4.8 Article

Near-Field Generation and Control of Ultrafast, Multipartite Entanglement for Quantum Nanoplasmonic Networks

期刊

NANO LETTERS
卷 22, 期 7, 页码 2801-2808

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.nanolett.1c04920

关键词

Multipartite entanglement; quantum networks; quantum Internet; tripartite; near-field transducer; plasmonic waveguide; quantum dot; Greenberger-Horne-Zeilinger (GHZ) state

资金

  1. Science Foundation of Ireland (SFI) [18/RP/6236]

向作者/读者索取更多资源

To realize a quantum Internet, reliable sources of entangled particles compatible with time-dependent, quantum error correction measurement techniques are needed. We propose a scalable, plasmonically based system that utilizes quantum dots as quantum emitters and is excited using a near-field transducer. The system is operable at room temperature with low decoherence rates and allows efficient control of entanglement with maximum fidelity.
For a quantum Internet, one needs reliable sources of entangled particles that are compatible with measurement techniques enabling time-dependent, quantum error correction. Ideally, they will be operable at room temperature with a manageable decoherence versus generation time. To accomplish this, we theoretically establish a scalable, plasmonically based archetype that uses quantum dots (QD) as quantum emitters, known for relatively low decoherence rates near room temperature, that are excited using subdiffracted light from a near-field transducer (NFT). NFTs are a developing technology that allow rasterization across arrays of qubits and remarkably generate enough power to strongly drive energy transitions on the nanoscale. This eases the fabrication of QD media, while efficiently controlling picosecond-scale dynamic entanglement of a multiqubit system that approaches maximum fidelity, along with fluctuation between tripartite and bipartite entanglement. Our strategy radically increases the scalability and accessibility of quantum information devices while permitting fault-tolerant quantum computing using time-repetition algorithms.

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