ArtA: Automating Design Space Exploration of Spin Qubit Architectures

• URL: http://arxiv.org/abs/2407.18151v2
• Date: Wed, 31 Jul 2024 17:28:19 GMT
• Title: ArtA: Automating Design Space Exploration of Spin Qubit Architectures
• Authors: Nikiforos Paraskevopoulos, David Hamel, Aritra Sarkar, Carmen G. Almudever, Sebastian Feld,
• Abstract summary: This paper introduces the first Design Space Exploration (DSE) for quantum-dot spin-qubit architectures. ArtA can leverage 17 optimization configurations, significantly reducing exploration times by up to 99.1%. Our work demonstrates that the synergy between DSE methodologies and optimization algorithms can effectively be deployed to provide useful suggestions to quantum processor designers.
• Score: 1.1528488253382057
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: In the fast-paced field of quantum computing, identifying the architectural characteristics that will enable quantum processors to achieve high performance across a diverse range of quantum algorithms continues to pose a significant challenge. Given the extensive and costly nature of experimentally testing different designs, this paper introduces the first Design Space Exploration (DSE) for quantum-dot spin-qubit architectures. Utilizing the upgraded SpinQ compilation framework, this study explores a substantial design space comprising 29,312 spin-qubit-based architectures and applies an innovative optimization tool, ArtA (Artificial Architect), to speed up the design space traversal. ArtA can leverage 17 optimization configurations, significantly reducing exploration times by up to 99.1% compared to a traditional brute force approach while maintaining the same result quality. After a comprehensive evaluation of best-matching optimization configurations per quantum circuit, ArtA suggests specific and universal architectural features that provide optimal performance across the examined circuits. Our work demonstrates that the synergy between DSE methodologies and optimization algorithms can effectively be deployed to provide useful suggestions to quantum processor designers.

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