Quantum Program Compilation via CSP Node Scheduling
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Solution Overview
Problem
The existing compilation process for quantum programs is inefficient in resource utilization, leading to suboptimal execution times and increased resource consumption on quantum execution platforms, as it does not effectively optimize the use of qubits and gates, and the current library of implementations does not always prioritize resource allocation efficiently.
Innovation Solution
The approach involves generating and utilizing quantum program implementations in different granularity levels, such as gate-level, partial DAG, and DAG levels, allowing the CSP solver to iteratively select and schedule node implementations that optimize resource sharing and utilization, thereby reducing the overall resource consumption of quantum circuits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the existing compilation process is used for quantum programs, then the compilation can be completed, but resource utilization is inefficient leading to increased resource consumption and suboptimal execution times
Solution Approach 1:
The patent applies parameter changes by transforming the compilation problem into a Constraint Satisfaction Problem (CSP) model where parameters such as qubit allocation, gate scheduling, and resource allocation are optimized through systematic variation and selection of valid parameter combinations that satisfy quantum hardware constraints and minimize resource consumption
Solution Approach 2:
The patent implements dynamics by enabling flexible and adaptive resource allocation through the CSP solver, which dynamically adjusts qubit assignments, gate scheduling, and auxiliary qubit sharing based on the specific quantum program being compiled and the target quantum hardware capabilities, rather than using static allocation methods
2Reliability
If the current library of implementations is used, then quantum programs can be executed, but resource allocation is not optimized efficiently
Solution Approach 1:
The patent applies universality by creating a unified CSP-based compilation framework that handles multiple quantum operations, resource allocation scenarios, and optimization objectives through a single systematic approach, making the system adaptable to various quantum hardware platforms and program types without requiring separate specialized routines for each case
3Loss of energy
If nodes in the quantum program do not share auxiliary qubits, then the implementation is simpler, but resource consumption increases
Solution Approach 1:
The patent applies merging by combining the scheduling of auxiliary qubits across multiple nodes in the quantum program into a unified CSP model, allowing the solver to identify opportunities where auxiliary qubits can be shared between nodes, thereby reducing total qubit consumption while managing the increased scheduling complexity through systematic constraint handling
Data Source
AI summary
A method, apparatus and product comprising: obtaining a Directed Cycle Graph (DAG) representation of a quantum program, the DAG representation comprises at least one non-executable node that represents a functionality in a high-level representation; generating a Constraint Satisfaction Problem (CSP) model of the DAG representation; generating a partial DAG representation of the quantum program based on the DAG representation, the partial DAG representation comprising at least a first executable node and a second non-executable node, said generating comprising selecting the first executable node and the second non-executable node as implementations of the at least one non-executable node; and synthesizing the quantum program based on the partial DAG representation.