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Quantum noise is a central challenge in quantum computing across many applications. Extensive work has examined how qubits couple to their environment, leading to decoherence and relaxation, which is irreversible. Current studies focus on…

Quantum Physics · Physics 2026-04-30 Yunos El Kaderi , Andreas Honecker , Iryna Andriyanova

Quantum sensing is an important application of emerging quantum technologies. We explore whether a hybrid system of quantum sensors and quantum circuits can surpass the classical limit of sensing. In particular, we use optimization…

Low-frequency noise can induce serious decoherence in superconducting qubits. Due to its diverse physical origin, such noise can couple with the qubits either as transverse or as longitudinal noise. Here, we present a universal quantum…

Quantum Physics · Physics 2013-10-02 X. -H. Deng , Y. Hu , Lin Tian

Characterizing noise in superconducting qubits is essential for improving coherence and gate performance. Conventional noise-sensing methods typically use the qubit itself as the sensor, which limits both accessible bandwidth and…

Quantum Physics · Physics 2026-04-10 Nitzan Kahn , Dror Garti , Uri Goldblatt , Lalit M. Joshi , Fabien Lafont , Serge Rosenblum

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

Characterizing and understanding the environment affecting quantum systems is critical to elucidate its physical properties and engineer better quantum devices. We develop an approach to reduce the quantum environment causing single-qubit…

Quantum Physics · Physics 2022-10-19 Won Kyu Calvin Sun , Paola Cappellaro

Quantum error mitigation has been proposed as a means to combat unwanted and unavoidable errors in near-term quantum computing without the heavy resource overheads required by fault tolerant schemes. Recently, error mitigation has been…

Quantum Physics · Physics 2024-10-15 Yihui Quek , Daniel Stilck França , Sumeet Khatri , Johannes Jakob Meyer , Jens Eisert

Quantum processing units boost entanglement at the level of hardware and enable physical simulations of highly correlated electron states in molecules and intermolecular chemical bonds. The variational quantum eigensolver provides a…

A precise measurement of dephasing over a range of timescales is critical for improving quantum gates beyond the error correction threshold. We present a metrological tool, based on randomized benchmarking, capable of greatly increasing the…

Transpilation, particularly noise-aware optimization, is widely regarded as essential for maximizing the performance of quantum circuits on superconducting quantum computers. The common wisdom is that each circuit should be transpiled using…

Quantum Physics · Physics 2025-10-03 Yuqian Huo , Jinbiao Wei , Christopher Kverne , Mayur Akewar , Janki Bhimani , Tirthak Patel

Bosonic modes are prevalent in all aspects of quantum information processing. However, existing tools for characterizing the quality, stability, and noise properties of bosonic modes are limited, especially in a driven setting. Here, we…

Quantum Physics · Physics 2025-06-13 Christophe H. Valahu , Tomas Navickas , Michael J. Biercuk , Ting Rei Tan

Instabilities due to extrinsic interference are routinely faced in systems engineering, and a common solution is to rely on a broad class of $\textit{filtering}$ techniques in order to afford stability to intrinsically unstable systems. For…

Quantum Physics · Physics 2015-06-19 A. Soare , H. Ball , D. Hayes , J. Sastrawan , M. C. Jarratt , J. J. McLoughlin , X. Zhen , T. J. Green , M. J. Biercuk

We consider the dynamics of strongly localized systems subject to dephasing noise with arbitrary correlation time. Although noise inevitably induces delocalization, transport in the noise-induced delocalized phase is subdiffusive in a…

Disordered Systems and Neural Networks · Physics 2017-07-28 Sarang Gopalakrishnan , K. Ranjibul Islam , Michael Knap

Simulating real-time dynamics of gauge theories represents a paradigmatic use case to test the hardware capabilities of a quantum computer, since it can involve non-trivial input states preparation, discretized time evolution, long-distance…

Noise sources unavoidably affect any quantum technological device. Noise's main features are expected to strictly depend on the physical platform on which the quantum device is realized, in the form of a distinguishable fingerprint. Noise…

Quantum Physics · Physics 2022-04-04 Stefano Martina , Lorenzo Buffoni , Stefano Gherardini , Filippo Caruso

Quantum computers have enabled solving problems beyond the current computers' capabilities. However, this requires handling noise arising from unwanted interactions in these systems. Several protocols have been proposed to address efficient…

Quantum Physics · Physics 2021-09-14 Ali Shaib , Mohamad H. Naim , Mohammed E. Fouda , Rouwaida Kanj , Fadi Kurdahi

Advancing quantum information processors and building fault-tolerant architectures rely on the ability to accurately characterize the noise sources and suppress their impact on quantum devices. In practice, noise often drifts over time,…

Quantum Physics · Physics 2025-11-13 Devansh Bhardwaj , Evangelia Takou , Yingjia Lin , Kenneth R. Brown

We present a general and exact formalism for finding the evolution of a quantum system subject to external telegraph noise. The various qubit decoherence rates are determined by the eigenvalues of a transfer matrix. The formalism can be…

Quantum Physics · Physics 2009-11-13 Bin Cheng , Qiang-Hua Wang , Robert Joynt

Quantum computers now show the promise of surpassing any possible classical machine. However, errors limit this ability and current machines do not have the ability to implement error correcting codes due to the limited number of qubits and…

Quantum Physics · Physics 2023-09-26 Zhao-Ming Wang , Feng-Hua Ren , Mark S. Byrd , Lian-Ao Wu

Generative models realized with machine learning techniques are powerful tools to infer complex and unknown data distributions from a finite number of training samples in order to produce new synthetic data. Diffusion models are an emerging…

Quantum Physics · Physics 2024-07-18 Marco Parigi , Stefano Martina , Filippo Caruso