Quantum Computing Digital Twin Generation
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Solution Overview
Problem
Current methods for generating digital twins of complex physical systems are hindered by high latency and inability to accurately replicate the behavior of systems with numerous components and parameters, making real-time generation challenging.
Innovation Solution
Employing quantum computing to process data from physical systems, utilizing quantum algorithms and machine learning models, such as quantum optimization and quantum machine learning, to enhance data quality and reduce processing time, allowing for real-time generation of high-quality digital twins.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional digital computing methods are used to generate digital twins of complex physical systems, then the processing can be performed with current technology, but the latency is too high to achieve real-time generation
Solution Approach 1:
The patent substitutes traditional digital computing systems with quantum computing systems to process data from physical systems. Quantum computing leverages quantum mechanical phenomena (superposition, entanglement, interference) to perform computations that are intractable for classical computers, thereby achieving real-time processing speeds necessary for generating digital twins of complex physical systems without excessive latency.
2Measurement precision
If traditional digital computing methods are used to generate digital twins of complex physical systems, then the system can operate with existing technology, but the digital twin cannot accurately behave like the physical system due to complexity
Solution Approach 1:
The patent employs quantum computing to handle the computational complexity of accurately modeling physical systems with numerous components and parameters. Quantum algorithms can efficiently process high-dimensional data and simulate quantum mechanical systems, enabling accurate digital twin generation even for highly complex physical systems that exceed the capabilities of traditional digital computers.
3Productivity
If quantum computing is used to process data from physical systems, then real-time generation of high-quality digital twins is achieved, but the technology requires quantum computing infrastructure
Solution Approach 1:
The patent uses quantum computing as an intermediary processing layer between data acquisition from physical systems and digital twin generation. The quantum computing device receives data from sensors or other sources, processes it using quantum algorithms to extract meaningful patterns and relationships, and outputs results that can be used to generate accurate digital twins in real-time, bridging the gap between raw data and actionable insights.
Data Source
AI summary
The disclosure relates to a method for generating data indicative of a digital twin of a physical system, the method:including the steps of receiving, by at least one quantum computing device, data acquirable from the physical system; andprocessing, by the at least one quantum computing device, the data acquirable from the physical system to provide the data indicative of the digital twin.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.