{"id":31382,"date":"2024-12-16T17:36:00","date_gmt":"2024-12-16T09:36:00","guid":{"rendered":"https:\/\/www.ime.ntnu.edu.tw\/?p=31382"},"modified":"2024-12-16T17:36:02","modified_gmt":"2024-12-16T09:36:02","slug":"2024-12-16","status":"publish","type":"post","link":"https:\/\/www.ime.ntnu.edu.tw\/index.php\/2024\/12\/16\/2024-12-16\/","title":{"rendered":"\u6d3b\u52d5\u8a0a\u606f\uff1a12\/20(\u4e94)Scalability enhancement of quantum computing under limited connectivity through distributed quantum computing\u00a0[1]\u00a0(Jun-Yi Wu)"},"content":{"rendered":"\n

Time\uff1aFriday,\u00a020\u00a015:00~17:00 December 2024\u00a0<\/strong><\/p>\n\n\n\n

Venue\uff1aF102<\/strong><\/p>\n\n\n\n

Abstract:
We employ quantum-volume random-circuit sampling to benchmark the performance of entanglement-assisted distributed quantum computing (DQC) with two quantum processing units (QPUs) and provide a comparative analysis with single-QPU quantum computing. Initially, a single-qubit depolarizing noise model is introduced within the random circuit framework, upon which a precise correspondence is established among three critical performance metrics: average gate fidelity, heavy output probability, and linear cross-entropy. An analytical approximation for average gate fidelity under this noise model is derived and demonstrated to align closely with numerical simulations. This approximation is obtained using a noise propagation matrix constructed from the extended connectivity graph of a DQC device. Numerical simulations indicate a scalability advantage for DQC in QPUs with constrained connectivity, enabled through the use of noisy entanglement. The proposed methodology provides a method for determining the noise threshold of entanglement required to enhance scalability in entanglement-assisted DQC configurations.<\/p>\n\n\n\n

[1] S.-H. Hu, G. Biswas, and J.-Y. Wu*, arXiv:2405.10942 (2024)<\/p>\n\n\n\n

\"\"<\/figure>\n","protected":false},"excerpt":{"rendered":"

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