Profiling quantum circuits for their efficient execution on single- and multi-core architectures
- URL: http://arxiv.org/abs/2407.12640v1
- Date: Wed, 17 Jul 2024 15:08:50 GMT
- Title: Profiling quantum circuits for their efficient execution on single- and multi-core architectures
- Authors: Medina Bandic, Pablo le Henaff, Anabel Ovide, Pau Escofet, Sahar Ben Rached, Santiago Rodrigo, Hans van Someren, Sergi Abadal, Eduard Alarcon, Carmen G. Almudever, Sebastian Feld,
- Abstract summary: This study introduces graph theory-based metrics extracted from their qubit interaction graph and gate dependency graph.
It uncovers a connection between parameters rooted in both qubit interaction and gate dependency graphs, and the performance metrics for quantum circuit mapping.
- Score: 1.7340157845783293
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Application-specific quantum computers offer the most efficient means to tackle problems intractable by classical computers. Realizing these architectures necessitates a deep understanding of quantum circuit properties and their relationship to execution outcomes on quantum devices. Our study aims to perform for the first time a rigorous examination of quantum circuits by introducing graph theory-based metrics extracted from their qubit interaction graph and gate dependency graph alongside conventional parameters describing the circuit itself. This methodology facilitates a comprehensive analysis and clustering of quantum circuits. Furthermore, it uncovers a connection between parameters rooted in both qubit interaction and gate dependency graphs, and the performance metrics for quantum circuit mapping, across a range of established quantum device and mapping configurations. Among the various device configurations, we particularly emphasize modular (i.e., multi-core) quantum computing architectures due to their high potential as a viable solution for quantum device scalability. This thorough analysis will help us to: i) identify key attributes of quantum circuits that affect the quantum circuit mapping performance metrics; ii) predict the performance on a specific chip for similar circuit structures; iii) determine preferable combinations of mapping techniques and hardware setups for specific circuits; and iv) define representative benchmark sets by clustering similarly structured circuits.
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