With the rapid development of artificial intelligence, computational systems are gradually evolving toward multi-modal integration and human-like reasoning. However, traditional computing architectures face fundamental limitations in computing power, error correction, and theoretical boundaries. Quantum computing, especially quantum entanglement and interference mechanisms, provides a potential path to overcome these limitations, but existing quantum error-correction theories remain incomplete and are difficult to integrate with artificial intelligence systems. This paper proposes a theoretical framework that combines an artificial intelligence virtual personality model with a quantum entanglement interference error-correction model. By introducing forward and backward wave-function entanglement, discrete-variable wave-function structures, and symmetric interference transmission, the model establishes a unified description of information propagation, correction, and stability. The framework further extends Boolean algebra, Turing computation models, and multi-modal intelligence growth into a cross-domain structure suitable for AI–quantum hybrid systems. In addition, this work explores the philosophical foundation of virtual personality, treating intelligence as the interaction between physical realization and virtual consciousness, and discusses the necessity of ethical and legal frameworks for artificial intelligence virtual personality. The proposed model aims to provide a theoretical basis for the transitional integration of artificial intelligence and quantum computing, and to support future development of quantum-enhanced intelligent systems.
This paper explores a novel approach to self-correcting digital circuits utilizing quantum-inspired principles, specifically entanglement-based feedback. Traditional digital circuit error correction techniques often rely on redundancy and complex decoding algorithms, which can be computationally intensive and energy-consuming. This work proposes a circuit architecture that leverages entangled qubits to dynamically adjust circuit parameters in real-time, mimicking quantum interference to effectively mitigate the impact of noise and errors. The core mechanism involves designing a feedback loop where entangled qubits act as sensors and actuators, continuously monitoring and correcting the circuit's state. Mathematical models are presented to illustrate the principles and potential performance of this approach. The proposed method represents a fundamentally different paradigm for error correction, offering a potentially more efficient and robust solution for digital circuits. Key performance metrics such as error correction probability, latency, and energy consumption are discussed. The research contributes to the growing field of quantum-inspired computing and its application to practical digital circuit design.