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Quantum error mitigation (QEM) provides a practical route for estimating reliable observables on noisy intermediate-scale quantum (NISQ) devices. Traditional QEM strategies, including zero-noise extrapolation (ZNE) and Clifford data…

Quantum Physics · Physics 2026-04-21 Huaxin Wang , Xinge Wu , Jiajun Liu , Ruiqing He , Jiandong Shang , Hengliang Guo , Qiang Chen

Quantum computing holds potential for accelerating the simulation of fluid dynamics. However, hardware noise in the noisy intermediate-scale quantum era significantly distorts simulation accuracy. Although error magnitudes are frequently…

Quantum Physics · Physics 2025-12-30 Jiahua Yang , Zhen Lu , Yue Yang

Quantum error mitigation, a data processing technique for recovering the statistics of target processes from their noisy version, is a crucial task for near-term quantum technologies. Most existing methods require prior knowledge of the…

Quantum Physics · Physics 2025-04-04 Manwen Liao , Yan Zhu , Giulio Chiribella , Yuxiang Yang

Quantum computers progress toward outperforming classical supercomputers, but quantum errors remain their primary obstacle. The key to overcoming errors on near-term devices has emerged through the field of quantum error mitigation,…

Quantum Physics · Physics 2025-05-14 Haoran Liao , Derek S. Wang , Iskandar Sitdikov , Ciro Salcedo , Alireza Seif , Zlatko K. Minev

Zero-noise extrapolation (ZNE) mitigates errors in near-term quantum devices by extrapolating measurements obtained at amplified noise levels to estimate noise-free expectation values. In practice, commonly used extrapolation models are…

Quantum Physics · Physics 2026-04-28 Andriy Miranskyy , Adam Sorrenti , Jasmine Thind , Claude Gravel

We propose a quantum error mitigation method termed self-mitigation, which is comparable with zero-noise extrapolation, to achieve quantum utility on near-term, noisy quantum computers. We investigate the effectiveness of several quantum…

Quantum Physics · Physics 2025-06-26 Seokwon Choi , Talal Ahmed Chowdhury , Kwangmin Yu

The distance-minimizing data-driven computational mechanics has great potential in engineering applications by eliminating material modeling error and uncertainty. In this computational framework, the solution-seeking procedure relies on…

Computational Engineering, Finance, and Science · Computer Science 2023-07-18 Yongchun Xu , Jie Yang , Zengtao Kuang , Qun Huang , Wei Huang , Heng Hu

As quantum computing advances towards practical applications, reducing errors remains a crucial frontier for developing near-term devices. Errors in the quantum gates and quantum state readout could result in noisy circuits, which would…

We present a new quantum error mitigation technique (QEM), called GUiding Extrapolations from Symmetry decayS (GUESS), which exploits Hamiltonian symmetries to improve accuracy of noisy quantum computations. This method is explicitly…

Quantum data encoding (QDE) enables faster com-putations than classical algorithms through superposition and en-tanglement. Circuit cutting and knitting are effective techniques for ameliorating current noisy quantum processing unit (QPUs)…

Quantum Physics · Physics 2025-11-19 Ziqing Guo , Jan Balewski , Kewen Xiao , Ziwen Pan

Quantum error mitigation techniques can reduce noise on current quantum hardware without the need for fault-tolerant quantum error correction. For instance, the quasiprobability method simulates a noise-free quantum computer using a noisy…

Quantum Physics · Physics 2022-02-01 Christophe Piveteau , David Sutter , Stefan Woerner

Error mitigation is essential for extracting reliable results from quantum computations performed on noisy intermediate-scale quantum hardware. Here we introduce Noise-Robust Estimation (NRE), a noise-agnostic framework that suppresses…

Manipulating quantum computing hardware in the presence of imperfect devices and control systems is a central challenge in realizing useful quantum computers. Susceptibility to noise limits the performance and capabilities of noisy…

Noise 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…

Quantum Physics · Physics 2021-10-14 Zhenyu Cai

Quantum Error Mitigation (QEM) enables the extraction of high-quality results from the presently-available noisy quantum computers. In this approach, the effect of the noise on observables of interest can be mitigated using multiple…

Quantum Physics · Physics 2023-11-23 Ivan Henao , Jader P. Santos , Raam Uzdin

Quantum computing allows for the manipulation of highly correlated states whose properties quickly go beyond the capacity of any classical method to calculate. Thus one natural problem which could lend itself to quantum advantage is the…

Quantum Physics · Physics 2024-12-19 Kevin Lively , Tim Bode , Jochen Szangolies , Jian-Xin Zhu , Benedikt Fauseweh

Overcoming the influence of noise and imperfections is a major challenge in quantum computing. Here, we present an approach based on applying a desired unitary computation in superposition between the system of interest and some auxiliary…

Quantum error mitigation (QEM) is vital for noisy intermediate-scale quantum (NISQ) devices. While most conventional QEM schemes assume discrete gate-based circuits with noise appearing either before or after each gate, the assumptions are…

Quantum Physics · Physics 2021-03-12 Jinzhao Sun , Xiao Yuan , Takahiro Tsunoda , Vlatko Vedral , Simon C. Bejamin , Suguru Endo

Quantum systems are inherently open and susceptible to environmental noise, which can have both detrimental and beneficial effects on their dynamics. This phenomenon has been observed in bio-molecular systems, where noise enables novel…

Significant challenges remain with the development of macroscopic quantum computing, hardware problems of noise, decoherence, and scaling, software problems of error correction, and, most important, algorithm construction. Finding truly…

Quantum Physics · Physics 2022-12-05 James E. Steck , Nathan L. Thompson , Elizabeth C. Behrman