{"title":"数字量子计算机的经典架构","authors":"Fang Zhang, Xing Zhu, Rui Chao, Cupjin Huang, Linghang Kong, Guoyang Chen, Dawei Ding, Haishan Feng, Yihuai Gao, Xiaotong Ni, Liwei Qiu, Zhe Wei, Yueming Yang, Yang Zhao, Yaoyun Shi, Weifeng Zhang, Peng Zhou, Jianxin Chen","doi":"10.1145/3626199","DOIUrl":null,"url":null,"abstract":"Scaling bottlenecks the making of digital quantum computers, posing challenges from both the quantum and the classical components. We present a classical architecture to cope with a comprehensive list of the latter challenges all at once , and implement it fully in an end-to-end system by integrating a multi-core RISC-V CPU with our in-house control electronics. Our architecture enables scalable, high-precision control of large quantum processors and accommodates evolving requirements of quantum hardware. A central feature is a microarchitecture executing quantum operations in parallel on arbitrary predefined qubit groups. Another key feature is a reconfigurable quantum instruction set that supports easy qubit re-grouping and instructions extensions. As a demonstration, we implement the surface code quantum computing workflow. Our design, for the first time, reduces instruction issuing and transmission costs to constants, which do not scale with the number of qubits, without adding any overheads in decoding or dispatching. Our system uses a dedicated general-purpose CPU for both qubit control and classical computation, including syndrome decoding. Implementing recent theoretical proposals as decoding firmware that parallelizes general inner decoders, we can achieve unprecedented decoding capabilities of up to distances 47 and 67 with the currently available systems-on-chips for physical error rate p = 0.001 and p = 0.0001, respectively, all in just 1 µs.","PeriodicalId":474832,"journal":{"name":"ACM transactions on quantum computing","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Classical Architecture For Digital Quantum Computers\",\"authors\":\"Fang Zhang, Xing Zhu, Rui Chao, Cupjin Huang, Linghang Kong, Guoyang Chen, Dawei Ding, Haishan Feng, Yihuai Gao, Xiaotong Ni, Liwei Qiu, Zhe Wei, Yueming Yang, Yang Zhao, Yaoyun Shi, Weifeng Zhang, Peng Zhou, Jianxin Chen\",\"doi\":\"10.1145/3626199\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Scaling bottlenecks the making of digital quantum computers, posing challenges from both the quantum and the classical components. We present a classical architecture to cope with a comprehensive list of the latter challenges all at once , and implement it fully in an end-to-end system by integrating a multi-core RISC-V CPU with our in-house control electronics. Our architecture enables scalable, high-precision control of large quantum processors and accommodates evolving requirements of quantum hardware. A central feature is a microarchitecture executing quantum operations in parallel on arbitrary predefined qubit groups. Another key feature is a reconfigurable quantum instruction set that supports easy qubit re-grouping and instructions extensions. As a demonstration, we implement the surface code quantum computing workflow. Our design, for the first time, reduces instruction issuing and transmission costs to constants, which do not scale with the number of qubits, without adding any overheads in decoding or dispatching. Our system uses a dedicated general-purpose CPU for both qubit control and classical computation, including syndrome decoding. Implementing recent theoretical proposals as decoding firmware that parallelizes general inner decoders, we can achieve unprecedented decoding capabilities of up to distances 47 and 67 with the currently available systems-on-chips for physical error rate p = 0.001 and p = 0.0001, respectively, all in just 1 µs.\",\"PeriodicalId\":474832,\"journal\":{\"name\":\"ACM transactions on quantum computing\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM transactions on quantum computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3626199\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM transactions on quantum computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3626199","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Classical Architecture For Digital Quantum Computers
Scaling bottlenecks the making of digital quantum computers, posing challenges from both the quantum and the classical components. We present a classical architecture to cope with a comprehensive list of the latter challenges all at once , and implement it fully in an end-to-end system by integrating a multi-core RISC-V CPU with our in-house control electronics. Our architecture enables scalable, high-precision control of large quantum processors and accommodates evolving requirements of quantum hardware. A central feature is a microarchitecture executing quantum operations in parallel on arbitrary predefined qubit groups. Another key feature is a reconfigurable quantum instruction set that supports easy qubit re-grouping and instructions extensions. As a demonstration, we implement the surface code quantum computing workflow. Our design, for the first time, reduces instruction issuing and transmission costs to constants, which do not scale with the number of qubits, without adding any overheads in decoding or dispatching. Our system uses a dedicated general-purpose CPU for both qubit control and classical computation, including syndrome decoding. Implementing recent theoretical proposals as decoding firmware that parallelizes general inner decoders, we can achieve unprecedented decoding capabilities of up to distances 47 and 67 with the currently available systems-on-chips for physical error rate p = 0.001 and p = 0.0001, respectively, all in just 1 µs.