Quantum Circuit Compilation Adaptability Optimization
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Solution Overview
Problem
Existing methods cannot compile any quantum circuit on any quantum processor and lack the ability to optimize quantum circuits using multiple optimization metrics in a flexible and adaptable manner.
Innovation Solution
A method that selects parameters such as the quantum circuit, processor, optimization metric, and heuristic or metaheuristic to compile and optimize quantum circuits, ensuring adaptability and effectiveness by transforming circuits into optimal subcircuits with executable quantum gates and minimizing permutation doors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing compilation methods are used, then the quantum circuit can be compiled on specific quantum processors, but the method cannot compile any quantum circuit on any quantum processor and lacks adaptability
Solution Approach 1:
The patent implements a universal compilation framework that can handle any quantum circuit on any quantum processor by introducing configurable parameter selection mechanisms. The system selects from multiple quantum circuit representations, processor models, optimization metrics, and heuristic algorithms to adapt to different compilation scenarios, making the method universally applicable across diverse quantum hardware platforms.
Solution Approach 2:
The patent employs dynamic parameter selection during the compilation process, allowing the system to adjust optimization metrics and heuristic algorithms based on the specific quantum circuit and target processor characteristics. This dynamic adaptation enables the compilation method to optimize for different criteria (e.g., gate count, circuit depth, permutation operations) depending on the runtime requirements and hardware constraints.
2Quantity of substance
If optimization is performed to reduce quantum gates, then the circuit size is reduced, but the number of permutation operations between qubits increases
Solution Approach 1:
The patent introduces multiple optimization metrics that can be selected and weighted differently based on compilation requirements. The system can optimize for gate count reduction while simultaneously constraining permutation operations, or adjust the balance between these competing objectives through configurable parameters. This multi-metric approach allows flexible trade-off management between circuit size and operational efficiency.
Solution Approach 2:
The patent implements an iterative optimization process with feedback mechanisms that evaluate the quantum circuit against multiple metrics simultaneously. The compilation system monitors both gate count and permutation operations throughout the optimization process, using feedback from metric evaluations to guide subsequent optimization steps and adjust the transformation strategy to achieve balanced optimization results.
3Ease of operation
If a fixed optimization method is used, then the compilation process is simple, but the method cannot be stopped mid-process without losing optimization progress (not an 'anytime' method)
Solution Approach 1:
The patent structures the compilation process into discrete, independently evaluatable stages with intermediate optimization checkpoints. Each stage produces a valid quantum circuit that can be evaluated against optimization metrics, allowing the process to be interrupted at any point while preserving the optimization progress achieved up to that stage. The system maintains optimization state information that can be resumed or abandoned without loss.
Data Source
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AI summary
A method for developing a compilation process for a quantum circuit on a quantum processor includes: - an implementation step of the compilation process comprising: * an iteration loop comprising successively: ° a simulation step of a given implementation of the logical qubits on the physical qubits of the quantum processor, ° a detection step, in the quantum circuit, of inefficient quantum gates, ° a step of estimating the number of permutation quantum gates to be inserted into the quantum circuit so that all the quantum gates of the quantum circuit are effective, ° a feedback step, via a simulated annealing, leading to a new simulation step, until reaching, when all the quantum gates are effective: ¤ either a minimum threshold of the estimated number of permutation quantum gates of value between two physical qubits, ¤ or a maximum threshold of iterations in the loop.