Efficient Generation of Multi-partite Entanglement between Non-local Superconducting Qubits using Classical Feedback
Abstract
Quantum entanglement is one of the primary features which distinguishes quantum computers from classical computers. In gate-based quantum computing, the creation of entangled states or the distribution of entanglement across a quantum processor often requires circuit depths which grow with the number of entangled qubits. However, in teleportation-based quantum computing, one can deterministically generate entangled states with a circuit depth that is constant in the number of qubits, provided that one has access to an entangled resource state, the ability to perform mid-circuit measurements, and can rapidly transmit classical information. In this work, aided by fast classical field programmable gate array-based control hardware with a feedback latency of only 150 ns, we explore the utility of teleportation-based protocols for generating non-local, multi-partite entanglement between superconducting qubits. First, we demonstrate well-known protocols for generating Greenberger-Horne-Zeilinger (GHZ) states and non-local CNOT gates in constant depth. Next, we utilize both protocols for implementing a quantum fan-out gate in constant depth among three non-local qubits (i.e., controlled-NOT-NOT). Finally, we demonstrate deterministic state teleportation and entanglement swapping between qubits on opposite sides of our quantum processor. Throughout this work, we find that the fidelity of our teleportation-based protocols is limited by measurement-induced dephasing on idling spectator qubits. Therefore, our work serves as a useful study of the current benefits and limitations of teleportation-based protocols on contemporary superconducting quantum processors.
Cite
@article{arxiv.2403.18768,
title = {Efficient Generation of Multi-partite Entanglement between Non-local Superconducting Qubits using Classical Feedback},
author = {Akel Hashim and Ming Yuan and Pranav Gokhale and Larry Chen and Christian Juenger and Neelay Fruitwala and Yilun Xu and Gang Huang and Kasra Nowrouzi and Liang Jiang and Irfan Siddiqi},
journal= {arXiv preprint arXiv:2403.18768},
year = {2025}
}