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Fisher information is a measure of the best precision with which a parameter can be estimated from statistical data. It can also be defined for a continuous random variable without reference to any parameters, in which case it has a…

Data Analysis, Statistics and Probability · Physics 2009-03-22 S. Prasad , N. C. Menicucci

We derive a general upper bound to mutual information in terms of the Fisher information. The bound may be further used to derive a lower bound for the Bayesian quadratic cost. These two provide alternatives to other inequalities in the…

Quantum Physics · Physics 2025-05-16 Wojciech Górecki , Xi Lu , Chiara Macchiavello , Lorenzo Maccone

Quantum systems used for metrology can offer enhanced precision over their classical counterparts. The design of quantum sensors can be optimized by maximizing the quantum Fisher information (QFI), which characterizes the precision of…

Quantum Physics · Physics 2025-08-26 George Mihailescu , Anthony Kiely , Andrew K. Mitchell

It is a widely accepted fact that the computational capability of recurrent neural networks is maximized on the so-called "edge of criticality". Once the network operates in this configuration, it performs efficiently on a specific…

Data Analysis, Statistics and Probability · Physics 2017-01-06 Lorenzo Livi , Filippo Maria Bianchi , Cesare Alippi

We consider estimating the magnitude of a monochromatic AC signal that couples to a two-level sensor. For any detection protocol, the precision achieved depends on the signal's frequency and can be quantified by the quantum Fisher…

The minimum error of unbiased parameter estimation is quantified by the quantum Fisher information in accordance to the Cram\'{e}r-Rao bound. We indicate that only superposed NOON states by simultaneous measurements can achieve the maximum…

Quantum Physics · Physics 2015-05-28 Y. R. Zhang , G. R. Jin , J. P. Cao , W. M. Liu , H. Fan

We investigated quantum critical behaviours in the non-equilibrium steady state of a $XXZ$ spin chain with boundary Markovian noise using the Fisher information. The latter represents the distance between two infinitesimally close states,…

Statistical Mechanics · Physics 2017-09-19 Ugo Marzolino , Tomaž Prosen

Quantum processes with indefinite causal structure emerge when we wonder which are the most general evolutions, allowed by quantum theory, of a set of local systems which are not assumed to be in any particular causal order. These processes…

Quantum Physics · Physics 2024-02-07 Luca Apadula , Alessandro Bisio , Paolo Perinotti

We address parameter estimation for complex/structured systems and suggest an effective estimation scheme based on continuous-variables quantum probes. In particular, we investigate the use of a single bosonic mode as a probe for Ohmic…

Quantum Physics · Physics 2018-01-31 Matteo Bina , Federico Grasselli , Matteo G. A. Paris

This paper deals with the problem of estimating the coupling constant $\theta$ of a mixing quantum Markov chain. For a repeated measurement on the chain's output we show that the outcomes' time average has an asymptotically normal…

Quantum Physics · Physics 2011-06-23 Madalin Guta

Quantum Fisher information matrix (QFIM) is a core concept in theoretical quantum metrology due to the significant importance of quantum Cram\'{e}r-Rao bound in quantum parameter estimation. However, studies in recent years have revealed…

Quantum Physics · Physics 2020-03-27 Jing Liu , Haidong Yuan , Xiao-Ming Lu , Xiaoguang Wang

The quantum switch has been widely studied as a prototypical example of indefinite causal order in quantum information processing. However, the potential advantages of utilising more general forms of indefinite causal orders remain largely…

Quantum Physics · Physics 2025-01-24 Spiros Kechrimparis , James Moran , Hyukjoon Kwon

In this work, we show that the sample complexity required in quantum learning theory within a general parametric framework, is fundamentally governed by the inverse Fisher information matrix. More specifically, we derive upper and lower…

Quantum Physics · Physics 2026-03-11 Hyukgun Kwon , Seok Hyung Lie , Liang Jiang

Quantum Fisher information characterizes the phase sensitivity of qubits in the spin-boson model with a finite bandwidth spectrum. In contrast with Markovian reservoirs, the quantum Fisher information will flow from the environments to…

Quantum Physics · Physics 2015-06-18 Xiang Hao , Ninghua Tong , Shiqun Zhu

We derive an approximate expression for mutual information in a broad class of discrete-time stationary channels with continuous input, under the constraint of vanishing input amplitude or power. The approximation describes the input by its…

Information Theory · Computer Science 2015-05-19 Lubomir Kostal

The optimal measurement configuration, i.e., the optimal input quantum state and measurement in the form of a POVM with two elements, is investigated in this paper for qubit and generalized Pauli channels. The channel directions are defined…

Quantum Physics · Physics 2015-11-23 László Ruppert , Dániel Virosztek , Katalin Hangos

Multiparameter quantum estimation theory aims to determine simultaneously the ultimate precision of all parameters contained in the state of a given quantum system. Determining this ultimate precision depends on the quantum Fisher…

Quantum Physics · Physics 2020-09-15 Lahcen Bakmou , Mohammed Daoud , Rachid ahl laamara

The observables of a noisy quantum system can be estimated by appropriately filtering the records of their continuous measurement. Such filtering is relevant for state estimation and measurement-based quantum feedback control. It is…

We uncover new behaviors of the transmission of information by three quantum channels in superposition of causal orders subject to some level of noise. We find that the transmission can exhibit three different behaviors as the level of…

Quantum Physics · Physics 2021-11-08 Lorenzo M. Procopio , Francisco Delgado , Marco Enriquez , Nadia Belabas

It is common practice to collect observations of feature and response pairs from different environments. A natural question is how to identify features that have consistent prediction power across environments. The invariant causal…

Information Theory · Computer Science 2022-07-01 Austin Goddard , Yu Xiang , Ilya Soloveychik