Physical qubit calibration on a directed acyclic graph

TL;DR

This paper introduces a graph-based framework for calibrating physical qubits, enabling efficient, automatable, and adaptable calibration strategies that account for device variability and drift.

Contribution

It presents a novel directed acyclic graph model to optimize the calibration process of qubits, improving efficiency and extensibility over traditional methods.

Findings

Framework reduces calibration to graph traversal

Automatable and extensible calibration process

Addresses device variability and drift

Abstract

High-fidelity control of qubits requires precisely tuned control parameters. Typically, these parameters are found through a series of bootstrapped calibration experiments which successively acquire more accurate information about a physical qubit. However, optimal parameters are typically different between devices and can also drift in time, which begets the need for an efficient calibration strategy. Here, we introduce a framework to understand the relationship between calibrations as a directed graph. With this approach, calibration is reduced to a graph traversal problem that is automatable and extensible.