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Signal processing techniques will lean on blind methods in the near future, where no redundant, resource allocating information will be transmitted through the channel. To achieve a proper decision, however, it is essential to know at least…

Quantum Physics · Physics 2007-05-23 Ferenc Balázs , Sándor Imre

It has long been agreed by academics that the inversion method is the method of choice for generating random variates, given the availability of the quantile function. However for several probability distributions arising in practice a…

Computational Finance · Quantitative Finance 2012-04-03 Asad Munir , William Shaw

Fisher's information measure plays a very important role in diverse areas of theoretical physics. The associated measures as functionals of quantum probability distributions defined in, respectively, coordinate and momentum spaces, are the…

Quantum Physics · Physics 2015-04-20 Angelo Plastino , Guido Bellomo , Angel R. Plastino

The minimum achievable statistical uncertainty in the estimation of physical parameters is determined by the quantum Fisher information. Its computation for noisy systems is still a challenging problem. Using a variational approach, we…

Quantum Physics · Physics 2012-11-21 B. M. Escher , L. Davidovich , N. Zagury , R. L. de Matos Filho

A factor-graph representation of quantum-mechanical probabilities (involving any number of measurements) is proposed. Unlike standard statistical models, the proposed representation uses auxiliary variables (state variables) that are not…

Information Theory · Computer Science 2017-06-13 Hans-Andrea Loeliger , Pascal O. Vontobel

In the recent years, information theory of quantum-mechanical systems have aroused the interest of many Theoretical Physicist. This due to the fact that it provides a deeper insight into the internal structure of the systems. Also, It is…

Quantum Physics · Physics 2014-08-18 B. J. Falaye , K. J. Oyewumi , S. M. Ikhdair , M. Hamzavi

This is a review about financial dependencies which merges efforts in econophysics and financial economics during the last few years. We focus on the most relevant contributions to the analysis of asset markets' dependencies, especially…

Statistical Finance · Quantitative Finance 2023-02-17 M. Raddant , T. Di Matteo

In this paper, the classical problem of the probabilistic characterization of a random variable is re-examined. A random variable is usually described by the probability density function (PDF) or by its Fourier transform, namely the…

Mathematical Physics · Physics 2013-01-22 Giulio Cottone , Mario Di Paola

The Bayesian decision-theoretic approach to design of experiments involves specifying a design (values of all controllable variables) to maximise the expected utility function (expectation with respect to the distribution of responses and…

Statistics Theory · Mathematics 2021-09-24 Antony M. Overstall

We study Heisenberg scaling of quantum metrology in the viewpoint of population coding. Although Fisher information has been used for a figure of merit to characterize Heisenberg scaling in quantum metrology, several studies pointed out it…

Quantum Physics · Physics 2025-03-05 Masahito Hayashi

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

We theoretically investigate parameter quantum estimation in quantum chaotic systems. Our analysis is based on an effective description of non-integrable quantum systems in terms of a random matrix Hamiltonian. Based on this approach we…

The objective of this work is the investigation of complexity, asymmetry, stochasticity and non-linearity of the financial and economic systems by using the tools of statistical mechanics and information theory. More precisely, this thesis…

Statistical Finance · Quantitative Finance 2024-08-30 Rubina Zadourian

In this paper, we review Fisher information matrices properties in weighted version and discuss inequalities/bounds on it by using reduced weight functions. In particular, an extended form of the Fisher information inequality previously…

Information Theory · Computer Science 2016-02-01 Mark Kelbert , Yuri Suhov , Salimeh Yasaei Sekeh

Preconditioning with the quantum Fisher information matrix (QFIM) is a popular approach in quantum variational algorithms. Yet the QFIM is costly to obtain directly, usually requiring more state preparation than its classical counterpart:…

Quantum Physics · Physics 2026-04-09 Jianfeng Lu , Kecen Sha

The relevance of the concept of Fisher information is increasing in both statistical physics and quantum computing. From a statistical mechanical standpoint, the application of Fisher information in the kinetic theory of gases is…

Quantum Physics · Physics 2018-05-09 Carlo Cafaro , Paul M. Alsing

We show how the quantum potential arises in various ways and trace its connection to quantum fluctuations and Fisher information along with its realization in terms of Weyl curvature. It is a quantization factor for certain classical…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Robert Carroll

Recent work has suggested that in highly correlated systems, such as sandpiles, turbulent fluids, ignited trees in forest fires and magnetization in a ferromagnet close to a critical point, the probability distribution of a global quantity…

Statistical Mechanics · Physics 2020-01-29 Sandra Chapman , George Rowlands , Nicholas Watkins

The econophysics approach to socio-economic systems is based on the assumption of their complexity. Such assumption inevitably lead to another assumption, namely that underlying interconnections within socio-economic systems, particularly…

Statistical Finance · Quantitative Finance 2023-07-19 Paweł Fiedor

We consider the problems of clustering, classification, and visualization of high-dimensional data when no straightforward Euclidean representation exists. Typically, these tasks are performed by first reducing the high-dimensional data to…

Machine Learning · Statistics 2009-09-29 Kevin M. Carter , Raviv Raich , William G. Finn , Alfred O. Hero