Quantum Brain
← Back to papers

Pattern-based quantum functional testing

Erik Weiss, Marcel Cech, Stanislaw Soltan, Martin Koppenhofer, M. Krebsbach, Thomas Wellens, Daniel Braun·May 31, 2024
Physics

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

Abstract

With the growing number of qubits of quantum information processing devices, the task of fully characterizing these processors becomes increasingly unfeasible. From a practical perspective, one wants to find possible errors in the functioning of the device as quickly as possible, or otherwise establish its correct functioning with high confidence. In response to these challenges, we propose a pattern-based approach inspired by classical memory testing algorithms to evaluate the functionality of a quantum memory, based on plausible failure mechanisms. We demonstrate the method's capability to extract pattern dependencies of important qubit characteristics, such as $T_1$ and $T_2$ times, and to identify and analyze interactions between adjacent qubits. Additionally, our approach enables the detection of different types of crosstalk effects and of signatures indicating non-Markovian dynamics in individual qubits.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.