Real-Time Digital Twin Modeling via Quantum-Inspired Computing
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Solution Overview
Problem
Current methods for generating digital twins of complex physical systems suffer from high latency and inability to accurately replicate the behavior of systems with numerous components and parameters, making real-time generation challenging.
Innovation Solution
A method utilizing classical computing devices to process data from physical systems using quantum-inspired algorithms, such as machine learning models and optimization algorithms, to generate high-quality digital twin data in real-time without requiring quantum computing devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional algorithms are used to generate digital twin data, then the processing method is simple and does not require quantum-inspired algorithms, but the processing time is too long to achieve real-time generation
Solution Approach 1:
The patent applies quantum-inspired algorithms that fundamentally change the computational parameters and approach, using quantum probability amplitudes and interference patterns to accelerate the processing of digital twin data generation, thereby achieving real-time performance without actual quantum hardware
Solution Approach 2:
The patent replaces traditional classical computational mechanics with quantum-inspired computational mechanics, using quantum probability theory and wave function interference to solve complex system modeling problems more efficiently than conventional algorithms
2Measurement precision
If traditional algorithms are used to generate digital twin data, then the algorithm is easy to implement, but the accuracy of digital twin data is insufficient for complex physical systems
Solution Approach 1:
The patent changes the computational parameters by implementing quantum-inspired algorithms that use quantum probability amplitudes and interference patterns, enabling more accurate representation of complex physical system behaviors that traditional algorithms cannot capture
Solution Approach 2:
The patent introduces quantum-inspired computational models as an intermediary layer between raw sensor data and digital twin representations, using quantum probability theory to mediate the transformation and achieve higher fidelity in modeling complex system behaviors
3Productivity
If quantum computing devices are used to process data, then the processing speed and accuracy are significantly improved, but the requirement for quantum computing devices increases system complexity and availability constraints
Solution Approach 1:
The patent creates a copy or simulation of quantum computational behavior through classical quantum-inspired algorithms, replicating the essential features of quantum probability and interference without requiring actual quantum hardware, thereby making the technology accessible to standard computing devices
Solution Approach 2:
The patent introduces quantum-inspired algorithms as an intermediary computational layer that bridges the gap between classical computing capabilities and quantum-level processing performance, enabling quantum-enhanced productivity on conventional hardware infrastructure
Data Source
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AI summary
The disclosure relates to a method (100) for generating data indicative of a digital twin of a physical system (2), the method comprising: - receiving (120), by at least one classical computing device (11), data acquirable from the physical system (2); and - processing (130), by the at least one classical computing device (11), the data acquirable from the physical system (2) to provide the data indicative of the digital twin, the processing (130) comprising digitally computing a quantum-inspired algorithm. The disclosure also relates to a device or system adapted to execute the method, to at least one computing device configured to execute the steps of the method and to a computer program product having instructions for executing the method.