Quantum CFD Mesh Compression for Faster Fluid-Solid Lookup
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Solution Overview
Problem
Quantum computing systems face bottlenecks when loading large lists of fluid/solid data for computational fluid dynamics, negating the computational advantages they offer.
Innovation Solution
A Voxel Union Mesh (VUM) representation is used to compactly store fluid/solid points, reducing the number of lookup operations by generating the minimum set of rectangular prisms that cover a given set of pixels or voxels, allowing faster determination of point properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If large lists of fluid/solid data are loaded for quantum computational fluid dynamics, then computational accuracy is maintained, but processing time increases and quantum computing advantages are negated
Solution Approach 1:
The computational domain is segmented into discrete point groups (voxels or pixels) organized in a union mesh table. Each point group represents a spatial region with uniform properties, allowing the system to process groups rather than individual points. This segmentation reduces the total number of operations required while maintaining computational accuracy through systematic sampling and representation of the fluid domain.
Solution Approach 2:
The union mesh table is pre-computed and stored before the quantum computational fluid dynamics execution. The table contains pre-organized point groups with their spatial relationships and properties already established. This preliminary organization eliminates the need for real-time data processing during computation, significantly reducing processing time while preserving accuracy.
2Loss of information
If traditional data structures are used for fluid/solid points, then complete data representation is achieved, but data loading and lookup operations become computationally expensive
Solution Approach 1:
Multiple individual point data structures are merged into unified point groups in the union mesh table. Points with similar properties and spatial proximity are combined into single representational units. This merging reduces data redundancy and accelerates lookup operations by allowing quantum algorithms to query groups rather than individual points, while maintaining complete data representation through the group structure.
Solution Approach 2:
The union mesh table creates a compressed representative copy of the complete fluid/solid domain data. Instead of storing and processing every individual point, the table stores consolidated point groups that capture the essential spatial and property information. This copying approach preserves data completeness for computational purposes while dramatically reducing memory access and lookup overhead.
Data Source
AI summary
A computational fluid dynamics system may include a quantum computing circuit and a processor. The processor may be configured to generate and store a union mesh table representing a plurality of point groups, with at least some points being shared among different groups, and each point having a same property. The processor may be further configured to cooperate with the quantum computing circuit to perform a fluid dynamic computation based on a streaming fluid velocity vector and the union mesh table.