Multi-Level Quantum Output Compression for Post-Processing Speed
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Solution Overview
Problem
Traditional approaches for quantum computing fail to efficiently and quickly post-process large amounts of data produced by quantum computers, leading to delayed delivery of results to users or services.
Innovation Solution
A system comprising a processor and memory that compresses quantum output data using multiple compression levels and adaptive algorithms, determining the appropriate level based on defined criteria and machine learning analysis to ensure sufficient data is processed by quantum logic components, thereby speeding up post-processing and reducing data volume.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If quantum output data is processed using traditional post-processing methods, then data accuracy is maintained, but processing time is excessively long and data volume is large
Solution Approach 1:
The patent segments quantum output data into multiple partitions and processes them in parallel using multiple quantum logic circuits. This segmentation enables simultaneous processing of different data portions, significantly reducing overall post-processing time while maintaining data accuracy through distributed computation across multiple circuit instances.
Solution Approach 2:
The patent applies preliminary compression to quantum output data before it enters the main post-processing pipeline. By pre-compressing the data and removing redundant information upfront, the system reduces the volume of data that requires extensive post-processing, thereby accelerating the overall processing speed without sacrificing essential information.
2Quantity of substance
If quantum output data is compressed to reduce data volume, then data transmission and storage efficiency improve, but data quality and processing accuracy may deteriorate
Solution Approach 1:
The patent implements dynamic compression that adapts to the specific characteristics of quantum output data. The compression level and method are adjusted in real-time based on data patterns, ensuring optimal compression ratios while preserving critical information. This dynamic approach prevents over-compression that would degrade data quality while maximizing volume reduction.
Solution Approach 2:
The patent employs multiple compression algorithms with different parameters and applies them selectively to different portions of quantum output data. By changing compression parameters based on data characteristics, the system achieves effective volume reduction while maintaining data integrity. Different compression strategies are used for different data types to preserve necessary precision.
3Productivity
If multiple compression levels are applied to quantum output data, then data processing efficiency improves, but system complexity increases
Solution Approach 1:
The patent introduces a compression management component that acts as an intermediary between the quantum logic circuits and the post-processing pipeline. This mediator automatically selects appropriate compression levels and algorithms based on data characteristics, shielding the rest of the system from the complexity of managing multiple compression strategies. The intermediary handles the complexity internally while presenting a simplified interface to other components.
Solution Approach 2:
The patent implements feedback mechanisms that monitor data quality and processing performance across multiple compression levels. Based on this feedback, the system automatically adjusts compression parameters and selects optimal processing paths. The feedback loop ensures that complexity is managed adaptively, maintaining efficiency while preventing unnecessary complexity from degrading performance.
Data Source
AI summary
Techniques for managing and compressing quantum output data (QOD) associated with quantum computing are presented. In response to receiving QOD from a quantum computer, a compressor component can compress QOD at first compression level to generate first compressed QOD, and can compress QOD at second compression level to generate second compressed QOD, the second compressed QOD can be less compressed than the first compressed QOD. Compressor management component (CMC) can determine whether first QOD includes sufficient data to enable it to be suitably processed by quantum logic. If so, CMC can allow first compressed QOD to continue to be sent to quantum logic and can discard second compressed QOD. If not sufficient, CMC can determine that second compressed QOD is to be processed by quantum logic. If CMC determines second compressed QOD does not include sufficient data, CMC can determine that the QOD is to be processed by quantum logic.