Implementing quantum dimensionality reduction for non-Markovian stochastic simulation.

Autor: Wu KD; CAS Key Laboratory of Quantum Information, University of Science and Technology of China, Hefei, 230026, People's Republic of China.; CAS Center For Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei, 230026, People's Republic of China., Yang C; Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore, 117543, Singapore. yangchengran92@gmail.com., He RD; CAS Key Laboratory of Quantum Information, University of Science and Technology of China, Hefei, 230026, People's Republic of China.; CAS Center For Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei, 230026, People's Republic of China., Gu M; Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore, 117543, Singapore. mgu@quantumcomplexity.org.; Nanyang Quantum Hub, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore, 637371, Singapore. mgu@quantumcomplexity.org.; MajuLab, CNRS-UNS-NUS-NTU International Joint Research Unit, UMI 3654, Singapore, 117543, Singapore. mgu@quantumcomplexity.org., Xiang GY; CAS Key Laboratory of Quantum Information, University of Science and Technology of China, Hefei, 230026, People's Republic of China. gyxiang@ustc.edu.cn.; CAS Center For Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei, 230026, People's Republic of China. gyxiang@ustc.edu.cn.; Hefei National Laboratory, University of Science and Technology of China, Hefei, 230088, People's Republic of China. gyxiang@ustc.edu.cn., Li CF; CAS Key Laboratory of Quantum Information, University of Science and Technology of China, Hefei, 230026, People's Republic of China.; CAS Center For Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei, 230026, People's Republic of China.; Hefei National Laboratory, University of Science and Technology of China, Hefei, 230088, People's Republic of China., Guo GC; CAS Key Laboratory of Quantum Information, University of Science and Technology of China, Hefei, 230026, People's Republic of China.; CAS Center For Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei, 230026, People's Republic of China.; Hefei National Laboratory, University of Science and Technology of China, Hefei, 230088, People's Republic of China., Elliott TJ; Department of Physics & Astronomy, University of Manchester, Manchester, M13 9PL, UK. physics@tjelliott.net.; Department of Mathematics, University of Manchester, Manchester, M13 9PL, UK. physics@tjelliott.net.; Department of Mathematics, Imperial College London, London, SW7 2AZ, UK. physics@tjelliott.net.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2023 May 06; Vol. 14 (1), pp. 2624. Date of Electronic Publication: 2023 May 06.
DOI: 10.1038/s41467-023-37555-0
Abstrakt: Complex systems are embedded in our everyday experience. Stochastic modelling enables us to understand and predict the behaviour of such systems, cementing its utility across the quantitative sciences. Accurate models of highly non-Markovian processes - where the future behaviour depends on events that happened far in the past - must track copious amounts of information about past observations, requiring high-dimensional memories. Quantum technologies can ameliorate this cost, allowing models of the same processes with lower memory dimension than corresponding classical models. Here we implement such memory-efficient quantum models for a family of non-Markovian processes using a photonic setup. We show that with a single qubit of memory our implemented quantum models can attain higher precision than possible with any classical model of the same memory dimension. This heralds a key step towards applying quantum technologies in complex systems modelling.
(© 2023. The Author(s).)
Databáze: MEDLINE
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