Barium Qubit State Detection and Ba Ion-Photon Entanglement

ORAL

Abstract

A modular ion-trap network is a promising framework for scalable quantum-computational devices. In this architecture, different ion-trap modules are connected via photonic buses while within one module ions interact locally via phonons. To eliminate cross-talk between photonic-link qubits and memory qubits, we use different atomic species for quantum information storage ($^{171}$Yb$^+$) and intermodular communication ($^{138}$Ba$^+$). Conventional deterministic Zeeman-qubit state detection schemes require additional stabilized narrow-linewidth lasers. Instead, we perform fast probabilistic state detection utilizing efficient detectors and high-NA lenses to detect emitted photons from circularly polarized 493 nm laser excitation. Our method is not susceptible to intensity and frequency noise, and we show single-shot detection efficiency of $\sim$2\%, meaning that we can discriminate between the two qubits states with 99\% confidence after as little as 50 ms of averaging. Using this measurement technique, we report entanglement between a single $^{138}$Ba$^+$ ion and its emitted photon with 86\% fidelity.

*This work is supported by the ARO with funding from the IARPA MQCO program, the DARPA Quiness program, the AFOSR MURI on Quantum Transduction, and the ARL Center for Distributed Quantum Information.

Authors

  • Ksenia Sosnova

    • Joint Quantum Institute and University of Maryland Department of Physics, College Park, Maryland 20742
  • Ismail Volkan Inlek

    • Joint Quantum Institute and University of Maryland Department of Physics, College Park, Maryland 20742
  • Clayton Crocker

    • Joint Quantum Institute and University of Maryland Department of Physics, College Park, Maryland 20742
  • Martin Lichtman

    • Joint Quantum Institute and University of Maryland Department of Physics, College Park, Maryland 20742
  • Christopher Monroe

    • Joint Quantum Institute and University of Maryland Department of Physics, College Park, Maryland 20742