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A universal programmable Gaussian boson sampler for drug discovery

Shang Yu, Zhipeng Zhong, Yuhua Fang, Raj B. Patel, Qingpeng Li, Wei Liu, Zhenghao Li, Liang Xu, Steven Sagona-Stophel, Ewan Mer, S. E. Thomas, Meng Yu, Zhipeng Li, Yuan-Ze Yang, Zhaoan Wang, Nai‐Jie Guo, Wen-Hao Zhang, Geoffrey K. Tranmer, Ying Dong, Yi‐Tao Wang, Jian‐Shun Tang, Chuan‐Feng Li, Ian A. Walmsley, Guang‐Can Guo

2023Nature Computational Science44 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Computer scienceScalabilityCliqueQuantum computerGaussianQuantum circuitUnitary stateTheoretical computer scienceParallel computingQuantumComputational scienceComputer engineeringQuantum networkMathematicsPhysicsQuantum mechanicsDatabasePolitical scienceLawCombinatoricsNeural Networks and Reservoir ComputingQuantum Computing Algorithms and ArchitectureQuantum Information and Cryptography