Quantum Circuit Optimization via Concurrent Sequence Evaluation
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Solution Overview
Problem
Current quantum circuit optimization methods struggle to efficiently reduce the gate count and depth of quantum circuits, and the order of optimization passes can significantly impact performance, especially as quantum devices grow in size.
Innovation Solution
A system and method that concurrently execute different quantum circuit optimization sequences on multiple copies of a quantum circuit, identifying the sequences that generate output quantum circuits with defined criteria, and employing a trained model to recommend optimal optimization sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If quantum circuit optimization sequences are executed sequentially on single copies, then resource consumption is low, but processing time and workload are excessive
Solution Approach 1:
The patent segments the optimization process by creating multiple copies of the quantum circuit and distributing different optimization sequences to different copies. This allows parallel processing of optimization tasks, significantly reducing the time required to evaluate multiple optimization sequences while maintaining manageable resource consumption through distributed computation.
Solution Approach 2:
The system performs preliminary actions by generating multiple copies of the quantum circuit before optimization evaluation. These pre-prepared copies enable concurrent execution of different optimization sequences, eliminating the need for sequential processing and reducing overall processing time without proportionally increasing resource demands.
2Loss of time
If multiple optimization sequences are evaluated sequentially, then resource consumption is manageable, but the time to identify optimal sequences is excessive
Solution Approach 1:
The patent creates multiple copies of the quantum circuit to enable parallel evaluation of different optimization sequences. This copying approach allows simultaneous execution of multiple optimization paths, dramatically reducing the time required to identify optimal sequences while the system manages complexity through standardized copy generation and comparison protocols.
3Productivity
If concurrent execution of optimization sequences is implemented, then processing efficiency improves, but system complexity increases
Solution Approach 1:
The patent merges the results from multiple concurrent optimization sequences through a unified evaluation process. The system combines outputs from different optimization paths, compares them against defined criteria, and identifies the best performing sequence. This merging approach maintains high productivity while managing complexity through centralized result aggregation and comparison logic.
Solution Approach 2:
The system implements feedback mechanisms by evaluating optimization results against defined criteria and using this information to identify optimal sequences. The feedback loop compares performance metrics from concurrent executions and selects the best optimization approach, enabling efficient decision-making despite the complexity of managing multiple concurrent processes.
Data Source
AI summary
Systems, computer-implemented methods, and computer program products to facilitate evaluation of quantum circuit optimization routines and knowledge base generation are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise a compilation component that concurrently executes different quantum circuit optimization sequences on multiple copies of a quantum circuit. The computer executable components can further comprise an identification component that identifies at least one of the different quantum circuit optimization sequences that generates an output quantum circuit comprising defined criteria.