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Quantum computing offers a potential for algorithmic speedups for applications, such as large-scale simulations in chemistry and physics. However, these speedups must yield results that are sufficiently accurate to predict realistic…

Quantum Physics · Physics 2025-01-15 Meenambika Gowrishankar , Daniel Claudino , Jerimiah Wright , Travis Humble

Kernel methods are the basis of most classical machine learning algorithms such as Gaussian Process (GP) and Support Vector Machine (SVM). Computing kernels using noisy intermediate scale quantum (NISQ) devices has attracted considerable…

We present a quantum algorithm based on the Generalized Quantum Master Equation (GQME) approach to simulate open quantum system dynamics on noisy intermediate-scale quantum (NISQ) computers. This approach overcomes the limitations of the…

Quantum error mitigation (QEM) protocols have provably exponential bounds on the cost scaling; however, exploring which regimes QEM can recover usable results is still of sizable interest. The expected absence of complete error correction…

Quantum Physics · Physics 2025-05-12 Ugnė Liaubaitė , S. E. Skelton

Quantum computational experiments exploiting Noisy Intermediate-Scale Quantum (NISQ) devices to demonstrate violation of a Bell inequality are proposed. They consist of running specified quantum algorithms on few-qubit computers. If such a…

Quantum Physics · Physics 2020-09-02 H. W. L. Naus , H. Polinder

In recent years, efficient quantum circuit simulations incorporating ideal noise assumptions have relied on tensor network simulators, particularly leveraging the matrix product density operator (MPDO) framework. However, experiments on…

Quantum Physics · Physics 2025-08-12 Wei-guo Ma , Yun-Hao Shi , Kai Xu , Heng Fan

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

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

NWQ-Sim is a cutting-edge quantum system simulation environment designed to run on classical multi-node, multi-CPU/GPU heterogeneous HPC systems. In this work, we provide a brief overview of NWQ-Sim and its implementation in simulating…

Quantum Physics · Physics 2024-01-17 In-Saeng Suh , Ang Li

Quantum computing allows for the manipulation of highly correlated states whose properties quickly go beyond the capacity of any classical method to calculate. Thus one natural problem which could lend itself to quantum advantage is the…

Quantum Physics · Physics 2024-12-19 Kevin Lively , Tim Bode , Jochen Szangolies , Jian-Xin Zhu , Benedikt Fauseweh

Quantum error mitigation (QEM) and quantum error correction (QEC) are two research areas that are often considered as distinct entities, and the problem of combining the two approaches in a non-trivial way has only recently started to be…

Quantum Physics · Physics 2026-03-13 George Umbrarescu , Oscar Higgott , Dan E. Browne

We present a novel method for simulating the noisy behaviour of quantum computers, which allows to efficiently incorporate environmental effects in the driven evolution implementing the gates acting on the qubits. We show how to modify the…

Some of the computational limitations in solving the nuclear many-body problem could be overcome by utilizing quantum computers. The nuclear shell-model calculations providing deeper insights into the properties of atomic nuclei, is one…

Quantum Physics · Physics 2026-05-25 Nifeeya Singh , Pooja Siwach , P. Arumugam

Mitigation of quantum errors is critical for current NISQ devices. In the present work, we address this task by treating the execution of quantum algorithms as the time evolution of an idealized physical system. We use knowledge of its…

Quantum Physics · Physics 2025-09-11 Theo Saporiti , Oleg Kaikov , Vasily Sazonov , Mohamed Tamaazousti

Digital zero-noise extrapolation (dZNE) has emerged as a common approach for quantum error mitigation (QEM) due to its conceptual simplicity, accessibility, and resource efficiency. In practice, however, properly applying dZNE to extend the…

Quantum Physics · Physics 2023-07-21 Ritajit Majumdar , Pedro Rivero , Friederike Metz , Areeq Hasan , Derek S Wang

Quantum Computing in the Noisy Intermediate-Scale Quantum (NISQ) era has shown promising applications in machine learning, optimization, and cryptography. Despite the progress, challenges persist due to system noise, errors, and decoherence…

Quantum Physics · Physics 2024-04-12 Bikram Khanal , Pablo Rivas

While the recent demonstration of accurate computations of classically intractable simulations on noisy quantum processors brings quantum advantage closer, there is still the challenge of demonstrating it for practical problems. Here we…

Quantum Physics · Physics 2024-04-29 Artemiy Burov , Oliver Nagl , Clément Javerzac-Galy

The search for useful applications of noisy intermediate-scale quantum (NISQ) devices in quantum simulation has been hindered by their intrinsic noise and the high costs associated with achieving high accuracy. A promising approach to…

Quantum Physics · Physics 2025-07-01 Emiel Koridon , Felix Frohnert , Eric Prehn , Evert van Nieuwenburg , Jordi Tura , Stefano Polla

Variational quantum eigensolver (VQE) is promising to show quantum advantage on near-term noisy-intermediate-scale quantum (NISQ) computers. One central problem of VQE is the effect of noise, especially the physical noise on realistic…

Quantum Physics · Physics 2021-09-30 Jinfeng Zeng , Zipeng Wu , Chenfeng Cao , Chao Zhang , Shiyao Hou , Pengxiang Xu , Bei Zeng

Achieving near-term quantum advantage will require effective methods for mitigating hardware noise. Data-driven approaches to error mitigation are promising, with popular examples including zero-noise extrapolation (ZNE) and Clifford data…