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In this paper, we study the asymptotic behavior of the volume of spheres in metric measure spaces. We first introduce a general setting adapted to the study of asymptotic isoperimetry in a general class of metric measure spaces. We then…

Metric Geometry · Mathematics 2007-05-23 R. Tessera

Symmetry principles underlie and guide scientific theory and research, from Curie's invariance formulation to modern applications across physics, chemistry, and mathematics. Building on a recent matrix Lie group measurement model, this…

Methodology · Statistics 2025-12-19 William R. Nugent

We review basic notions in the field of information geometry such as Fisher metric on statistical manifold, $\alpha$-connection and corresponding curvature following Amari's work . We show application of information geometry to asymptotic…

Statistics Theory · Mathematics 2014-10-14 Mashbat Suzuki

Accurate finite element analysis of refined shell theories is crucial but often hindered by membrane and shear locking effects. While various element-based locking-free techniques exist, this work addresses the problem at the theoretical…

Numerical Analysis · Mathematics 2025-08-26 Khanh Chau Le , Hoang-Giang Bui

In multiparameter quantum metrology, the weighted-arithmetic-mean error of estimation is often used as a scalar cost function to be minimized during design optimization. However, other types of mean error can reveal different facets of…

Quantum Physics · Physics 2020-02-12 Xiao-Ming Lu , Zhihao Ma , Chengjie Zhang

This paper proposes a class of origin-smooth approximators of indicators underlying the sum-of-negative-part statistic for testing multiple inequalities. The need for simulation or bootstrap to obtain test critical values is thereby…

Methodology · Statistics 2012-06-27 Le-Yu Chen , Jerzy Szroeter

We develop a resource theory of symmetric distinguishability, the fundamental objects of which are elementary quantum information sources, i.e., sources that emit one of two possible quantum states with given prior probabilities. Such a…

Quantum Physics · Physics 2021-08-23 Robert Salzmann , Nilanjana Datta , Gilad Gour , Xin Wang , Mark M. Wilde

Deep metrics have been shown effective as similarity measures in multi-modal image registration; however, the metrics are currently constructed from aligned image pairs in the training data. In this paper, we propose a strategy for learning…

Computer Vision and Pattern Recognition · Computer Science 2018-04-06 Alireza Sedghi , Jie Luo , Alireza Mehrtash , Steve Pieper , Clare M. Tempany , Tina Kapur , Parvin Mousavi , William M. Wells

We introduce modified generalized Wigner-Yanase-Dyson (MGWYD) skew information and modified weighted generalized Wigner-Yanase-Dyson (MWGWYD) skew information. By revisiting state-channel interaction based on MGWYD skew information, a…

Quantum Physics · Physics 2020-04-27 Zhaoqi Wu , Lin Zhang , Shao-Ming Fei , Xianqing Li-Jost

It is known that the high-dimensional quantum state space is notoriously complicated in contrast with the beautiful Bloch ball of the qubit. We examined the mechanism behind this fact in the frame work of general probabilistic theory (GPT),…

Quantum Physics · Physics 2022-03-17 Keiji Matsumoto , Gen Kimura

In this paper, we introduce a new extended version of the shallow water equations with surface tension which is skew-symmetric with respect to the L2 scalar product and allows for large gradients of fluid height. This result is a…

This paper gives an overview about particular quasi-entropies, generalized quantum covariances, quantum Fisher informations, skew-informations and their relations. The point is the dependence on operator monotone functions. It is proven…

Functional Analysis · Mathematics 2007-12-19 Denes Petz , V. E. Sandor Szabo

Flexible estimation of the mean outcome under a treatment regimen (i.e., value function) is the key step toward personalized medicine. We define our target parameter as a conditional value function given a set of baseline covariates which…

Statistics Theory · Mathematics 2023-09-29 Ashkan Ertefaie , Luke Duttweiler , Brent A. Johnson , Mark J. van der Laan

Quantum Fisher information places the fundamental limit to the accuracy of estimating an unknown parameter. Here we shall provide the quantum Fisher information an operational meaning: a mixed state can be so prepared that a given…

Quantum Physics · Physics 2013-02-22 Sixia Yu

We analyze the Shannon and Fisher information measures for systems subjected to quartic and symmetric potential wells. The wave functions are obtained by solving the time-independent Schr\"{o}dinger equation, using aspects of perturbation…

Quantum Physics · Physics 2025-01-07 Vikash Kumar Ojha , Ramkumar Radhakrishnan , Mariyah Ughradar

This paper studies the asymptotic behavior of the Fisher information for a Levy process discretely sampled at an increasing frequency. We show that it is possible to distinguish not only the continuous part of the process from its jumps…

Probability · Mathematics 2007-05-23 Yacine Ait-Sahalia , Jean Jacod

Stochastic approximation (SA) is a key method used in statistical learning. Recently, its non-asymptotic convergence analysis has been considered in many papers. However, most of the prior analyses are made under restrictive assumptions…

Machine Learning · Statistics 2019-06-18 Belhal Karimi , Blazej Miasojedow , Eric Moulines , Hoi-To Wai

In this chapter, a statistical measure of complexity and the Fisher-Shannon information product are introduced and their properties are discussed. These measures are based on the interplay between the Shannon information, or a function of…

Chaotic Dynamics · Physics 2012-01-13 Ricardo Lopez-Ruiz , Jaime Sanudo , Elvira Romera , Xavier Calbet

In the literature, quite a few measures have been proposed for quantifying the deviation of a probability distribution from symmetry. The most popular of these skewness measures are based on the third centralized moment and on quantiles.…

Statistics Theory · Mathematics 2019-08-23 Andreas Eberl , Bernhard Klar

M-type smoothing splines are a broad class of spline estimators that include the popular least-squares smoothing spline but also spline estimators that are less susceptible to outlying observations and model-misspecification. However,…

Statistics Theory · Mathematics 2025-03-06 Ioannis Kalogridis