DisQ: A Novel Quantum Output State Classification Method on IBM Quantum Computers using OpenPulse

TL;DR

DisQ introduces a new quantum output state classification method designed to reduce error rates in quantum programs on IBM quantum computers, leveraging OpenPulse to optimize state definitions.

Contribution

The paper presents DisQ, a novel classification approach that enhances quantum output state accuracy and reduces errors on NISQ devices, a relatively unexplored area.

Findings

DisQ improves quantum program accuracy on IBM quantum computers.

The method effectively reduces error rates in quantum output states.

OpenPulse integration enhances state classification efficiency.

Abstract

Superconducting quantum computing technology has ushered in a new era of computational possibilities. While a considerable research effort has been geared toward improving the quantum technology and building the software stack to efficiently execute quantum algorithms with reduced error rate, effort toward optimizing how quantum output states are defined and classified for the purpose of reducing the error rate is still limited. To this end, this paper proposes DisQ, a quantum output state classification approach which reduces error rates of quantum programs on NISQ devices.