Big Data Processing via Quantum State Modeling
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Solution Overview
Problem
Current technologies lack a holistic approach for understanding and analyzing large-scale, heterogeneous big data sets, which are typically processed using superscalar computers, but these methods are not effective for users with limited hardware resources and fail to provide reliable insights into both current and future data dynamics.
Innovation Solution
A computer-implemented method for automated parameter specification from raw data, involving data import from distributed heterogeneous sources, extraction of object entities, generation of relations, calculation of statistical measurement parameters, and prediction of future trends, which can process any type of raw data without human intervention and minimize bias.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional superscalar computers are used to process big data, then processing power is increased, but hardware resource requirements increase and accessibility for users with limited resources decreases
Solution Approach 1:
The patent replaces traditional mechanical computing approaches with a quantum computing model that uses quantum bits (qubits) representing technical objects. This substitution enables complex data processing without requiring proportionally complex hardware resources, as the quantum model processes technical energy dynamics directly at the information level rather than through sequential mechanical operations.
Solution Approach 2:
The patent transforms the processing approach by changing from classical binary parameters to quantum mechanical parameters that describe technical energy dynamics. By modeling data as quantum states representing technical objects and their energy transformations, the system achieves high processing capability while using standardized quantum computing hardware rather than specialized superscalar architectures.
2Ease of operation
If linear statistical analysis methods are used, then simplicity is maintained, but holistic understanding of complex data dynamics is lost
Solution Approach 1:
The patent adds a new dimension to data analysis by introducing quantum mechanical concepts of technical energy dynamics. Instead of linear statistical analysis, the system models data as quantum states with multiple dimensions representing different aspects of technical object behavior. This enables holistic understanding while maintaining mathematical tractability through quantum probability amplitudes that encode complex relationships.
Solution Approach 2:
The patent creates a composite analytical framework that combines quantum computing theory with domain-specific knowledge about technical systems. This composite approach integrates multiple layers of analysis (quantum states, technical energy dynamics, domain semantics) into a unified model that preserves holistic information while providing structured, interpretable results through the quantum formalism.
3Reliability
If manual data processing is performed, then human judgment is applied, but time consumption increases and human bias is introduced
Solution Approach 1:
The patent implements self-service processing where the quantum computing system automatically extracts and analyzes technical energy dynamics from data without human intervention. The quantum model inherently captures domain knowledge about technical systems and performs autonomous analysis, eliminating both the time cost and bias problems of manual processing while maintaining high-quality insights through the mathematical rigor of quantum mechanics.
Solution Approach 2:
The patent incorporates feedback mechanisms where the quantum computing system iteratively refines its analysis of technical energy dynamics. By using quantum measurement and collapse, the system receives feedback from the data itself, automatically adjusting its model to better represent the underlying technical processes. This closed-loop approach ensures reliability without human judgment while maintaining efficiency through automated adaptation.
4Ease of manufacture
If data is broken into small manageable pieces, then processing feasibility is improved, but holistic understanding of the system is lost
Solution Approach 1:
The patent applies segmentation by representing complex technical systems as collections of quantum bits, each encoding information about a specific technical object or component. This segmentation enables manageable processing of large datasets while the quantum formalism naturally integrates the segmented information through superposition and entanglement, preserving holistic system understanding without requiring processing of the entire dataset as a single unit.
Data Source
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AI summary
The present invention is directed towards a computer-implemented method for hardware independent processing of big data applications allowing an enhanced analysis of extracted parameters. The suggested method is able to automatically perform technical processes such that firstly no human ado is required and secondly the resulting data is not prone to errors. The method suggests iterations on evolving data sets and hence a bias is excluded or at least minimized in each iteration. The invention is furthermore directed towards a respectively arranged system along with a computer program product and a computer-readable medium.