Adaptive Quantum Computing Quantum State Prediction

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Adaptive quantum computing represents a paradigm shift in the field, offering the potential for significantly enhanced computational capabilities. A core challenge in this evolution is accurate quantum state prediction, crucial for efficient quantum operations and algorithm design. This paper introduces a novel self-adaptive quantum computing algorithm designed to address this challenge by dynamically adjusting algorithm parameters based on prediction results. We propose a feedback loop that continuously refines the algorithm, improving prediction accuracy and efficiency. The algorithm's core mechanism involves a dynamic parameter adjustment based on the difference between predicted and observed states, offering a real-time prediction capability. This research explores the potential of this approach to overcome limitations of static methods and paves the way for more effective quantum state prediction.

DOI: 10.5281/zenodo.22200171

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