Qimax: Efficient quantum simulation via GPU-accelerated extended stabilizer formalism
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866913131202084864 |
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| author | Hai, Vu Tuan Doanh, Bui Cao Duong, Le Vu Trung Luan, Pham Hoai Nakashima, Yasuhiko |
| author_facet | Hai, Vu Tuan Doanh, Bui Cao Duong, Le Vu Trung Luan, Pham Hoai Nakashima, Yasuhiko |
| contents | Simulating Clifford and near-Clifford circuits using the extended stabilizer formalism has become increasingly popular, particularly in quantum error correction. Compared to the state-vector approach, the extended stabilizer formalism can solve the same problems with fewer computational resources, as it operates on stabilizers rather than full state vectors. Most existing studies on near-Clifford circuits focus on balancing the trade-off between the number of ancilla qubits and simulation accuracy, often overlooking performance considerations. Furthermore, in the presence of high-rank stabilizers, performance is limited by the sequential property of the stabilizer formalism. In this work, we introduce a parallelized version of the extended stabilizer formalism, enabling efficient execution on multi-core devices such as GPU. Experimental results demonstrate that, in certain scenarios, our Python-based implementation outperforms state-of-the-art simulators such as Qiskit and Pennylane. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_03307 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Qimax: Efficient quantum simulation via GPU-accelerated extended stabilizer formalism Hai, Vu Tuan Doanh, Bui Cao Duong, Le Vu Trung Luan, Pham Hoai Nakashima, Yasuhiko Quantum Physics Software Engineering Simulating Clifford and near-Clifford circuits using the extended stabilizer formalism has become increasingly popular, particularly in quantum error correction. Compared to the state-vector approach, the extended stabilizer formalism can solve the same problems with fewer computational resources, as it operates on stabilizers rather than full state vectors. Most existing studies on near-Clifford circuits focus on balancing the trade-off between the number of ancilla qubits and simulation accuracy, often overlooking performance considerations. Furthermore, in the presence of high-rank stabilizers, performance is limited by the sequential property of the stabilizer formalism. In this work, we introduce a parallelized version of the extended stabilizer formalism, enabling efficient execution on multi-core devices such as GPU. Experimental results demonstrate that, in certain scenarios, our Python-based implementation outperforms state-of-the-art simulators such as Qiskit and Pennylane. |
| title | Qimax: Efficient quantum simulation via GPU-accelerated extended stabilizer formalism |
| topic | Quantum Physics Software Engineering |
| url | https://arxiv.org/abs/2505.03307 |