Quantum gate teleportation between separated qubits in a trapped-ion processor

Abstract

Large-scale quantum computers will require quantum gate operations between widely separated qubits. A method for implementing such operations, known as quantum gate teleportation (QGT), requires only local operations, classical communication, and shared entanglement. We demonstrate QGT in a scalable architecture by deterministically teleporting a controlled-NOT (CNOT) gate between two qubits in spatially separated locations in an ion trap. The entanglement fidelity of our teleported CNOT is in the interval (0.845, 0.872) at the 95% confidence level. The implementation combines ion shuttling with individually addressed single-qubit rotations and detections, same- and mixed-species two-qubit gates, and real-time conditional operations, thereby demonstrating essential tools for scaling trapped-ion quantum computers combined in a single device.

Detecting and tracking drift in quantum information processors

“…The counts may then be irreconcilable with any model for the QIP that assumes that all operations (state preparations, gates, and measurements) are time-independent. This discrepancy results in failed or unreliable tomography and benchmarking experiments [16][17][18][19][20][21][22] .…”

“…This is becoming a critical concern as stable sources of errors are steadily reduced. For example, drift significantly impacted the recent tomographic experiments of Wan et al 22 but this was only verified using a complicated, special-purpose analysis. In this article, we have introduced a general, flexible, and powerful methodology for diagnosing instabilities in a QIP.…”

“…We have incorporated these tools into an open-source software package 52,53 , making it easy to check any time-series QIP data for signs of instability. Because of the disastrous impact of drift on characterization protocols [16][17][18][19][20][21][22] , its largely unknown impact on QIP applications, and the minimal overhead required to implement our methods, we hope to see this analysis broadly and quickly adopted.…”

“…But almost all of these techniques assume that the QIP is stable-that data taken over a second or an hour reflects some constant property of the processor. These methods can malfunction badly if the actual error mechanisms are timedependent [16][17][18][19][20][21][22] .…”

“…Yet temporal instability in QIPs is ubiquitous [21][22][23][24][25][26][27][28][29][30][31][32] . The control fields used to drive logic gates drift 22 , T 1 times can change abruptly 32 , low-frequency 1/f α noise is common 24 , and laboratory equipment produces strongly oscillating noise (e.g., 50 Hz/60 Hz line noise and~1 Hz mechanical vibrations from refrigerator pumps). These intrinsically time-dependent error mechanisms are becoming more and more important as technological improvements suppress stable and better-understood errors.…”