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We derive fundamental bounds on the maximal achievable precision in multiparameter noisy quantum metrology, valid under the most general entanglement-assisted adaptive strategy, which are tighter than the bounds obtained by a direct use of…

Quantum Physics · Physics 2022-05-27 Francesco Albarelli , Rafal Demkowicz-Dobrzanski

For a generic set of Markovian noise models, the estimation precision of a parameter associated with the Hamiltonian is limited by the $1/\sqrt{t}$ scaling where $t$ is the total probing time, in which case the maximal possible quantum…

Quantum Physics · Physics 2020-03-11 Sisi Zhou , Liang Jiang

Bosonic systems, particularly in quantum optics and atomic physics, are leading platforms for achieving quantum enhanced precision in parameter estimation. By exploiting properties such as mode and particle entanglement, it is possible to…

Quantum Physics · Physics 2026-02-19 Astghik Saharyan , Eloi Descamps , Arne Keller , Pérola Milman

Quantum metrology aims to exploit quantum phenomena to overcome classical limitations in the estimation of relevant parameters. We consider a probe undergoing a phase shift $\varphi$ whose generator is randomly sampled according to a…

Quantum Physics · Physics 2017-06-07 Rozhin Yousefjani , Rosanna Nichols , Shahriar Salimi , Gerardo Adesso

Simultaneous quantum estimation of multiple parameters has recently become essential in quantum metrology. Although the ultimate sensitivity of a multiparameter quantum estimation in noiseless environments can beat the standard quantum…

Quantum Physics · Physics 2020-08-12 Le Bin Ho , Hideaki Hakoshima , Yuichiro Matsuzaki , Masayuki Matsuzaki , Yasushi Kondo

Quantum error correction allows to actively correct errors occurring in a quantum computation when the noise is weak enough. To make this error correction competitive information about the specific noise is required. Traditionally, this…

Quantum Physics · Physics 2021-04-07 Thomas Wagner , Hermann Kampermann , Dagmar Bruß , Martin Kliesch

In quantum computation, amplitude estimation is a fundamental subroutine that is utilized in various quantum algorithms. A general important task of such estimation problems is to characterize the estimation lower bound, which is referred…

Quantum Physics · Physics 2025-07-10 Kohei Oshio , Yohichi Suzuki , Kaito Wada , Keigo Hisanaga , Shumpei Uno , Naoki Yamamoto

Quantum advantage requires overcoming noise-induced degradation of quantum systems. Conventional methods for reducing noise such as error mitigation face scalability issues in deep circuits. Specifically, noise hampers the extraction of…

Quantum Physics · Physics 2023-12-05 Yonglong Ding , Ruyu Yang

The inevitable accumulation of errors in near-future quantum devices represents a key obstacle in delivering practical quantum advantages, motivating the development of various quantum error-mitigation methods. Here, we derive fundamental…

Quantum Physics · Physics 2022-09-23 Ryuji Takagi , Suguru Endo , Shintaro Minagawa , Mile Gu

In this paper, we introduce an efficient algorithm for the quantum amplitude estimation task which works in noisy intermediate-scale quantum(NISQ) devices. The quantum amplitude estimation is an important problem which has various…

Quantum Physics · Physics 2021-11-29 Kouhei Nakaji

Noise mechanisms in quantum systems can be broadly characterized as either coherent (i.e., unitary) or incoherent. For a given fixed average error rate, coherent noise mechanisms will generally lead to a larger worst-case error than…

Quantum Physics · Physics 2019-01-29 Joel J. Wallman , Christopher Granade , Robin Harper , Steven T. Flammia

Coherent ensembles of $N$ qubits present an advantage in quantum phase estimation over separable mixtures, but coherence decay due to classical phase diffusion reduces overall precision. In some contexts, the strength of diffusion may be…

Quantum Physics · Physics 2013-07-02 Sergey I. Knysh , Gabriel A. Durkin

As quantum computing hardware steadily increases in qubit count and quality, one important question is how to allocate these resources to mitigate the effects of hardware noise. In a transitional era between noisy small-scale and fully…

Phase estimation protocols provide a fundamental benchmark for the field of quantum metrology. The latter represents one of the most relevant applications of quantum theory, potentially enabling the capability of measuring unknown physical…

Quantum error correction protocols have been developed to offset the high sensitivity to noise inherent in quantum systems. However, much is still unknown about the behaviour of a quantum error-correcting code under general noise, including…

Quantum Physics · Physics 2021-06-09 Stefanie J. Beale , Joel J. Wallman

We demonstrate that memory in an $N$-qubit system subjected to decoherence, is a potential resource for the slow-down of the entanglement decay. We show that this effect can be used to retain the sub shot-noise sensitivity of the parameter…

Quantum Physics · Physics 2014-12-17 P. Szankowski , M. Trippenbach , J. Chwedenczuk

In order to provide a guaranteed precision and a more accurate judgement about the true value of the Cram\'{e}r-Rao bound and its scaling behavior, an upper bound (equivalently a lower bound on the quantum Fisher information) for precision…

Quantum Physics · Physics 2017-05-04 R. Yousefjani , S. Salimi , A. S. Khorashad

Quantum physics holds the promise of enabling certain tasks with better performance than possible when only classical resources are employed. The quantum phenomena present in many experiments signify nonclassical behavior, but do not always…

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…

Compressed sensing typically deals with the estimation of a system input from its noise-corrupted linear measurements, where the number of measurements is smaller than the number of input components. The performance of the estimation…

Information Theory · Computer Science 2016-11-17 Jin Tan , Danielle Carmon , Dror Baron