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OnePerc: A Randomness-aware Compiler for Photonic Quantum Computing

International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)(2024)CCF A

University of California San Diego | Cisco Systems

Cited 0|Views53
Abstract
The photonic platform holds great promise for quantum computing.Nevertheless, the intrinsic probabilistic characteristics of its native fusionoperations introduces substantial randomness into the computing process, posingsignificant challenges to achieving scalability and efficiency in programexecution. In this paper, we introduce a randomness-aware compilation frameworkdesigned to concurrently achieve scalability and efficiency. Our approachleverages an innovative combination of offline and online optimization passes,with a novel intermediate representation serving as a crucial bridge betweenthem. Through a comprehensive evaluation, we demonstrate that this frameworksignificantly outperforms the most efficient baseline compiler in a scalablemanner, opening up new possibilities for realizing scalable photonic quantumcomputing.
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Photonic Reservoir Computing,Fault-tolerant Quantum Computation,Quantum Computation,Neuromorphic Photonics,Quantum Simulation
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要点】:本文提出了一种使用力控连续机器人进行半自动器官探测与配准的方法,以实现手术过程中器官几何形态的准确对应,解决了器官变形和移位的问题。

方法】:研究采用混合反馈控制法,结合关节级别和末端执行器的位置测量,满足参考运动轨迹,并通过磁跟踪和力感测输入实现混合力/位置控制。

实验】:实验在IREP(单端口接入手术系统)上进行验证,结果显示即使器官发生变形,也可以通过实施连续点漂移注册,使用力控探测数据对手术计划进行变形配准。