Author
Listed:
- Xiao Xue
(QuTech, Delft University of Technology
Delft University of Technology)
- Bishnu Patra
(QuTech, Delft University of Technology
Delft University of Technology
Delft University of Technology)
- Jeroen P. G. Dijk
(QuTech, Delft University of Technology
Delft University of Technology
Delft University of Technology)
- Nodar Samkharadze
(QuTech, Delft University of Technology
Netherlands Organization for Applied Scientific Research (TNO))
- Sushil Subramanian
(Intel Corporation)
- Andrea Corna
(QuTech, Delft University of Technology
Delft University of Technology)
- Brian Paquelet Wuetz
(QuTech, Delft University of Technology
Delft University of Technology)
- Charles Jeon
(Intel Corporation)
- Farhana Sheikh
(Intel Corporation)
- Esdras Juarez-Hernandez
(Intel Guadalajara)
- Brando Perez Esparza
(Intel Guadalajara)
- Huzaifa Rampurawala
(Intel Corporation)
- Brent Carlton
(Intel Corporation)
- Surej Ravikumar
(Intel Corporation)
- Carlos Nieva
(Intel Corporation)
- Sungwon Kim
(Intel Corporation)
- Hyung-Jin Lee
(Intel Corporation)
- Amir Sammak
(QuTech, Delft University of Technology
Netherlands Organization for Applied Scientific Research (TNO))
- Giordano Scappucci
(QuTech, Delft University of Technology
Delft University of Technology)
- Menno Veldhorst
(QuTech, Delft University of Technology
Delft University of Technology)
- Fabio Sebastiano
(QuTech, Delft University of Technology
Delft University of Technology)
- Masoud Babaie
(QuTech, Delft University of Technology
Delft University of Technology)
- Stefano Pellerano
(Intel Corporation)
- Edoardo Charbon
(QuTech, Delft University of Technology
Delft University of Technology
Intel Corporation
École Polytechnique Fédérale de Lausanne (EPFL))
- Lieven M. K. Vandersypen
(QuTech, Delft University of Technology
Delft University of Technology
Intel Corporation)
Abstract
The most promising quantum algorithms require quantum processors that host millions of quantum bits when targeting practical applications1. A key challenge towards large-scale quantum computation is the interconnect complexity. In current solid-state qubit implementations, an important interconnect bottleneck appears between the quantum chip in a dilution refrigerator and the room-temperature electronics. Advanced lithography supports the fabrication of both control electronics and qubits in silicon using technology compatible with complementary metal oxide semiconductors (CMOS)2. When the electronics are designed to operate at cryogenic temperatures, they can ultimately be integrated with the qubits on the same die or package, overcoming the ‘wiring bottleneck’3–6. Here we report a cryogenic CMOS control chip operating at 3 kelvin, which outputs tailored microwave bursts to drive silicon quantum bits cooled to 20 millikelvin. We first benchmark the control chip and find an electrical performance consistent with qubit operations of 99.99 per cent fidelity, assuming ideal qubits. Next, we use it to coherently control actual qubits encoded in the spin of single electrons confined in silicon quantum dots7–9 and find that the cryogenic control chip achieves the same fidelity as commercial instruments at room temperature. Furthermore, we demonstrate the capabilities of the control chip by programming a number of benchmarking protocols, as well as the Deutsch–Josza algorithm10, on a two-qubit quantum processor. These results open up the way towards a fully integrated, scalable silicon-based quantum computer.
Suggested Citation
Xiao Xue & Bishnu Patra & Jeroen P. G. Dijk & Nodar Samkharadze & Sushil Subramanian & Andrea Corna & Brian Paquelet Wuetz & Charles Jeon & Farhana Sheikh & Esdras Juarez-Hernandez & Brando Perez Espa, 2021.
"CMOS-based cryogenic control of silicon quantum circuits,"
Nature, Nature, vol. 593(7858), pages 205-210, May.
Handle:
RePEc:nat:nature:v:593:y:2021:i:7858:d:10.1038_s41586-021-03469-4
DOI: 10.1038/s41586-021-03469-4
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Citations
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Cited by:
- Zenghui Bao & Yan Li & Zhiling Wang & Jiahui Wang & Jize Yang & Haonan Xiong & Yipu Song & Yukai Wu & Hongyi Zhang & Luming Duan, 2024.
"A cryogenic on-chip microwave pulse generator for large-scale superconducting quantum computing,"
Nature Communications, Nature, vol. 15(1), pages 1-9, December.
- Juhyeok Lee & Syed Zahid Hassan & Sangjun Lee & Hye Ryun Sim & Dae Sung Chung, 2022.
"Azide-functionalized ligand enabling organic–inorganic hybrid dielectric for high-performance solution-processed oxide transistors,"
Nature Communications, Nature, vol. 13(1), pages 1-11, December.
- Brian Paquelet Wuetz & Davide Degli Esposti & Anne-Marije J. Zwerver & Sergey V. Amitonov & Marc Botifoll & Jordi Arbiol & Amir Sammak & Lieven M. K. Vandersypen & Maximilian Russ & Giordano Scappucci, 2023.
"Reducing charge noise in quantum dots by using thin silicon quantum wells,"
Nature Communications, Nature, vol. 14(1), pages 1-9, December.
- Akito Noiri & Kenta Takeda & Takashi Nakajima & Takashi Kobayashi & Amir Sammak & Giordano Scappucci & Seigo Tarucha, 2022.
"A shuttling-based two-qubit logic gate for linking distant silicon quantum processors,"
Nature Communications, Nature, vol. 13(1), pages 1-7, December.
- Brian Paquelet Wuetz & Merritt P. Losert & Sebastian Koelling & Lucas E. A. Stehouwer & Anne-Marije J. Zwerver & Stephan G. J. Philips & Mateusz T. Mądzik & Xiao Xue & Guoji Zheng & Mario Lodari & Ser, 2022.
"Atomic fluctuations lifting the energy degeneracy in Si/SiGe quantum dots,"
Nature Communications, Nature, vol. 13(1), pages 1-8, December.
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