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Current hardware for quantum computing suffers from high levels of noise, and so to achieve practical fault-tolerant quantum computing will require powerful and efficient methods to correct for errors in quantum circuits. Here, we explore…

Quantum Physics · Physics 2023-08-16 Aditya Jain , Pavithran Iyer , Stephen D. Bartlett , Joseph Emerson

Quantum computing with qudits is an emerging approach that exploits a larger, more-connected computational space, providing advantages for many applications, including quantum simulation and quantum error correction. Nonetheless, qudits are…

Quantum machine learning is among the most exciting potential applications of quantum computing. However, the vulnerability of quantum information to environmental noises and the consequent high cost for realizing fault tolerance has…

Quantum metrology seeks to leverage the richness of quantum systems for making better measurements than are possible using only classical resources in order to gain a ``quantum advantage''. Quantum metrology schemes must also be resilient…

Two schemes are presented that mitigate the effect of errors and decoherence in short depth quantum circuits. The size of the circuits for which these techniques can be applied is limited by the rate at which the errors in the computation…

Quantum Physics · Physics 2017-11-08 Kristan Temme , Sergey Bravyi , Jay M. Gambetta

Reducing measurement errors in multi-qubit quantum devices is critical for performing any quantum algorithm. Here we show how to mitigate measurement errors by a classical post-processing of the measured outcomes. Our techniques apply to…

Quantum Physics · Physics 2021-04-14 Sergey Bravyi , Sarah Sheldon , Abhinav Kandala , David C. Mckay , Jay M. Gambetta

We propose a noise-mitigation quantum simulation strategy for near-term quantum devices based on Quantum Circuit Learning (QCL), which is in particular effective for integrable quantum spin chains. The method trains a shallow variational…

Quantum Physics · Physics 2026-05-01 Wenlong Zhao , Yimeng Zhang , Yan Guo , Yufan Cui , Zhuohang Wang , Rui-Dong Zhu

Quantum Image Processing (QIP) is a field that aims to utilize the benefits of quantum computing for manipulating and analyzing images. However, QIP faces two challenges: the limitation of qubits and the presence of noise in a quantum…

Quantum Physics · Physics 2024-09-27 Yifan Zhou , Yan Shing Liang

Major obstacles remain to the implementation of macroscopic quantum computing: hardware problems of noise, decoherence, and scaling; software problems of error correction; and, most important, algorithm construction. Finding truly quantum…

Quantum Physics · Physics 2020-07-17 Nathan Thompson , James Steck , Elizabeth Behrman

There has been tremendous progress in the physical realization of quantum computing hardware in recent times, bringing us closer than ever before to realizing the promise of quantum computing. However, noise continues to pose a crucial…

Quantum phase estimation (QPE) is one of the core algorithms for quantum computing. It has been extensively studied and applied in a variety of quantum applications such as the Shor's factoring algorithm, quantum sampling algorithms and the…

Current approaches to fault-tolerant quantum computation will not enable useful quantum computation on near-term devices of 50 to 100 qubits. Leading proposals, such as the color code and surface code schemes, must devote a large fraction…

Quantum Physics · Physics 2017-11-08 Peter D. Johnson , Jonathan Romero , Jonathan Olson , Yudong Cao , Alán Aspuru-Guzik

Quantum computing promises a disruptive impact on machine learning algorithms, taking advantage of the exponentially large Hilbert space available. However, it is not clear how to scale quantum machine learning (QML) to industrial-level…

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

Quantum computing is a game-changing technology for global academia, research centers and industries including computational science, mathematics, finance, pharmaceutical, materials science, chemistry and cryptography. Although it has seen…

Quantum Physics · Physics 2023-03-07 He-Liang Huang , Xiao-Yue Xu , Chu Guo , Guojing Tian , Shi-Jie Wei , Xiaoming Sun , Wan-Su Bao , Gui-Lu Long

A universal fault-tolerant quantum computer holds the promise to speed up computational problems that are otherwise intractable on classical computers; however, for the next decade or so, our access is restricted to noisy intermediate-scale…

Quantum Physics · Physics 2023-02-22 Archismita Dalal , Amara Katabarwa

In the era of quantum computing without full fault-tolerance, it is essential to suppress noise effects via the quantum error mitigation techniques to enhance the computational power of the quantum devices. One of the most effective…

Quantum Physics · Physics 2023-03-24 Yasuhiro Ohkura , Suguru Endo , Takahiko Satoh , Rodney Van Meter , Nobuyuki Yoshioka

Quantum computing testbeds exhibit high-fidelity quantum control over small collections of qubits, enabling performance of precise, repeatable operations followed by measurements. Currently, these noisy intermediate-scale devices can…

Quantum information processing faces a significant hurdle: noise. Different noise sources induce varying errors in quantum operations depending on the underlying dynamics. To gain a deeper understanding of these error mechanisms, we…

Quantum Physics · Physics 2025-05-02 Yong-Ju Hai , Junning Li , Junkai Zeng , Xiu-Hao Deng

We develop a classical bit-flip correction method to mitigate measurement errors on quantum computers. This method can be applied to any operator, any number of qubits, and any realistic bit-flip probability. We first demonstrate the…

Quantum Physics · Physics 2022-09-02 Lena Funcke , Tobias Hartung , Karl Jansen , Stefan Kühn , Paolo Stornati , Xiaoyang Wang