Quantum State Adaptation and Cooperative Optimization for Quantum Computing

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum state adaptation is a crucial aspect of quantum computation, enabling the manipulation of qubits and ultimately, the execution of complex algorithms. This paper explores a novel approach to quantum state adaptation, termed "Adaptive Parameter Adjustment with Cooperative Optimization," which leverages self-adaptation and synergistic optimization to enhance quantum computation performance. We present a framework that dynamically adjusts parameters based on the quantum state, intelligently combining the strengths of quantum algorithms and classical optimization techniques. The core mechanism focuses on a continuous feedback loop to refine the quantum state, resulting in improved fidelity and precision in quantum computations. This research contributes to the advancement of quantum computing by offering a more robust and adaptable strategy for state optimization, paving the way for significantly enhanced computational capabilities.

DOI: 10.5281/zenodo.22203215

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