تقرير
XGSwap: eXtreme Gradient boosting Swap for Routing in NISQ Devices
| العنوان: | XGSwap: eXtreme Gradient boosting Swap for Routing in NISQ Devices |
|---|---|
| المؤلفون: | Waring, Jean-Baptiste, Pere, Christophe, Beux, Sébastien Le |
| سنة النشر: | 2024 |
| المجموعة: | Quantum Physics |
| مصطلحات موضوعية: | Quantum Physics, 81P68 |
| الوصف: | In the current landscape of noisy intermediate-scale quantum (NISQ) computing, the inherent noise presents significant challenges to achieving high-fidelity long-range entanglement. Furthermore, this challenge is amplified by the limited connectivity of current superconducting devices, necessitating state permutations to establish long-distance entanglement. Traditionally, graph methods are used to satisfy the coupling constraints of a given architecture by routing states along the shortest undirected path between qubits. In this work, we introduce a gradient boosting machine learning model to predict the fidelity of alternative--potentially longer--routing paths to improve fidelity. This model was trained on 4050 random CNOT gates ranging in length from 2 to 100+ qubits. The experiments were all executed on ibm_quebec, a 127-qubit IBM Quantum System One. Through more than 200+ tests run on actual hardware, our model successfully identified higher fidelity paths in approximately 23% of cases. Comment: 7 pages, 11 figures, 3 tables. Submitted to QCE24 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2404.17982 |
| رقم الأكسشن: | edsarx.2404.17982 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |