Quantum Trend Detection Using Cost-Function Minimization
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Solution Overview
Problem
Current methods for calculating trends in complex data systems are resource-intensive and time-consuming, limiting the number of measurable parameters and leading to a loss of insights due to exponential processing times, especially with conventional computing systems.
Innovation Solution
A computer-implemented method using a quantum processor to solve a cost function representative of trends in a network by creating a multi-dimensional configuration space and iteratively updating tensor network coefficients, leveraging quantum annealing and variational quantum algorithms to identify minimums in the cost function.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of measured parameters is increased to improve understanding of system operation, then the quality of insights into the system is improved, but the processing time increases exponentially
Solution Approach 1:
The patent replaces classical computational systems with a quantum computational system. The quantum computer utilizes quantum mechanical principles (superposition, entanglement, interference) to process the cost function and identify trends, achieving exponential speedup over classical systems for certain computational tasks while maintaining the ability to handle multiple parameters simultaneously
2Measurement precision
If more parameters are measured to improve system understanding, then the quality of insights is improved, but computing resource requirements increase
Solution Approach 1:
The patent substitutes quantum computational resources for classical computational resources. The quantum computer's ability to process multiple states simultaneously through superposition and to explore the solution space through quantum parallelism reduces the overall computing resource requirements despite handling increased numbers of parameters
3Ease of manufacture
If classical methods are used to analyze trends in complex data systems, then the system is easier to implement, but the processing speed is insufficient for real-time analysis
Solution Approach 1:
The patent replaces classical computational mechanisms with quantum computational mechanisms. The quantum computer processes the cost function representing the complex data system by preparing quantum states, applying quantum operations, and measuring outcomes to identify trends, achieving real-time processing speeds unattainable by classical systems
Solution Approach 2:
The patent changes the computational paradigm from classical to quantum. By utilizing quantum parameters such as qubit states, superposition coefficients, and quantum interference patterns, the system achieves fundamentally different processing capabilities that enable real-time analysis of complex data systems
Data Source
AI summary
A computer-implemented method and system for identifying trends in a network of elements. The method comprises obtaining a plurality of properties for the elements in the network, creating a multi-dimensional configuration space from the measured plurality of properties and storing the multi-dimensional configuration space in data storage. A cost function which is representative of the trends in the network is then built and the cost function is passed to a quantum processor for solving to identify a minimum in the cost function. The identified minimum is processed extract in a central processing unit the trends from the identified minimum. The cost function has one or more components which are representative of interaction between different elements in the network.