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To get the best possible results from current quantum devices error mitigation is essential. In this work we present a simple but effective error mitigation technique based on the assumption that noise in a deep quantum circuit is well…

In the noisy intermediate-scale quantum (NISQ) era, quantum error mitigation (QEM) is essential for producing reliable outputs from quantum circuits. We present a statistical signal processing approach to QEM that estimates the most likely…

Understanding the spectrum of noise acting on a qubit can yield valuable information about its environment, and crucially underpins the optimization of dynamical decoupling protocols that can mitigate such noise. However, extracting…

Quantum Physics · Physics 2021-02-01 David F. Wise , John J. L. Morton , Siddharth Dhomkar

Using near-term quantum computers to achieve a quantum advantage requires efficient strategies to improve the performance of the noisy quantum devices presently available. We develop and experimentally validate two efficient error…

We propose a hybrid protocol to classify quantum noises using supervised classical machine learning models and simple quantum key distribution protocols. We consider the quantum bit error rates (QBERs) generated in QKD schemes under…

Quantum Physics · Physics 2025-04-02 Shreya Banerjee , Ashmi A. , Prasanta K. Panigrahi

Maximizing the computational utility of near-term quantum processors requires predictive noise models that inform robust, noise-aware compilation and error mitigation. Conventional models often fail to capture the complex error dynamics of…

Quantum Physics · Physics 2026-03-17 Yanjun Ji , Marco Roth , David A. Kreplin , Ilia Polian , Frank K. Wilhelm

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

We apply quantum error mitigation techniques to a variety of benchmark problems and quantum computers to evaluate the performance of quantum error mitigation in practice. To do so, we define an empirically motivated, resource-normalized…

Quantum Physics · Physics 2023-08-21 Vincent Russo , Andrea Mari , Nathan Shammah , Ryan LaRose , William J. Zeng

Various noise models have been developed in quantum computing study to describe the propagation and effect of the noise which is caused by imperfect implementation of hardware. Identifying parameters such as gate and readout error rates are…

Quantum Physics · Physics 2022-11-08 Muqing Zheng , Ang Li , Tamás Terlaky , Xiu Yang

Quantum noise fundamentally limits the utility of near-term quantum devices, making error mitigation essential for practical quantum computation. While traditional quantum error correction codes require substantial qubit overhead and…

Quantum Physics · Physics 2025-09-23 Karan Kendre

The inevitable accumulation of errors in near-future quantum devices represents a key obstacle in delivering practical quantum advantages, motivating the development of various quantum error-mitigation methods. Here, we derive fundamental…

Quantum Physics · Physics 2022-09-23 Ryuji Takagi , Suguru Endo , Shintaro Minagawa , Mile Gu

In the current quantum computing paradigm, significant focus is placed on the reduction or mitigation of quantum decoherence. When designing new quantum processing units, the general objective is to reduce the amount of noise qubits are…

Quantum Physics · Physics 2026-02-17 Viacheslav Kuzmin , Wilfrid Somogyi , Ekaterina Pankovets , Alexey Melnikov

Mitigating measurement errors in quantum systems without relying on quantum error correction is of critical importance for the practical development of quantum technology. Deep learning-based quantum measurement error mitigation has…

Quantum Physics · Physics 2024-08-12 ChangWon Lee , Daniel K. Park

Quantum computation promises to advance a wide range of computational tasks. However, current quantum hardware suffers from noise and is too small for error correction. Thus, accurately utilizing noisy quantum computers strongly relies on…

Optimization and Control · Mathematics 2024-12-16 Friedrich Wagner , Daniel J. Egger , Frauke Liers

Noisy, intermediate-scale quantum computers come with intrinsic limitations in terms of the number of qubits (circuit "width") and decoherence time (circuit "depth") they can have. Here, for the first time, we demonstrate a recently…

Quantum Physics · Physics 2020-09-02 Thomas Ayral , François-Marie Le Régent , Zain Saleem , Yuri Alexeev , Martin Suchara

A general method to mitigate the effect of errors in quantum circuits is outlined. The method is developed in sight of characteristics that an ideal method should possess and to ameliorate an existing method which only mitigates state…

Quantum Physics · Physics 2020-11-24 Manpreet Singh Jattana , Fengping Jin , Hans De Raedt , Kristel Michielsen

This is an introduction to software methods of quantum fault tolerance. Broadly speaking, these methods describe strategies for using the noisy hardware components of a quantum computer to perform computations while continually monitoring…

Quantum Physics · Physics 2013-12-06 Panos Aliferis

Parameterized Quantum Circuits (PQCs) have been acknowledged as a leading strategy to utilize near-term quantum advantages in multiple problems, including machine learning and combinatorial optimization. When applied to specific tasks, the…

Error mitigation has enabled quantum computing applications with over one hundred qubits and deep circuits. The most general error mitigation methods rely on a faithful characterization of the noise channels of the hardware. However,…

The field of quantum computing has experienced a rapid expansion in recent years, with ongoing exploration of new technologies, a decrease in error rates, and a growth in the number of qubits available in quantum processors. However,…

Quantum Physics · Physics 2023-03-16 Samuel Stein , Nathan Wiebe , Yufei Ding , James Ang , Ang Li