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Noisy and Intermediate-Scale Quantum, or NISQ, processors are sensitive to noise, prone to quantum decoherence, and are not yet capable of continuous quantum error correction for fault-tolerant quantum computation. Hence, quantum algorithms…

Adaptive measurements were recently shown to significantly improve the performance of quantum state tomography. Utilizing information about the system for the on-line choice of optimal measurements allows to reach the ultimate bounds of…

We present a general route to reduce inhomogeneous broadening in nanodevices due to 1/f noise. We apply this method to a universal two-qubit gate and demonstrate that for selected optimal couplings, a high-efficient gate can be implemented…

Mesoscale and Nanoscale Physics · Physics 2010-02-16 E. Paladino , A. Mastellone , A. D'Arrigo , G. Falci

Noise in quantum computing is countered with quantum error correction. Achieving optimal performance will require tailoring codes and decoding algorithms to account for features of realistic noise, such as the common situation where the…

Quantum Physics · Physics 2020-04-02 David K. Tuckett , Stephen D. Bartlett , Steven T. Flammia , Benjamin J. Brown

Achieving quantum-enhanced performances when measuring unknown quantities requires developing suitable methodologies for practical scenarios, that include noise and the availability of a limited amount of resources. Here, we report on the…

We investigate how the efficiency of the quantum teleportation protocol is affected when the qubits involved in the protocol are subjected to noise or decoherence. We study all types of noise usually encountered in real world…

Quantum Physics · Physics 2015-08-05 Raphael Fortes , Gustavo Rigolin

A method to suppress noise, which is one of the major obstacles to obtain an optimal solution in quantum annealers, is proposed. We generalize the conventionally used Hamiltonian, i.e., the transverse field Hamiltonian, by introducing an…

Quantum Physics · Physics 2020-06-25 Takayuki Suzuki , Hiromichi Nakazato

Quantum computation, a completely different paradigm of computing, benefits from theoretically proven speed-ups for certain problems and opens up the possibility of exactly studying the properties of quantum systems. Yet, because of the…

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

Quantum machine learning algorithms based on parameterized quantum circuits are promising candidates for near-term quantum advantage. Although these algorithms are compatible with the current generation of quantum processors, device noise…

Quantum Physics · Physics 2023-10-11 André Melo , Nathan Earnest-Noble , Francesco Tacchino

Superconducting transmon qubits are a promising platform for quantum computation, yet they face significant fidelity degradation due to connectivity noise, particularly in the intermediate coupling regime where noise levels are substantial.…

Quantum Physics · Physics 2026-04-29 Quan Fu , Xin Wang , Rui Xiong

A process which strongly amplifies both quadrature amplitudes of an oscillatory signal necessarily adds noise. Alternatively, if the information in one quadrature is lost in phase-sensitive amplification, it is possible to completely…

Mesoscale and Nanoscale Physics · Physics 2017-03-14 C. F. Ockeloen-Korppi , E. Damskägg , J. -M. Pirkkalainen , T. T. Heikkilä , F. Massel , M. A. Sillanpää

As quantum processors grow in scale and reliability, the need for efficient quantum gate decomposition of circuits to a set of specific available gates, becomes ever more critical. The decomposition of a particular algorithm into a sequence…

Quantum Physics · Physics 2025-01-30 Jonathan Nemirovsky , Maya Chuchem , Yotam Shapira

Automatic differentiation is an invaluable feature of machine learning and quantum machine learning software libraries. In this work it is shown how quantum automatic differentiation can be used to solve the condensed-matter problem of…

Quantum Physics · Physics 2022-11-29 Olivia Di Matteo , R. M. Woloshyn

We analyze and compare the characterization of a quantum device in terms of noise, transmitted bit-error-rate (BER) and mutual information, showing how the noise description is meaningful only for Gaussian channels. After reviewing the…

Quantum Physics · Physics 2015-06-26 G. M. D'Ariano , C. Macchiavello , L. Maccone

Noise is the defining feature of the NISQ era, but it remains unclear if noisy quantum devices are capable of quantum speedups. Quantum supremacy experiments have been a major step forward, but gaps remain between the theory behind these…

Quantum Physics · Physics 2022-03-08 Adam Bouland , Bill Fefferman , Zeph Landau , Yunchao Liu

Advancing quantum technologies necessitates an in-depth exploration of how operations generate quantum resources and respond to noise. Crucial are gates generating quantum coherence and the challenge of mitigating gate dephasing noise.…

Quantum Physics · Physics 2024-03-29 Roberto Salazar , Fereshte Shahbeigi

The rapid development of noisy intermediate-scale quantum (NISQ) devices has raised the question of whether or not these devices will find commercial use. Unfortunately, a major shortcoming of many proposed NISQ-amenable algorithms, such as…

Quantum Physics · Physics 2021-10-22 Amara Katabarwa , Alex Kunitsa , Borja Peropadre , Peter Johnson

Quantum noise in real-world devices poses a significant challenge in achieving practical quantum advantage, since accurately compiled and executed circuits are typically deep and highly susceptible to decoherence. To facilitate the…

Quantum Physics · Physics 2025-06-13 Yuchen Guo , Shuo Yang

Quantum computers are poised to radically outperform their classical counterparts by manipulating coherent quantum systems. A realistic quantum computer will experience errors due to the environment and imperfect control. When these errors…

Quantum Physics · Physics 2016-11-21 Joel J. Wallman , Joseph Emerson
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