| SPECIAL TOPIC — Quantum computing and quantum sensing |
Prev
Next
|
|
|
M2CS: A microwave measurement and control system for large-scale superconducting quantum processors |
| Jiawei Zhang(张家蔚)1,2,3,†, Xuandong Sun(孙炫东)1,2,3,4,†, Zechen Guo(郭泽臣)1,2,3, Yuefeng Yuan(袁跃峰)2, Yubin Zhang(张玉斌)2, Ji Chu(储继)2, Wenhui Huang(黄文辉)1,2,3, Yongqi Liang(梁咏棋)1,2,3, Jiawei Qiu(邱嘉威)1,2,3, Daxiong Sun(孙大雄)1,2,3, Ziyu Tao(陶子予)2, Jiajian Zhang(张家健)1,2,3,4, Weijie Guo(郭伟杰)2, Ji Jiang(蒋骥)1,2,3, Xiayu Linpeng(林彭夏雨)2, Yang Liu(刘阳)2, Wenhui Ren(任文慧)2, Jingjing Niu(牛晶晶)2,5, Youpeng Zhong(钟有鹏)1,2,3,5,‡, and Dapeng Yu(俞大鹏)1,2,3,4,5 |
1 Shenzhen Institute for Quantum Science and Engineering, Southern University of Science and Technology, Shenzhen 518048, China;
2 Department of Physics, Southern University of Science and Technology, Shenzhen 518048, China;
3 International Quantum Academy, Shenzhen 518048, China;
4 Guangdong Provincial Key Laboratory of Quantum Science and Engineering, Southern University of Science and Technology, Shenzhen 518048, China;
5 Shenzhen Branch, Hefei National Laboratory, Shenzhen 518048, China |
|
|
|
|
Abstract As superconducting quantum computing continues to advance at an unprecedented pace, there is a compelling demand for the innovation of specialized electronic instruments that act as crucial conduits between quantum processors and host computers. Here, we introduce a microwave measurement and control system (M$^{2}$CS) dedicated to large-scale superconducting quantum processors. M$^{2}$CS features a compact modular design that balances overall performance, scalability and flexibility. Electronic tests of M$^{2}$CS show key metrics comparable to commercial instruments. Benchmark tests on transmon superconducting qubits further show qubit coherence and gate fidelities comparable to state-of-the-art results, confirming M$^{2}$CS's capability to meet the stringent requirements of quantum experiments running on intermediate-scale quantum processors. The compact and scalable nature of our design holds the potential to support over 1000 qubits after upgrade in stability and integration. The M$^{2}$CS architecture may also be adopted to a wider range of scenarios, including other quantum computing platforms such as trapped ions and silicon quantum dots, as well as more traditional applications like microwave kinetic inductance detectors and phased array radar systems.
|
Received: 22 August 2024
Revised: 10 October 2024
Accepted manuscript online: 23 October 2024
|
|
PACS:
|
03.67.Lx
|
(Quantum computation architectures and implementations)
|
|
| Fund: This work was supported by the Science, Technology and Innovation Commission of Shenzhen Municipality (Grant Nos. KQTD20210811090049034, RCBS20231211090824040, and RCBS20231211090815032), the National Natural Science Foundation of China (Grant Nos. 12174178, 12204228, 12374474, and 123b2071), the Innovation Program for Quantum Science and Technology (Grant No. 2021ZD0301703), the Shenzhen-Hong Kong Cooperation Zone for Technology and Innovation (Grant No. HZQB-KCZYB-2020050), and Guangdong Basic and Applied Basic Research Foundation (Grant Nos. 2024A1515011714 and 2022A1515110615). |
