Quantum Computation Engine Reduces Task Dimensionality
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Solution Overview
Problem
Complex computational tasks are often intractable for both classical and quantum computing resources due to high dimensionality or complexity, limiting their ability to provide efficient solutions.
Innovation Solution
A quantum computation engine that utilizes multiple calls to quantum computing resources to reduce the complexity of tasks through methods like principal component analysis, followed by processing with classical or quantum resources to generate approximate solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If quantum computing resources are used to solve complex computational tasks, then computational speed and capability are improved, but device complexity and task dimensionality increase
Solution Approach 1:
The patent divides complex computational tasks into multiple sub-tasks by routing them to different quantum computing resources based on problem classification. This segmentation allows each sub-task to be processed by appropriately matched resources, reducing the dimensionality burden on any single resource while maintaining overall computational speed.
Solution Approach 2:
The patent introduces a routing dimension that classifies computational tasks into different categories and directs them to specialized quantum resources. This dimensional approach to task organization enables efficient resource utilization by matching task characteristics with resource capabilities, effectively managing task dimensionality.
2Measurement precision
If multiple quantum computing resources are used to process computational tasks, then solution accuracy is improved, but loss of time increases
Solution Approach 1:
By segmenting computational tasks into sub-tasks and routing them to different quantum resources simultaneously, the system processes multiple aspects of the problem in parallel. This segmentation enables accurate solution generation without sequential time penalties, as different resources work concurrently on divided task portions.
Solution Approach 2:
The patent performs preliminary classification and routing of computational tasks before processing begins. This preliminary action organizes tasks optimally for parallel execution, ensuring that when processing starts, the decomposition and resource allocation are already in place, thereby reducing overall processing time while maintaining accuracy.
Data Source
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AI summary
Methods, systems, and apparatus for solving optimization tasks. In one aspect, a system includes one or more classical processors and one or more quantum computing resources, wherein the one or more classical processors and one or more quantum computing resources are configured to perform operations comprising receiving input data comprising data specifying a computational task to be solved; processing the received input data using a first quantum computing resource to generate data representing a reduced computational task, wherein the reduced computational task has lower dimensionality that the computational task; and processing the data representing the reduced computational task to obtain a solution to the computational task.