Quantum Program Characterization Without Execution Using Secure Vectors
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Solution Overview
Problem
Characterizing quantum programs without executing them on a quantum computing system is challenging, especially when the content is unknown, which complicates understanding their intent and required resources, and existing methods may violate data privacy concerns.
Innovation Solution
A system and method that utilizes previously characterized quantum programs to compare and assign attributes to unknown quantum programs, converting them into a secure format for analysis without execution, using AI and ML techniques to determine similarities and required system components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If quantum programs are executed on a quantum computing system to characterize them, then understanding of their intent and functionality is improved, but resource demand and execution time increase
Solution Approach 1:
The patent creates vector representations (copies) of quantum programs that capture their essential characteristics without requiring actual execution. These vector copies enable comparison and characterization of quantum programs through mathematical operations rather than physical quantum computation, thereby understanding program intent while avoiding resource-intensive execution.
Solution Approach 2:
The patent replaces the mechanical quantum computing system with a classical computational approach. Instead of executing quantum programs on quantum hardware, the system uses classical computers to perform vector operations, similarity comparisons, and characterization algorithms, substituting quantum mechanical processes with classical information processing.
2Measurement precision
If quantum programs with unknown content are analyzed, then characterization accuracy is improved, but data privacy concerns worsen
Solution Approach 1:
The patent creates vector representations that serve as privacy-preserving copies of the original quantum programs. These vectors capture functional characteristics necessary for characterization while removing or obscuring sensitive proprietary information, enabling accurate analysis without exposing confidential code content.
Solution Approach 2:
The patent introduces vector representations as an intermediary between the original quantum program and the analysis system. This intermediary layer enables characterization while protecting privacy, as the vectors contain sufficient information for analysis but do not directly expose the original program's sensitive content.
3Speed
If quantum programs are converted to vector representations for comparison, then analysis speed is improved, but implementation complexity worsens
Solution Approach 1:
The patent transforms quantum programs from their original complex format into vector representations with simplified parameters. This parameter transformation enables faster comparison operations using standard mathematical techniques while the system manages the complexity of the transformation process through automated algorithms.
Data Source
AI summary
Various systems and methods are presented herein regarding automatically utilizing characterized codes to characterize an undefined code. The undefined code can be computer instructions for implementation with a quantum computing system. Characterizing the undefined code with previously characterized codes enables knowledge of the undefined code to be acquired without the undefined code having to be executed on the quantum computing system. Prior to characterizing the undefined code, the undefined code can be converted from an original format (e.g., high-level language) to a secure format (e.g., low-level language), wherein the secure format cannot be reverse engineered back to the original format. The undefined code can be represented as a vector, with characterization based on a characterized code having a similar vector representation as the vector representation of the undefined code.