Corresponding Authors:
Youpeng Zhong
E-mail: zhongyp@sustech.edu.cn
|
Cite this article:
Jiawei Zhang(张家蔚), Xuandong Sun(孙炫东), Zechen Guo(郭泽臣), Yuefeng Yuan(袁跃峰), Yubin Zhang(张玉斌), Ji Chu(储继), Wenhui Huang(黄文辉), Yongqi Liang(梁咏棋), Jiawei Qiu(邱嘉威), Daxiong Sun(孙大雄), Ziyu Tao(陶子予), Jiajian Zhang(张家健), Weijie Guo(郭伟杰), Ji Jiang(蒋骥), Xiayu Linpeng(林彭夏雨), Yang Liu(刘阳), Wenhui Ren(任文慧), Jingjing Niu(牛晶晶), Youpeng Zhong(钟有鹏), and Dapeng Yu(俞大鹏) M2CS: A microwave measurement and control system for large-scale superconducting quantum processors 2024 Chin. Phys. B 33 120309
|
[1] Shor P W 1999 SIAM Review 41 303
[2] Grover L K 1997 Phys. Rev. Lett. 79 4709
[3] Arute F, Arya K, Babbush R, Bacon D, Bardin J C, Barends R, Biswas R, Boixo S, Brandao F G, Buell D A, et al. 2019 Nature 574 505
[4] Wu Y, Bao W S, Cao S, Chen F, Chen M C, Chen X, Chung T H, Deng H, Du Y, Fan D, Gong M, et al. 2021 Phys. Rev. Lett. 127 180501
[5] Kim Y, Eddins A, Anand S, Wei K X, Van Den Berg E, Rosenblatt S, Nayfeh H, Wu Y, Zaletel M, Temme K, et al. 2023 Nature 618 500
[6] Guo X Y, Li S S, Xiao X, Xiang Z C, Ge Z Y, Li H K, Song P T, Peng Y, Wang Z, Xu K, et al. 2023 Chin. Phys. B 32 010307
[7] Zhao C, He Y, Geng X, He K, Dai G, Liu J and Chen W 2023 Chin. Phys. Lett. 40 010301
[8] Xu S, Sun Z Z, Wang K, Xiang L, Bao Z, Zhu Z, Shen F, Song Z, Zhang P, Ren W, Zhang X, Dong H, Deng J, Chen J, Wu Y, Tan Z, et al. 2023 Chin. Phys. Lett. 40 060301
[9] Jin Y X, Xu H Z, Wang Z A, Zhuang W F, Huang K X, Shi Y H, Ma B G, Li T M, Chen C T, Xu K, Feng Y L, Pei-Liu, Chen M, Li S S, Yang Z P, Qian C, et al. 2024 Chin. Phys. B 33 050301
[10] Bao Z, Xu S, Song Z, Wang K, Xiang L, Zhu Z, Chen J, Jin F, Zhu X, Gao Y, Wu Y, Zhang C, Wang N, Zou Y, Tan Z, Zhang A, Cui Z, Shen F, Zhong J, Li T, Deng J, Zhang X, Dong H, Zhang P, Liu Y R, Zhao L, Hao J, Li H, Wang Z, Song C, Guo Q, Huang B and Wang H 2024 arXiv:2401.08284
[11] Castelvecchi D 2023 Nature 624 238
[12] Google Quantum AI 2023 Nature 614 676
[13] Gupta R S, Sundaresan N, Alexander T, Wood C J, Merkel S T, Healy M B, Hillenbrand M, Jochym-O’Connor T, Wootton J R, Yoder T J, Cross A W, Takita M and Brown B J 2024 Nature 625 259
[14] Ni Z, Li S, Deng X, Cai Y, Zhang L, Wang W, Yang Z B, Yu H, Yan F, Liu S, Zou C L, Sun L, Zheng S B, Xu Y and Yu D 2023 Nature 616 56
[15] Sivak V V, Eickbusch A, Royer B, Singh S, Tsioutsios I, Ganjam S, Miano A, Brock B L, Ding A Z, Frunzio L, Girvin S M, Schoelkopf R J and Devoret M H 2023 Nature 616 50
[16] Acharya R, Aghababaie-Beni L, Aleiner I, Andersen T I, Ansmann M, Arute F, Arya K, Asfaw A, Astrakhantsev N, Atalaya J, et al. 2024 arXiv:2408.13687
[17] Koch J, Yu T M, Gambetta J, Houck A A, Schuster D I, Majer J, Blais A, Devoret M H, Girvin S M and Schoelkopf R J 2007 Phys. Rev. A 76 042319
