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A massive gap exists between current quantum computing (QC) prototypes, and the size and scale required for many proposed QC algorithms. Current QC implementations are prone to noise and variability which affect their reliability, and yet…

Neutral atoms devices represent a promising technology that uses optical tweezers to geometrically arrange atoms and modulated laser pulses to control the quantum states. A neutral atoms Noisy Intermediate Scale Quantum (NISQ) device is…

Quantum Physics · Physics 2024-07-08 Ettore Canonici , Stefano Martina , Riccardo Mengoni , Daniele Ottaviani , Filippo Caruso

Noise and imperfections are among the prevalent challenges in quantum software engineering for current NISQ systems. They will remain important in the post-NISQ area, as logical, error-corrected qubits will be based on software mechanisms.…

Quantum Physics · Physics 2025-09-17 Stefan Raimund Maschek , Jürgen Schwitalla , Maja Franz , Wolfgang Mauerer

Noisy intermediate-scale quantum (NISQ) devices offer unique platforms to test and evaluate the behavior of non-fault-tolerant quantum computing. However, validating programs on NISQ devices is difficult due to fluctuations in the…

Quantum Physics · Physics 2022-01-10 Megan L. Dahlhauser , Travis S. Humble

Complex quantum networks are not only hard to establish, but also difficult to simulate due to the exponentially growing state space and noise-induced imperfections. In this work, we propose an alternative approach that leverage quantum…

Quantum Physics · Physics 2025-09-30 Ferran Riera-Sàbat , Jorge Miguel-Ramiro , Wolfgang Dür

For quantum computers to successfully solve real-world problems, it is necessary to tackle the challenge of noise: the errors which occur in elementary physical components due to unwanted or imperfect interactions. The theory of quantum…

In the noisy intermediate-scale quantum (NISQ) era, quantum error mitigation will be a necessary tool to extract useful performance out of quantum devices. However, there is a big gap between the noise models often assumed by error…

Quantum Physics · Physics 2023-01-10 Abdullah Ash Saki , Amara Katabarwa , Salonik Resch , George Umbrarescu

We present a systematic investigation of deep learning methods applied to quantum error mitigation of noisy output probability distributions from measured quantum circuits. We compare different architectures, from fully connected neural…

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

This paper introduces a noise-aware distributed Quantum Approximate Optimization Algorithm (QAOA) tailored for execution on near-term quantum hardware. Leveraging a distributed framework, we address the limitations of current Noisy…

Quantum Physics · Physics 2024-08-12 Kuan-Cheng Chen , Xiatian Xu , Felix Burt , Chen-Yu Liu , Shang Yu , Kin K Leung

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

Error mitigation (EM) methods are crucial for obtaining reliable results in the realm of noisy intermediate-scale quantum (NISQ) computers, where noise significantly impacts output accuracy. Some EM protocols are particularly efficient for…

Quantum Physics · Physics 2026-03-03 Thibault Scoquart , Hugo Perrin , Kyrylo Snizhko

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…

Quantum computing hardware is affected by quantum noise that undermine the quality of results of an executed quantum program. Amongst other quantum noises, coherent error that caused by parameter drifting and miscalibration, remains…

Hardware Architecture · Computer Science 2024-10-15 Xiangyu Ren , Junjie Wan , Zhiding Liang , Antonio Barbalace

Quantum computer emulators model the behavior and error rates of specific quantum processors. Without accurate noise models in these emulators, it is challenging for users to optimize and debug executable quantum programs prior to running…

Quantum Physics · Physics 2026-05-20 Matthew Ho , Jun Yong Khoo , Adrian M. Mak , Stefano Carrazza

Learning problems involving quantum data are natural candidates for demonstrating an advantage in quantum machine learning. Recent results indicate that, for certain tasks and under noiseless conditions, coherent processing of quantum data…

Noisy intermediate-scale quantum computers (NISQ) are in their childhood, but showing high promise. One main concern for NISQ machines is their inherent noisiness, as the qubit states are subject to disturbances with each algorithmic…

Quantum Physics · Physics 2024-07-08 Wolfgang Nowak , Tim Brünnette , Merel Schalkers , Matthias Möller

Noisy Intermediate-Scale Quantum (NISQ) devices fail to produce outputs with sufficient fidelity for deep circuits with many gates today. Such devices suffer from read-out, multi-qubit gate and crosstalk noise combined with short…

Quantum Physics · Physics 2021-07-15 Ellis Wilson , Frank Mueller , Lindsay Bassman , Constin Iancu

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…

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