A Thin Film Lithium Niobate Near-Infrared Platform for Multiplexing Quantum Nodes

• URL: http://arxiv.org/abs/2405.03912v1
• Date: Tue, 7 May 2024 00:13:46 GMT
• Title: A Thin Film Lithium Niobate Near-Infrared Platform for Multiplexing Quantum Nodes
• Authors: Daniel Assumpcao, Dylan Renaud, Aida Baradari, Beibei Zeng, Chawina De-Eknamkul, C. J. Xin, Amirhassan Shams-Ansari, David Barton, Bartholomeus Machielse, Marko Loncar,
• Abstract summary: Quantum networks will require quantum nodes consisting of many memory qubits. This in turn will require strategies to multiplex memories and overcome the inhomogeneous distribution of their transition frequencies. In this work, we realize a VNIR thin-film lithium niobate (TFLN) integrated photonics platform with the key components to meet these requirements.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Practical quantum networks will require quantum nodes consisting of many memory qubits. This in turn will increase the complexity of the photonic circuits needed to control each qubit and will require strategies to multiplex memories and overcome the inhomogeneous distribution of their transition frequencies. Integrated photonics operating at visible to near-infrared (VNIR) wavelength range, compatible with the transition frequencies of leading quantum memory systems, can provide solutions to these needs. In this work, we realize a VNIR thin-film lithium niobate (TFLN) integrated photonics platform with the key components to meet these requirements. These include low-loss couplers ($<$ 1 dB/facet), switches ($>$ 20 dB extinction), and high-bandwidth electro-optic modulators ($>$ 50 GHz). With these devices we demonstrate high-efficiency and CW-compatible frequency shifting ($>$ 50 $\%$ efficiency at 15 GHz), as well as simultaneous laser amplitude and frequency control through a nested modulator structure. Finally, we highlight an architecture for multiplexing quantum memories using the demonstrated TFLN components, and outline how this platform can enable a 2-order of magnitude improvement in entanglement rates over single memory nodes. Our results demonstrate that TFLN can meet the necessary performance and scalability benchmarks to enable large-scale quantum nodes.

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