Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits

Understand

Parameterized Quantum Circuits (PQCs) have been acknowledged as a leading strategy to utilize near-term quantum advantages in multiple problems, including machine learning and combinatorial optimization.

• When applied to specific tasks, the parameters in the quantum circuits are trained to minimize the target function.
• Although there have been comprehensive studies to improve the performance of the PQCs on practical tasks, the errors caused by the quantum noise downgrade the performance when running on real quantum computers.
• In particular, when the quantum state is transformed through multiple quantum circuit layers, the effect of the quantum noise happens cumulatively and becomes closer to the maximally mixed state or complete noise.