Quantum Circuit Synthesis with CSP for Hardware-Constrained Gate Mapping
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Solution Overview
Problem
Existing quantum programming methods face challenges in efficiently translating functional-level quantum programs into gate-level representations that optimize resource utilization and adhere to hardware constraints, leading to suboptimal performance and execution on quantum computers.
Innovation Solution
A functional-level processing component is introduced to generate a gate-level representation of quantum circuits by solving a Constraint Satisfaction Problem (CSP) based on the functional-level representation, considering hardware and user constraints to select optimal implementations for functional blocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If existing quantum programming methods are used to translate functional-level quantum programs into gate-level representations, then the translation process is simple, but the resource utilization is suboptimal and hardware constraints are not adequately adhered to
Solution Approach 1:
The patent introduces an intermediary component called a functional-level processing component that acts as a mediator between the functional-level quantum program and the gate-level representation. This component formulates and solves constraint satisfaction problems (CSPs) to optimize resource utilization while translating the program, thereby resolving the contradiction between translation simplicity and resource efficiency.
Solution Approach 2:
The patent applies preliminary action by formulating constraint satisfaction problems and determining optimal implementations of functional blocks before generating the final gate-level representation. This preliminary optimization step ensures that resource constraints are satisfied and resource utilization is maximized before the actual translation to gate-level code occurs.
2Ease of operation
If existing quantum programming methods are used to translate functional-level quantum programs into gate-level representations, then the implementation is straightforward, but the execution efficiency and fidelity on quantum computers are suboptimal
Solution Approach 1:
The functional-level processing component serves as an intermediary that enhances execution efficiency without complicating the overall implementation. It automatically formulates and solves CSPs to determine optimal gate-level implementations that maximize fidelity and efficiency, while the user interface remains simple and straightforward.
Solution Approach 2:
The system applies self-service by automatically optimizing its own translation process through CSP formulation and solving. The functional-level processing component independently determines optimal implementations of functional blocks based on hardware constraints and performance metrics, without requiring manual intervention, thereby maintaining ease of operation while improving reliability.
3Productivity
If auxiliary qubits are used to store temporarily computed values, then the quantum circuit can perform computations, but the number of available qubits is limited and synthesis must find circuits that satisfy the number of available qubits
Solution Approach 1:
The patent applies parameter changes by formulating CSPs that explicitly model and optimize the number of auxiliary qubits required for each functional block implementation. The system evaluates multiple possible implementations with different auxiliary qubit requirements and selects the optimal configuration that satisfies the limited available qubits while maintaining computation capability.
Solution Approach 2:
The patent applies local quality by optimizing the auxiliary qubit usage at the level of individual functional blocks. The CSP formulation allows different parts of the circuit (functional blocks) to have different auxiliary qubit requirements based on their specific computational needs, enabling efficient local resource allocation that maximizes overall circuit performance within global qubit constraints.
Data Source
AI summary
A method, system and product for synthesizing a quantum circuit using Constraint Satisfaction Problem (CSP). A functional-level representation of a quantum circuit that includes a first functional blocks and a second functional block is obtained. The functional-level representation defines a relationship between the first functional block and the second functional block. A CSP that is determined based on the functional-level representation, is automatically solved. The CSP is solved by identifying a first and second implementations to the first and second functional blocks that adhere to the CSP. A gate-level representation of the quantum circuit is synthesized using the first and second implementations.