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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.00822 |
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| _version_ | 1866910853971836928 |
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| author | Reichental, Israel Alon, Ravid Preminger, Lior Vax, Matan Naveh, Amir |
| author_facet | Reichental, Israel Alon, Ravid Preminger, Lior Vax, Matan Naveh, Amir |
| contents | As quantum computing technology advances, the complexity of quantum algorithms increases, necessitating a shift from low-level circuit descriptions to high-level programming paradigms. This paper addresses the challenges of developing a compilation algorithm that optimizes memory management and scales well for bigger, more complex circuits. Our approach models the high-level quantum code as a control flow graph and presents a workflow that searches for a topological sort that maximizes opportunities for qubit reuse. Various heuristics for qubit reuse strategies handle the trade-off between circuit width and depth. We also explore scalability issues in large circuits, suggesting methods to mitigate compilation bottlenecks. By analyzing the structure of the circuit, we are able to identify sub-problems that can be solved separately, without a significant effect on circuit quality, while reducing runtime significantly. This method lays the groundwork for future advancements in quantum programming and compiler optimization by incorporating scalability into quantum memory management. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_00822 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Scalable Memory Recycling for Large Quantum Programs Reichental, Israel Alon, Ravid Preminger, Lior Vax, Matan Naveh, Amir Quantum Physics Programming Languages As quantum computing technology advances, the complexity of quantum algorithms increases, necessitating a shift from low-level circuit descriptions to high-level programming paradigms. This paper addresses the challenges of developing a compilation algorithm that optimizes memory management and scales well for bigger, more complex circuits. Our approach models the high-level quantum code as a control flow graph and presents a workflow that searches for a topological sort that maximizes opportunities for qubit reuse. Various heuristics for qubit reuse strategies handle the trade-off between circuit width and depth. We also explore scalability issues in large circuits, suggesting methods to mitigate compilation bottlenecks. By analyzing the structure of the circuit, we are able to identify sub-problems that can be solved separately, without a significant effect on circuit quality, while reducing runtime significantly. This method lays the groundwork for future advancements in quantum programming and compiler optimization by incorporating scalability into quantum memory management. |
| title | Scalable Memory Recycling for Large Quantum Programs |
| topic | Quantum Physics Programming Languages |
| url | https://arxiv.org/abs/2503.00822 |