Markovian Noise Modelling and Parameter Extraction Framework for Quantum Devices

TL;DR

This paper introduces a hardware-agnostic, real-time framework for modeling Markovian noise in quantum devices, enabling efficient calibration and performance evaluation of NISQ computers, demonstrated on IBM Quantum hardware.

Contribution

It presents a novel, simplified, and reliable method for extracting multiple calibration parameters simultaneously in quantum devices, improving over previous calibration techniques.

Findings

Framework effectively models Markovian noise in quantum systems.

Enables real-time calibration of hardware parameters.

Reduces computational cost by leveraging qubit pair consistency.

Abstract

In recent years, Noisy Intermediate Scale Quantum (NISQ) computers have been widely used as a test bed for quantum dynamics. This work provides a new hardware-agnostic framework for modelling the Markovian noise and dynamics of quantum systems in benchmark procedures used to evaluate device performance. As an accessible example, the application and performance of this framework is demonstrated on IBM Quantum computers. This framework serves to extract multiple calibration parameters simultaneously through a simplified process which is more reliable than previously studied calibration experiments and tomographic procedures. Additionally, this method allows for real-time calibration of several hardware parameters of a quantum computer within a comprehensive procedure, providing quantitative insight into the performance of each device to be accounted for in future quantum circuits. The framework proposed here has the additional benefit of highlighting the consistency among qubit pairs when extracting parameters, which leads to a less computationally expensive calibration process than evaluating the entire device at once.