Distributed blind quantum computing using a two-node quantum network based on Silicon-vacancy (SiV) centers in nanophotonic cavities

ORAL

Abstract

Quantum networks have the potential to enable secure communications and distributed quantum computing. The key obstacle thus far has been the difficulty in achieving efficient light-matter interfaces while accessing multi-qubit controls. In this talk, I will first talk about our approach to realizing a two-node quantum network based on the silicon-vacancy center (SiV) in diamond in nanophotonic cavities. Each node contains an electronic spin communication qubit and a nuclear spin memory qubit, while cavity-enhanced interactions enable heralded entangling gates between the spin qubits and time-bin photons, allowing us to generate remote entanglement between two physically separate nodes. This directly enables applications leveraging distributed quantum systems, such as blind quantum computing (BQC). In the second part, I will talk about our recent work in the experimental demonstration of BQC using this two-node quantum network. Specifically, I will report the first experimental implementation of a universal gate set for matter-based BQC, including distributed blind operations, using a two-node SiV-based quantum network.

Publication: Y.-C. Wei, et al., arXiv preprint arXiv:2412.03020 (2024)

Presenters

  • Yan-Cheng Wei

    Harvard University

Authors

  • Yan-Cheng Wei

    Harvard University

  • Pieter-Jan Constant Stas

    Harvard University

  • Aziza Suleymanzade

    Harvard University

  • Gefen Baranes

    Massachusetts Institute of Technology, Harvard University

  • Francisco Machado

    Harvard - Smithsonian Center for Astrophysics

  • Yan Qi Huan

    Harvard University

  • Can Mithat Knaut

    Harvard University

  • Sophie Weiyi Ding

    Harvard University

  • Moritz Merz

    ETH Zurich

  • Erik Knall

    Harvard University

  • Umut Yazlar

    Boston University, Harvard University

  • Maxim Sirotin

    Massachusetts Institute of Technology, Harvard University

  • Iria Wang

    Harvard University

  • Bart Machielse

    Harvard University, Lightsynq Technologies Inc.

  • Susanne F Yelin

    Harvard University

  • Johannes Borregaard

    Harvard University

  • Hongkun Park

    Harvard University

  • Marko Loncar

    Harvard University

  • Mikhail D Lukin

    Harvard University