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20022026
most citedAn Experimental Review on Deep Learning Architectures for Time Series Forecasting

529 citations

Showing 2022 · quant-phShow all

16 papers · 2 filters

quant-ph2022★ 4 cited

Deterministic single-photon source in the ultrastrong coupling regime

Jie Peng, Jianing Tang, Pinghua Tang +7

Deterministic single-photon sources are important and ubiquitous in quantum information protocols. However, to the best of our knowledge, none of them work in the ultrastrong light…

quant-ph2022★ 9 cited

Experimental test of high-dimensional quantum contextuality based on contextuality concentration

Zheng-Hao Liu, Hui-Xian Meng, Zhen-Peng Xu +6

Contextuality is a distinctive feature of quantum theory and a fundamental resource for quantum computation. However, existing examples of contextuality in high-dimensional systems…

quant-ph2022★ 31 cited

Quantum Stirling engine based on dinuclear metal complexes

Clebson Cruz, Hamid-Reza Rastegar-Sedehi, Maron F. Anka +2

Low-dimensional metal complexes are versatile materials with tunable physical and chemical properties that make these systems promising platforms for caloric applications. In this…

quant-ph2022★ 4 cited

Observation of stochastic resonance in directed propagation of cold atoms

Alexander Staron, Kefeng Jiang, Casey Scoggins +3

Randomly diffusing atoms confined in a dissipative optical lattice are illuminated by a weak probe of light. The probe transmission spectrum reveals directed atomic propagation tha…

quant-ph2022★ 2 cited

Boson sampling with ultracold atoms in a programmable optical lattice

Carsten Robens, Iñigo Arrazola, Wolfgang Alt +4

Sampling from a quantum distribution can be exponentially hard for classical computers and yet could be performed efficiently by a noisy intermediate-scale quantum device. A prime…

quant-ph2022★ 8 cited

Quantum reinforcement learning in the presence of thermal dissipation

M. L. Olivera-Atencio, L. Lamata, M. Morillo +1

A study of the effect of thermal dissipation on quantum reinforcement learning is performed. For this purpose, a nondissipative quantum reinforcement learning protocol is adapted t…