English
Related papers

Related papers: Quantum state estimation with nuisance parameters

200 papers

In this paper, we analyze quantum-state estimation problems when some of the parameters are of no interest to be estimated. In classical statistics, these irrelevant parameters are called nuisance parameters and this problem is of great…

Quantum Physics · Physics 2020-08-26 Jun Suzuki

Many quantum algorithms contain an important subroutine, the quantum amplitude estimation. As the name implies, this is essentially the parameter estimation problem and thus can be handled via the established statistical estimation theory.…

Quantum Physics · Physics 2022-01-10 Tomoki Tanaka , Shumpei Uno , Tamiya Onodera , Naoki Yamamoto , Yohichi Suzuki

The quantum variables that can be accessed directly by experiments are described by observables. Therefore, physical parameters can only be evaluated indirectly, via estimations based on experimental measurement results. I show that the…

Quantum Physics · Physics 2012-12-12 B. M. Escher

Several quantities of interest in quantum information, including entanglement and purity, are nonlinear functions of the density matrix and cannot, even in principle, correspond to proper quantum observables. Any method aimed to determine…

Quantum Physics · Physics 2009-08-25 Matteo G. A. Paris

Quantum resources, such as entanglement, can decrease the uncertainty of a parameter-estimation procedure beyond what is classically possible. This phenomenon is well described for noiseless systems with asymptotically many measurement…

Quantum Physics · Physics 2021-08-09 Jason Saunders , Jean-Francois Van Huele

Quantum metrology studies quantum strategies which enable us to outperform their classical counterparts. In this framework, the existence of perfect classical reference frames is usually assumed. However, such ideal reference frames might…

Quantum Physics · Physics 2015-03-17 Dominik Šafránek , Mehdi Ahmadi , Ivette Fuentes

The inherent connection between noise and disturbance is one of the most fundamental features of quantum measurements. In the two well-known extreme cases a measurement either makes no disturbance but then has to be totally noisy or is as…

Quantum Physics · Physics 2014-01-08 Teiko Heinosaari , Takayuki Miyadera

Even though measurement results obtained in the real world are generally both noisy and continuous, quantum measurement theory tends to emphasize the ideal limit of perfect precision and quantized measurement results. In this article, a…

Quantum Physics · Physics 2008-12-18 Holger F. Hofmann

Phase estimation is the most investigated protocol in quantum metrology, but its performance is affected by the presence of noise, also in the form of imperfect state preparation. Here we discuss how to address this scenario by using a…

Quantum multiparameter estimation involves estimating multiple parameters simultaneously and can be more precise than estimating them individually. Our interest here is to determine fundamental quantum limits to the achievable…

Quantum Physics · Physics 2019-03-26 Shibdas Roy

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

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…

The efficiency of parameter estimation of quantum channels is studied in this paper. We introduce the concept of programmable parameters to the theory of estimation. It is found that programmable parameters obey the standard quantum limit…

Quantum Physics · Physics 2010-03-17 Zhengfeng Ji , Guoming Wang , Runyao Duan , Yuan Feng , Mingsheng Ying

In an idealistic setting, quantum metrology protocols allow to sense physical parameters with mean squared error that scales as $1/N^2$ with the number of particles involved---substantially surpassing the $1/N$-scaling characteristic to…

Quantum Physics · Physics 2015-01-05 Jan Kolodynski

Quantum-enhanced parameter estimation has widespread applications in many fields. An important issue is to protect the estimation precision against the noise-induced decoherence. Here we develop a general theoretical framework for improving…

Quantum Physics · Physics 2019-04-03 Yao Ma , Mi Pang , Libo Chen , Wen Yang

Near-term quantum computers are noisy, and therefore must run algorithms with a low circuit depth and qubit count. Here we investigate how noise affects a quantum neural network (QNN) for state discrimination, applicable on near-term…

Quantum Physics · Physics 2021-01-27 Andrew Patterson , Hongxiang Chen , Leonard Wossnig , Simone Severini , Dan Browne , Ivan Rungger

Information-theoretic definitions for the noise associated with a quantum measurement and the corresponding disturbance to the state of the system have recently been introduced [F. Buscemi et al., Phys. Rev. Lett. 112, 050401 (2014)]. These…

Quantum Physics · Physics 2016-12-14 Alastair A. Abbott , Cyril Branciard

We develop a hybrid framework for quantum parameter estimation in the presence of nuisance parameters. In this Bayes-point scheme, the parameters of interest are treated as fixed non-random parameters while nuisance parameters are…

Quantum Physics · Physics 2025-10-21 Jianchao Zhang , Jun Suzuki

Quantum theory allows the traversing of multiple channels in a superposition of different orders. When the order in which the channels are traversed is controlled by an auxiliary quantum system, various unknown parameters of the channels…

Quantum Physics · Physics 2023-09-27 A. Z. Goldberg , L. L. Sanchez-Soto , K. Heshami

In this work we discuss the impact of nuisance parameters on the effectiveness of machine learning in high-energy physics problems, and provide a review of techniques that allow to include their effect and reduce their impact in the search…

Machine Learning · Statistics 2021-01-19 Tommaso Dorigo , Pablo de Castro
‹ Prev 1 2 3 10 Next ›