Quantum Circuit Subcircuit Orchestration via Segmentation
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Solution Overview
Problem
Executing quantum circuits in quantum computing systems is complex and resource-intensive due to limitations in qubit count, accuracy issues with larger hardware, and exponential resource requirements in simulated systems.
Innovation Solution
The system employs an orchestration engine to dynamically manage the execution of quantum jobs by cutting large quantum circuits into smaller subcircuits, optimizing resource usage through runtime predictions and telemetry data, and generating execution plans that account for service-level objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If quantum circuits are executed on real quantum hardware with more qubits, then the circuit size capacity increases, but the accuracy decreases
Solution Approach 1:
The patent divides a large quantum circuit into multiple smaller subcircuits that can be executed separately on quantum hardware with fewer qubits. Each subcircuit is processed independently and the results are combined classically, avoiding the need to use larger quantum hardware that would provide fewer qubits but higher accuracy per operation.
2Adaptability or versatility
If quantum circuits are simulated with increased complexity, then the circuit capability increases, but the resource consumption increases exponentially
Solution Approach 1:
The patent segments complex quantum circuits into smaller subcircuits that can be simulated with manageable computational resources. By dividing the circuit execution into multiple smaller tasks that are processed sequentially or in parallel, the exponential resource consumption is reduced to linear or polynomial scaling with respect to the original circuit size.
Solution Approach 2:
The patent introduces a classical computing system as an intermediary to manage and coordinate the execution of quantum subcircuits. The classical system handles circuit compilation, resource allocation, and result aggregation, allowing complex quantum circuits to be processed through multiple simpler steps rather than requiring a single large-scale simulation.
3Productivity
If quantum circuits are executed on available hardware, then the execution can proceed, but the circuit may need to wait for resource availability
Solution Approach 1:
The patent compiles quantum circuits into multiple subcircuits that can be executed independently and in parallel on available quantum hardware. This segmentation allows the system to utilize hardware resources more efficiently by distributing subcircuits across multiple execution slots, reducing the waiting time for resource availability and increasing overall execution throughput.
Solution Approach 2:
The patent performs preliminary circuit compilation and optimization into subcircuits before execution, and pre-allocates or queues execution tasks based on predicted hardware availability. This preliminary preparation reduces idle waiting time by having circuits ready to execute immediately when resources become available.
4Reliability
If large quantum circuits are executed directly, then the computation completeness is maintained, but the resource requirements become prohibitive
Solution Approach 1:
The patent divides large quantum circuits into smaller subcircuits that can be executed with available quantum resources. By maintaining the logical structure and dependencies between subcircuits, and using classical systems to coordinate execution and aggregate results, the patent ensures computation completeness while reducing resource requirements to manageable levels.
Solution Approach 2:
The patent employs a classical computing system as an intermediary to manage the execution of quantum subcircuits. This classical mediator handles resource allocation, coordinates subcircuit execution, and aggregates results, enabling large quantum circuits to be processed with limited quantum resources while maintaining overall computation integrity and completeness.
Data Source
AI summary
Dynamic orchestration of quantum circuit execution. A runtime prediction is performed on a quantum circuit to determine or estimate an amount of resources and execution time that are needed to execute the quantum circuit. The runtime prediction may also estimate the resources, time, and other factors associated with cutting the quantum circuit. When cutting the circuit is beneficial, the quantum subcircuits generated by cutting the quantum circuit are subject to runtime prediction. This information generated by the runtime prediction, along with telemetry data from computing and quantum resources and service level objectives, is used to generate an execution plan for performing or executing the quantum circuit or the quantum subcircuits when the quantum circuit is cut.