Quantum Instruction Compiler for Hybrid Algorithm Execution

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing technologies face challenges in efficiently compiling and executing hybrid classical/quantum algorithms on gate-based superconducting quantum computers due to the complexity and volatility of quantum hardware systems.

Innovation Solution

A compiler is developed to compile hybrid classical/quantum algorithms for quantum processing cells with different configurations and calibration settings, generating target language code executable by a quantum processing system. The compiler parses algorithms, analyzes control flow, addresses quantum instructions to qubits, and optimizes code generation based on hardware-specific information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Power

If quantum hardware systems are used to execute algorithms, then computational capability for complex problems is improved, but hardware complexity and volatility increase

Engineering Contradiction:

Improvecomputational capabilityVSAvoidhardware complexity

Core Design Contradiction:

PowerVSDevice complexity

Solution Approach 1:

The patent introduces a compiler as an intermediary layer between the high-level quantum algorithm and the physical quantum hardware. The compiler translates quantum instructions into hardware-specific operations, managing the complexity of quantum hardware systems while preserving their computational power. This intermediary handles calibration settings, qubit mappings, and instruction optimization, shielding users from hardware volatility.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent segments the compilation process into distinct phases: parsing quantum instructions, analyzing control flow, mapping qubits, optimizing code generation, and handling calibration settings. This segmentation allows each component to be independently optimized and managed, reducing overall system complexity while maintaining computational capability.

Inventive Principle:

Principle #1Segmentation

2Adaptability or versatility

If quantum instructions are compiled for diverse quantum processing cells, then adaptability is improved, but compilation complexity increases

Engineering Contradiction:

Improveadaptability to diverse quantum processing cellsVSAvoidcompilation complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent creates a universal compiler framework that can handle multiple quantum processing cell configurations through a common interface. The compiler reads calibration settings and hardware descriptions from standardized input files, allowing it to adapt to different quantum processors without requiring separate compilation tools for each device type.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent uses parameter-based configuration files that describe quantum processing cell characteristics (qubit counts, connectivity, calibration settings). By changing these parameters, the same compiler can adapt to different hardware configurations. The compiler dynamically adjusts its code generation based on these parameters, optimizing for each specific hardware setup.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If code optimization is performed based on hardware-specific information, then execution efficiency is improved, but compilation time increases

Engineering Contradiction:

Improveexecution efficiencyVSAvoidcompilation time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent performs preliminary analysis of the quantum algorithm during compilation, including control flow analysis and qubit mapping optimization. By pre-calculating optimal qubit assignments and instruction sequences based on hardware characteristics, the compiler reduces execution time during runtime. This preliminary optimization balances compilation time against execution efficiency.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces manual code optimization with automated compiler-based optimization using hardware description files. Instead of manually tuning quantum circuits for different hardware, the compiler automatically generates optimized code by reading hardware specifications and applying optimization algorithms, reducing both compilation time and the need for expert intervention.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12293254B1Quantum instruction compiler for optimizing hybrid algorithms

Publication Date: 2025.05.06 RIGETTI & CO INC

AI summary

A compiler for a gate-based superconducting quantum computer compiles hybrid classical/quantum algorithms for quantum processing cells with different configurations. The compiler inputs the algorithm and outputs code in a target language executable by a quantum processing cell of a quantum processing system that can execute the algorithm. The compiler includes various functionality, such as: parsing, analyzing control flows, addressing, compressing, and translating. The compiler optimizes algorithms in various manners using the functionality. Some optimizations include addressing efficiently, compressing based on simulations, and translating for efficient execution of parametric functions. The compiler may function in the environment of a cloud quantum computing system. The cloud quantum computing system may receive algorithms from remote access nodes for execution on local classical and quantum computing systems.