Brain-Computer Interface Acceleration through Quantum Computing

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper explores the potential of quantum computing to revolutionize brain-computer interfaces (BCIs) and accelerate complex computations within the brain. We propose a novel architecture for a quantum-enhanced BCI, leveraging quantum algorithms to efficiently decode brain signals and translate them into optimized quantum operations. The core mechanism centers around a quantum-accelerated signal processing pipeline, aiming to significantly increase the speed and accuracy of neural control tasks. The paper details the design of the BCI system, outlining the quantum algorithms employed, the hardware components involved, and a preliminary analysis of the expected performance improvements. We conclude by highlighting the novelty and potential impact of this approach, emphasizing its promise for advancements in neuroscience, cognitive computing, and control systems.

DOI: 10.5281/zenodo.22323701

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