[18] Barends R, Kelly J, Megrant A, Sank D, Jeffrey E, Chen Y, Yin Y, Chiaro B, Mutus J, Neill C, et al. 2013 Phys. Rev. Lett. 111 080502
[19] Bardin J C, Sank D, Naaman O and Jeffrey E 2020 IEEE Microwave Magazine 21 24
[20] Krantz P, Kjaergaard M, Yan F, Orlando T P, Gustavsson S and Oliver W D 2019 Appl. Phys. Rev. 6 021318
[21] Ding C, Di Federico M, Hatridge M, Houck A, Leger S, Martinez J, Miao C, Schuster D I, Stefanazzi L, Stoughton C, Sussman S, Treptow K, Uemura S, Wilcer N, Zhang H, Zhou C and Cancelo G 2023 arXiv:2311.17171 [quant-ph]
[22] Stefanazzi L, Treptow K, Wilcer N, Stoughton C, Bradford C, Uemura S, Zorzetti S, Montella S, Cancelo G, Sussman S, Houck A, Saxena S, Arnaldi H, Agrawal A, Zhang H, Ding C and Schuster D I 2022 Rev. Sci. Instrum. 93 044709
[23] Xu Y, Huang G, Fruitwala N, Rajagopala A, Naik R K, Nowrouzi K, Santiago D I and Siddiqi I 2023 arXiv:2309.10333 [quant-ph]
[24] Xu Y, Huang G, Balewski J, Naik R, Morvan A, Mitchell B, Nowrouzi K, Santiago D I and Siddiqi I 2021 IEEE Transactions on Quantum Engineering 2 1
[25] Guo C, Liang F, Lin J, Xu Y, Sun L, Liu W, Liao S and Peng C 2019 IEEE Transactions on Nuclear Science 66 1222
[26] Lin J, Liang F, Xu Y, Sun L H, Guo C, Liao S K and Peng C Z 2019 AIP Advances 9 115309
[27] Sun L, Liang F, Lin J, Guo C, Xu Y, Liao S and Peng C 2020 IEEE Transactions on Nuclear Science 67 2148
[28] Yang Y, Shen Z, Zhu X, Wang Z, Zhang G, Zhou J, Jiang X, Deng C and Liu S 2022 Rev. Sci. Instrum. 93 074701
[29] Yang Y, Shen Z, Zhu X, Deng C, Liu S and An Q 2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) pp. 1
[30] Wang Z, Yu H, Liu R, Ma X, Guo X, Xiang Z, Song P, Su L, Jin Y and Zheng D 2021 Chin. Phys. B 30 110305
[31] Analog Devices 2014 HMC7044 Datasheet and Product InfojAnalog Devices
[32] Xilinx 2018 Zynq-7000 SoC Data Sheet: Overview (DS190)
[33] Analog Devices 2012 AD9739 Datasheet and Product InfojAnalog Devices
[34] Xilinx 2020 7 Series FPGAs Data Sheet: Overview (DS180)
[35] Texas Instruments 2013 ADC08D1020 data sheet, product information and supportjTI.com
[36] Jolin S W, Borgani R, Tholen M O, Forchheimer D and Haviland D B 2020 Rev. Sci. Instrum. 91 124707
[37] Herrmann J, Hellings C, Lazar S, Pfäffli F, Haupt F, Thiele T, Zanuz D C, Norris G J, Heer F, Eichler C, et al. 2022 arXiv:2210.02513 [quantph]
[38] Wu N, Lin J, Xie C, Guo Z, Huang W, Zhang L, Zhou Y, Sun X, Zhang J, Guo W, Linpeng X, Liu S, Liu Y, Ren W, Tao Z, Jiang J, Chu J, Niu J, Zhong Y and Yu D 2024 arXiv:2408.11671 [quant-ph]
[39] Yang X, Chu J, Guo Z, Huang W, Liang Y, Liu J, Qiu J, Sun X, Tao Z, Zhang J, et al. 2024 arXiv:2403.16155 [quant-ph]
[40] Zhu M D, Yan L, Qin X, Zhang W Z, Lin Y and Du J 2023 Chin. Phys. B 32 090702
[41] Xue X, Russ M, Samkharadze N, Undseth B, Sammak A, Scappucci G and Vandersypen L M 2022 Nature 601 343
[42] McHugh S, Mazin B A, Serfass B, Meeker S, O’Brien K, Duan R, Raffanti R and Werthimer D 2012 Rev. Sci. Instrum. 83 044702 |
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|
