Key ingredients for manufacturing superconducting quantum processors at scale

Thorsten Last, M. Mongillo, T. Ivanov, Adriaan Rol, A. Lawrence, G. Alberts, D. Wan, A. Potočnik, K. De Greve
{"title":"Key ingredients for manufacturing superconducting quantum processors at scale","authors":"Thorsten Last, M. Mongillo, T. Ivanov, Adriaan Rol, A. Lawrence, G. Alberts, D. Wan, A. Potočnik, K. De Greve","doi":"10.1117/12.2657319","DOIUrl":null,"url":null,"abstract":"Computational ecosystems in which classical supercomputers and general-purpose quantum computers provide a steady increase in value-creating computation capabilities have shown immense progress in recent years. Superconducting qubit technology, in particular, has emerged as a leading candidate for realizing a scalable quantum computing platform ready for paving the way to commercial quantum advantage. However, current academic approaches in fabrication and testing of quantum devices are not scalable and have already started to limit the rapid development of the field. Novel solutions are required to tackle the combined challenge of increasing the qubit count on a quantum processor and the need to further reduce the qubit’s error rates. This, in turn, will lead to a renewed acceleration in qubit manufacturing, test and diagnostics. Here we present aspects of how to move superconducting qubit manufacturing and testing from small-scale laboratory to large-scale fabrication facility environments. To enable this transfer, two key ingredients are demonstrated: (i) A foundry-compatible fabrication process of superconducting qubits that can benefit from the advanced process control in industry-scale CMOS fabrication facilities, and (ii) an acceleration of testing and cryogenic measurement throughput by using a milli-Kelvin cryo-CMOS signal multiplexer operating in near proximity to quantum devices and integrated qubit diagnostic and benchmarking tools with end-to-end data analytics. Although some of these elements have been explored independently, co-development is crucial to enable an efficient scalable development cycle for quantum computing technology. A full development cycle consisting of scalable manufacturing, testing, and benchmarking will enable the large-scale fabrication and control of quantum computing devices and thus pave the way to commercial quantum advantage.","PeriodicalId":212235,"journal":{"name":"Advanced Lithography","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Lithography","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2657319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Computational ecosystems in which classical supercomputers and general-purpose quantum computers provide a steady increase in value-creating computation capabilities have shown immense progress in recent years. Superconducting qubit technology, in particular, has emerged as a leading candidate for realizing a scalable quantum computing platform ready for paving the way to commercial quantum advantage. However, current academic approaches in fabrication and testing of quantum devices are not scalable and have already started to limit the rapid development of the field. Novel solutions are required to tackle the combined challenge of increasing the qubit count on a quantum processor and the need to further reduce the qubit’s error rates. This, in turn, will lead to a renewed acceleration in qubit manufacturing, test and diagnostics. Here we present aspects of how to move superconducting qubit manufacturing and testing from small-scale laboratory to large-scale fabrication facility environments. To enable this transfer, two key ingredients are demonstrated: (i) A foundry-compatible fabrication process of superconducting qubits that can benefit from the advanced process control in industry-scale CMOS fabrication facilities, and (ii) an acceleration of testing and cryogenic measurement throughput by using a milli-Kelvin cryo-CMOS signal multiplexer operating in near proximity to quantum devices and integrated qubit diagnostic and benchmarking tools with end-to-end data analytics. Although some of these elements have been explored independently, co-development is crucial to enable an efficient scalable development cycle for quantum computing technology. A full development cycle consisting of scalable manufacturing, testing, and benchmarking will enable the large-scale fabrication and control of quantum computing devices and thus pave the way to commercial quantum advantage.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
大规模制造超导量子处理器的关键要素
近年来,经典超级计算机和通用量子计算机提供了稳定增长的价值创造计算能力的计算生态系统取得了巨大进展。特别是超导量子比特技术,已经成为实现可扩展量子计算平台的主要候选者,为商业量子优势铺平了道路。然而,目前量子器件的制造和测试的学术方法是不可扩展的,并且已经开始限制该领域的快速发展。需要新颖的解决方案来应对增加量子处理器上的量子比特计数和进一步降低量子比特错误率的双重挑战。反过来,这将导致量子比特制造、测试和诊断的重新加速。在这里,我们介绍了如何将超导量子比特的制造和测试从小规模实验室转移到大规模制造设施环境的各个方面。为了实现这种转移,展示了两个关键要素:(i)超导量子比特的铸造厂兼容制造工艺,可以受益于工业规模CMOS制造设施的先进过程控制;(ii)通过使用靠近量子设备的毫开尔文低温CMOS信号多路复用器,以及集成的量子比特诊断和基准测试工具,加速测试和低温测量吞吐量,端到端数据分析。虽然其中一些元素已经独立探索,但共同开发对于实现量子计算技术的高效可扩展开发周期至关重要。由可扩展的制造、测试和基准测试组成的完整开发周期将使量子计算设备的大规模制造和控制成为可能,从而为商业量子优势铺平道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Considerations in the design of photoacid generators Predicting the critical features of the chemically-amplified resist profile based on machine learning Application of double exposure technique in plasmonic lithography The damage control of sub layer while ion-driven etching with vertical carbon profile implemented Ultra-high carbon fullerene-based spin-on-carbon hardmasks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1