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The reliable characterization of quantum states is a fundamental task in quantum information science. For this purpose, quantum state tomography provides a standard framework for reconstructing quantum states from measurement data, yet it…

Quantum Physics · Physics 2026-04-14 Yixuan Hu , Mengru Ma , Jiangwei Shang

Current noisy quantum computers have multiple types of errors, which can occur in the state preparation, measurement/readout, and gate operation, as well as intrinsic decoherence and relaxation. Partly motivated by the booming of…

Quantum Physics · Physics 2025-05-07 Hongye Yu , Tzu-Chieh Wei

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…

Simulating real-time dynamics under a Hamiltonian is a central goal of quantum information science. While numerous Hamiltonian-simulation quantum algorithms have been proposed, the effects of physical noise have rarely been incorporated…

Quantum Physics · Physics 2026-03-13 Keisuke Murota , Synge Todo , Suguru Endo

The development of quantum computers has been the stimulus that enables the realization of Quantum Machine Learning (QML), an area that integrates the calculational framework of quantum mechanics with the adaptive properties of classical…

Computational Engineering, Finance, and Science · Computer Science 2025-09-04 Bhavna Bose , Saurav Verma

Quantum systems, in general, output data that cannot be simulated efficiently by a classical computer, and hence is useful for solving certain mathematical problems and simulating quantum many-body systems. This also implies, unfortunately,…

Quantum Physics · Physics 2017-10-04 Keisuke Fujii , Masahito Hayashi

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

Machine-learning (ML) classifiers are increasingly used in quantum computing systems to improve multi-qubit readout discrimination and to mitigate correlated readout errors. These ML classifiers are an integral component of today's quantum…

Quantum Physics · Physics 2025-12-24 Anthony Etim , Jakub Szefer

Quantum Machine Learning (QML) is becoming increasingly prevalent due to its potential to enhance classical machine learning (ML) tasks, such as classification. Although quantum noise is often viewed as a major challenge in quantum…

Quantum Physics · Physics 2026-02-03 Hoang M. Ngo , Tre' R. Jeter , Incheol Shin , Wanli Xing , Tamer Kahveci , My T. Thai

Quantum computers promise to enhance machine learning for practical applications. Quantum machine learning for real-world data has to handle extensive amounts of high-dimensional data. However, conventional methods for measuring quantum…

Quantum Physics · Physics 2023-02-10 Tobias Haug , Chris N. Self , M. S. Kim

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…

Quantum metrology stands as a leading application of quantum science and technology, yet noise often constrains its precision and sensitivity. In near-term quantum metrology, existing protocols largely depend on virtual state purification,…

Quantum Physics · Physics 2025-12-03 Xiaodie Lin , Haidong Yuan

The demonstration of quantum error correction (QEC) is one of the most important milestones in the realization of fully-fledged quantum computers. Toward this, QEC experiments using the surface codes have recently been actively conducted.…

Quantum Physics · Physics 2024-01-12 Mitsuki Katsuda , Kosuke Mitarai , Keisuke Fujii

Quantum computers are becoming increasingly accessible, and may soon outperform classical computers for useful tasks. However, qubit readout errors remain a significant hurdle to running quantum algorithms on current devices. We present a…

Quantum Physics · Physics 2022-02-28 Alistair W. R. Smith , Kiran E. Khosla , Chris N. Self , M. S. Kim

Finding ground states and low-lying excitations of a given Hamiltonian is one of the most important problems in many fields of physics. As a novel approach, quantum computing on Noisy Intermediate-Scale Quantum (NISQ) devices offers the…

Noise is one of the central obstacles to building useful quantum computers, and quantum error correction (QEC) provides the framework for protecting quantum information against it. Unlike classical error correction, QEC must preserve…

Adversarial noise attacks present a significant threat to quantum machine learning (QML) models, similar to their classical counterparts. This is especially true in the current Noisy Intermediate-Scale Quantum era, where noise is…

Quantum Physics · Physics 2024-07-19 Yanling Lin , Ji Guan , Wang Fang , Mingsheng Ying , Zhaofeng Su

Present-day quantum computers suffer from various noises or errors such as gate error, relaxation, dephasing, readout error, and crosstalk. Besides, they offer a limited number of qubits with restrictive connectivity. Therefore, quantum…

Quantum computing has the potential to provide solutions to problems that are intractable on classical computers, but the accuracy of the current generation of quantum computers suffer from the impact of noise or errors such as leakage,…

Quantum Physics · Physics 2025-09-03 Benjamin Harper , Behnam Tonekaboni , Bahar Goldozian , Martin Sevior , Muhammad Usman

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