中国物理B ›› 2022, Vol. 31 ›› Issue (4): 48704-048704.doi: 10.1088/1674-1056/ac40fb
Yangyang Ge(葛阳阳), Zhimin Wang(王治旻), Wen Zheng(郑文), Yu Zhang(张钰), Xiangmin Yu(喻祥敏), Renjie Kang(康人杰), Wei Xin(辛蔚), Dong Lan(兰栋), Jie Zhao(赵杰), Xinsheng Tan(谭新生), Shaoxiong Li(李邵雄)†, and Yang Yu(于扬)‡
Yangyang Ge(葛阳阳), Zhimin Wang(王治旻), Wen Zheng(郑文), Yu Zhang(张钰), Xiangmin Yu(喻祥敏), Renjie Kang(康人杰), Wei Xin(辛蔚), Dong Lan(兰栋), Jie Zhao(赵杰), Xinsheng Tan(谭新生), Shaoxiong Li(李邵雄)†, and Yang Yu(于扬)‡
摘要: Quantum singular value thresholding (QSVT) algorithm, as a core module of many mathematical models, seeks the singular values of a sparse and low rank matrix exceeding a threshold and their associated singular vectors. The existing all-qubit QSVT algorithm demands lots of ancillary qubits, remaining a huge challenge for realization on nearterm intermediate-scale quantum computers. In this paper, we propose a hybrid QSVT (HQSVT) algorithm utilizing both discrete variables (DVs) and continuous variables (CVs). In our algorithm, raw data vectors are encoded into a qubit system and the following data processing is fulfilled by hybrid quantum operations. Our algorithm requires O[log(MN)] qubits with O(1) qumodes and totally performs O(1) operations, which significantly reduces the space and runtime consumption.
中图分类号: (Algorithms)