# 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.

## Key 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.