Quantum computational advantage via 60-qubit 24-cycle random circuit sampling

Zhu, Qing–Ling; Cao, Shuchao; Chen, Fusheng; Chen, Ming-Cheng; Chen, Xiawei; Chung, Taek‐Mo; Deng, Hui; Du, Yajie; Fan, Daojin; Gong, Ming; Guo, Cheng; Guo, Chu; Guo, Shaojun; Han, Lianchen; Hong, Linyin; Huang, He-Liang; Huo, Yongheng; Li, Liping; Li, Na; Li, Shaowei; Li, Yuan; Liang, Futian; Lin, Chun; Lin, Jin; Qian, Haoran; Qiao, Dan; Rong, Hao; Su, Hong; Sun, Lihua; Wang, Liangyuan; Wang, Shiyu; Wu, Donghui; Wu, Yulin; Xu, Yu; Yan, Kai; Yang, Weifeng; Yang, Yang; Ye, Yangsen; Yin, Jianghan; Ying, Chong; Yu, Jiabing; Zha, Chen; Cha, Zhang; Zhang, Haibin; Zhang, Kaili; Zhang, Yiming; Han, Zhao; Zhao, Youwei; Zhou, Liang; Lu, Chao‐Yang; Peng, Cheng-Zhi; Zhu, Xiaobo; Pan, Jian-Wei

doi:10.1016/j.scib.2021.10.017

Cited by 165 publications

(79 citation statements)

References 44 publications

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“…After contracting two tensors at location i and j, the resulting new tensor will be put back to location i. In the following order, the contractions from (47, 70) to (192,234) (28,10), (28,58), (28,71), (56, 16), (56, 36), (56, 28), (14,24), (14,6), (14,56), (101, 186), (101, 167), (101, 14), (18,82), (18,40), (101, 18), (33, 53), (33, 39), (101, 33), (17,48), (17,37), (101, 17), (11,59), (11,29), (101, 11), (15,25), (15,7) FIG. 6.…”

Section: Appendix A: Contraction Ordermentioning

confidence: 99%

“…The sampling problem of the quantum circuits has been proposed recently as a specific computational task to demonstrate whether programmable quantum devices are able to surpass the ability of classical computations, also known as quantum supremacy (or quantum advantage) [1][2][3][4][5][6][7][8][9][10]. As a milestone, in 2019, Google released the Sycamore quantum circuits to realize this approach for the first time [1].…”

Section: Introductionmentioning

confidence: 99%

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Solving the sampling problem of the Sycamore quantum supremacy circuits

Pan,

Chen,

Zhang

2021

Preprint

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We study the problem of generating independent samples from the output distribution of Google's Sycamore quantum circuits with a target fidelity, which is believed to be beyond the reach of classical supercomputers and has been used to demonstrate quantum supremacy. We propose a new method to classically solve this problem by contracting the corresponding tensor network just once, and is massively more efficient than existing methods in obtaining a large number of uncorrelated samples with a target fidelity. For the Sycamore quantum supremacy circuit with 53 qubits and 20 cycles, we have generated one million uncorrelated bitstrings s which are sampled from a distribution P(s) = | ψ(s)| 2 , where the approximate state ψ has fidelity F ≈ 0.0037. The whole computation has cost about 15 hours on a computational cluster with 512 GPUs. The obtained one million samples, the contraction code and contraction order are made public. If our algorithm could be implemented with high efficiency on a modern supercomputer with ExaFLOPS performance, we estimate that ideally, the simulation would cost a few dozens of seconds, which is faster than Google's quantum hardware.

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Section: Appendix A: Contraction Ordermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Solving the sampling problem of the Sycamore quantum supremacy circuits

Pan,

Chen,

Zhang

2021

Preprint

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“…Superconducting quantum computers with moderate numbers of qubits are already available [1][2][3][4][5]. To increase the number of qubits further, every part of the current setups needs to be improved: data artificial atoms (AAs) that encode the qubits, room-temperature electronics that controls these AAs, and the interconnect between them.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, we show how to reduce the number of the needed transmission lines attached to each AA. The current designs [1][2][3][4][5] use separate lines for control and measurement of the AA. The control line is directly attached to the AA, but has a very small coupling such that the decay of the AA into this line is smaller than the other decoherence rates.…”

Section: Introductionmentioning

confidence: 99%

“…Addition of an unsaturable Purcell filter to a transmission line makes it more challenging to control the AA, precisely due to the fact that the qubit frequency is filtered out. If this frequency is filtered out completely, a separate control line is required [1][2][3][4][5], but it is possible to make a trade-off be- * ivan.las@tmd.ac.jp tween filtering and leaving a small coupling to perform control using the measurement line [9].…”

Section: Introductionmentioning

confidence: 99%

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Saturable Purcell filter for circuit QED

Iakoupov¹,

Koshino²

2022

Preprint

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We consider a typical circuit QED setup where a data artificial atom encodes a qubit and is dispersively coupled to a measurement resonator that in turn is coupled to a transmission line. We show theoretically that by placing a filter artificial atom in this transmission line, the effective decay of the data artificial atom into the transmission line (the Purcell decay) is suppressed. When strong control fields are present in the transmission line, the filter artificial atom is saturated and hence effectively switched off. This permits both control and measurement of the data artificial atom using a single transmission line, while maintaining the Purcell filtering capability and therefore a long coherence time of the data artificial atom in the absence of the control pulses. We also apply open systems optimal control techniques to optimize the π-pulse on the data artificial atom, achieving high fidelity. The considered setup is compatible with the frequency multiplexing, potentially enabling both control and measurement of several qubits using a single Purcell-filtered transmission line. Our work helps with the scalability of the superconducting quantum computers by decreasing the ratio between the number of qubits and the number of the required transmission lines. For the setups that already use one transmission line both for measurement and control, our work provides a way to filter out the qubit frequency completely without removing the possibility of controlling the system.

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Noisy Random Quantum Circuit Sampling and its Classical Simulation

Zhang

Wang²,

Han

2023

Adv Quantum Tech

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Demonstrating quantum advantage on noisy quantum devices is one of the most important tasks of quantum computing research in the near future. Random quantum circuit sampling is proposed as the most promising approach to the task and has been implemented in experiments for achieving quantum advantage. A series of encouraging computational complexity results, based on some plausible assumptions, show that this task is impossible to complete efficiently by classical computers. However, in practical experiments on noisy quantum devices, the approximate average‐case hardness and the effects of the noise need to be further checked. The competition between the classical simulation algorithm (mainly based on tensor network algorithms) and noisy quantum devices is the explicit way to understand quantum advantage in practice. This review briefly overviews the computational complexity arguments for the hardness of classical simulation of random quantum circuits sampling, then focus on various methods of classical simulation of quantum circuits based on tensor network method.

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Quantum computational advantage via 60-qubit 24-cycle random circuit sampling

Cited by 165 publications

References 44 publications

Solving the sampling problem of the Sycamore quantum supremacy circuits

Solving the sampling problem of the Sycamore quantum supremacy circuits

Saturable Purcell filter for circuit QED

Noisy Random Quantum Circuit Sampling and its Classical Simulation

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