a 32-node graph, achieving approximately twice the success probability compared to classical sampling. As proof of concept, we implemented a versatile quantum drug discovery platform using this GBS processor, enabling molecular docking and RNA-folding prediction tasks. Our work achieves GBS circuitry with its universal and programmable architecture, advancing GBS toward use in real-world applications.
AU - Yu,S
AU - Zhong,Z-P
AU - Fang,Y
AU - Patel,RB
AU - Li,Q-P
AU - Liu,W
AU - Li,Z
AU - Xu,L
AU - Sagona-Stophel,S
AU - Mer,E
AU - Thomas,SE
AU - Meng,Y
AU - Li,Z-P
AU - Yang,Y-Z
AU - Wang,Z-A
AU - Guo,N-J
AU - Zhang,W-H
AU - Tranmer,GK
AU - Dong,Y
AU - Wang,Y-T
AU - Tang,J-S
AU - Li,C-F
AU - Walmsley,IA
AU - Guo,G-C
DO - 10.1038/s43588-023-00526-y
EP - 848
PY - 2023///
SP - 839
TI - A universal programmable Gaussian boson sampler for drug discovery.
T2 - Nat Comput Sci
UR -
UR -
VL - 3
ER -