scholarly journals Practical Quantum Error Mitigation for Near-Future Applications

2018 ◽  
Vol 8 (3) ◽  
Author(s):  
Suguru Endo ◽  
Simon C. Benjamin ◽  
Ying Li
Keyword(s):  
Error Mitigation ◽  
Quantum Error ◽  
Near Future

scholarly journals Quantum computation with universal error mitigation on a superconducting quantum processor

2019 ◽  
Vol 5 (9) ◽  
pp. eaaw5686 ◽  
Author(s):  
Chao Song ◽  
Jing Cui ◽  
H. Wang ◽  
J. Hao ◽  
H. Feng ◽  
...  
Keyword(s):  
Quantum Computation ◽  
Quantum Computers ◽  
Superconducting Device ◽  
Error Mitigation ◽  
Main Challenge ◽  
Quantum Processor ◽  
Quantum Error ◽  
And Control ◽  
The Impact ◽  
Near Future

Medium-scale quantum devices that integrate about hundreds of physical qubits are likely to be developed in the near future. However, these devices will lack the resources for realizing quantum fault tolerance. Therefore, the main challenge of exploring the advantage of quantum computation is to minimize the impact of device and control imperfections without complete logical encoding. Quantum error mitigation is a solution satisfying the requirement. Here, we demonstrate an error mitigation protocol based on gate set tomography and quasi-probability decomposition. One- and two-qubit circuits are tested on a superconducting device, and computation errors are successfully suppressed. Because this protocol is universal for digital quantum computers and algorithms computing expected values, our results suggest that error mitigation can be an essential component of near-future quantum computation.

scholarly journals Unified approach to data-driven quantum error mitigation

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Angus Lowe ◽  
Max Hunter Gordon ◽  
Piotr Czarnik ◽  
Andrew Arrasmith ◽  
Patrick J. Coles ◽  
...  
Keyword(s):  
Data Driven ◽  
Unified Approach ◽  
Error Mitigation ◽  
Quantum Error

scholarly journals Quantum Error Mitigation With Artificial Neural Network

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 188853-188860
Author(s):  
Changjun Kim ◽  
Kyungdeock Daniel Park ◽  
June-Koo Rhee
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Error Mitigation ◽  
Artificial Neural ◽  
Quantum Error

scholarly journals Hybrid Quantum-Classical Algorithms and Quantum Error Mitigation

2021 ◽  
Vol 90 (3) ◽  
pp. 032001
Author(s):  
Suguru Endo ◽  
Zhenyu Cai ◽  
Simon C. Benjamin ◽  
Xiao Yuan
Keyword(s):  
Error Mitigation ◽  
Quantum Error

scholarly journals Virtual Distillation for Quantum Error Mitigation

2021 ◽  
Vol 11 (4) ◽  
Author(s):  
William J. Huggins ◽  
Sam McArdle ◽  
Thomas E. O’Brien ◽  
Joonho Lee ◽  
Nicholas C. Rubin ◽  
...  
Keyword(s):  
Error Mitigation ◽  
Quantum Error

scholarly journals Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Zhenyu Cai
Keyword(s):  
Estimation Accuracy ◽  
Quantum Computers ◽  
Practical Application ◽  
Combined Method ◽  
Error Mitigation ◽  
Sampling Cost ◽  
Mitigation Techniques ◽  
Near Term ◽  
Quantum Error ◽  
Error Count

AbstractNoise in quantum hardware remains the biggest roadblock for the implementation of quantum computers. To fight the noise in the practical application of near-term quantum computers, instead of relying on quantum error correction which requires large qubit overhead, we turn to quantum error mitigation, in which we make use of extra measurements. Error extrapolation is an error mitigation technique that has been successfully implemented experimentally. Numerical simulation and heuristic arguments have indicated that exponential curves are effective for extrapolation in the large circuit limit with an expected circuit error count around unity. In this Article, we extend this to multi-exponential error extrapolation and provide more rigorous proof for its effectiveness under Pauli noise. This is further validated via our numerical simulations, showing orders of magnitude improvements in the estimation accuracy over single-exponential extrapolation. Moreover, we develop methods to combine error extrapolation with two other error mitigation techniques: quasi-probability and symmetry verification, through exploiting features of these individual techniques. As shown in our simulation, our combined method can achieve low estimation bias with a sampling cost multiple times smaller than quasi-probability while without needing to be able to adjust the hardware error rate as required in canonical error extrapolation.

scholarly journals Quantum Error Mitigation for Quantum State Tomography

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Syahri Ramadhani ◽  
Junaid Ur Rehman ◽  
Hyundong Shin
Keyword(s):  
Quantum State ◽  
Quantum State Tomography ◽  
Error Mitigation ◽  
State Tomography ◽  
Quantum Error

scholarly journals Relationship between costs for quantum error mitigation and non-Markovian measures

2021 ◽  
Vol 103 (1) ◽  
Author(s):  
Hideaki Hakoshima ◽  
Yuichiro Matsuzaki ◽  
Suguru Endo
Keyword(s):  
Error Mitigation ◽  
Quantum Error

scholarly journals A Software Method For Mitigating Single Qubit Errors On Superconducting Quantum Devices

2020 ◽  
Author(s):  
Macauley Coggins ◽  
Devanshi Arora
Keyword(s):  
Error Correction ◽  
Quantum Error Correction ◽  
Superconducting Qubits ◽  
Quantum Decoherence ◽  
Small Scale ◽  
Quantum Devices ◽  
Single Qubit ◽  
Error Mitigation ◽  
Quantum Error

Quantum error correction schemes have gained a lot of attention in recent years. This is due to the emergence of small scale quantum devices that make use of superconducting qubits. However these devices are noisy and prone to quantum decoherence and thus errors. Along with quantum error correction there has been a push for new schemes in quantum error mitigation that take a more passive approach in eliminating readout errors. In this research we introduce a software method for quantum error mitigation that maps virtual qubits in a circuit to physical qubits with the least error. The method developed was tested on 9 IBM quantum devices. Results in the study have shown the method can reduce readout errors by up to 35.52%.

scholarly journals Sampling Overhead Analysis of Quantum Error Mitigation: Uncoded vs. Coded Systems

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 228967-228991
Author(s):  
Yifeng Xiong ◽  
Daryus Chandra ◽  
Soon Xin Ng ◽  
Lajos Hanzo
Keyword(s):  
Error Mitigation ◽  
Coded Systems ◽  
Quantum Error
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