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Related papers: Comments on Omn\`es' Model for Uniqueness of Data

200 papers

We introduce the Random Subsequence Model, a spin glass model on pairs of random strings $(X,Y) \in \{0,1\}^N \times \{0,1\}^M$ whose partition function counts subsequence embeddings of $Y$ into $X$. We study two variants: the null model,…

Information Theory · Computer Science 2026-04-09 Ryan Jeong , Francisco Pernice

We consider in this work the problem of minimizing the von Neumann entropy under the constraints that the density of particles, the current, and the kinetic energy of the system is fixed at each point of space. The unique minimizer is a…

Mathematical Physics · Physics 2019-10-29 Romain Duboscq , Olivier Pinaud

We investigate some bounds for the density of states in the pure point regime for the random Schr\"{o}dinger operators $H^{\omega}=-\Delta+\displaystyle\sum_{n\in\mathbb{Z}^d}a_nq_n(\omega)$, acting on $\ell^2(\mathbb{Z}^d)$, where…

Spectral Theory · Mathematics 2015-06-26 Dhriti Ranjan Dolai

The goal of this paper is to develop novel tools for understanding the local structure of systems of functions, e.g. time-series data points, such as the total correlation function, the Cohen class of the data set, the data operator and the…

Functional Analysis · Mathematics 2023-03-20 Monika Doerfler , Franz Luef , Eirik Skrettingland

For configurational space of arbitrary dimension a strict form of the uncertainty principle has been obtained, which takes into account the dependence of inequality limit on the effective number of pure states present in given statistical…

Quantum Physics · Physics 2009-11-06 M. U. Karelin , A. M. Lazaruk

Some concepts, such as non-compactness measure and condensing operators, defined on metric spaces are extended to uniform spaces. Such extensions allow us to locate, in the context of uniform spaces, some classical results existing in…

General Topology · Mathematics 2015-11-25 Raúl Fierro

This paper studies regularity properties of optimization-based controllers, which are obtained by solving optimization problems where the parameter is the system state and the optimization variable is the input to the system. Under a wide…

Optimization and Control · Mathematics 2024-08-08 Pol Mestres , Ahmed Allibhoy , Jorge Cortés

We develop a theory of operator renewal sequences in the context of infinite ergodic theory. For large classes of dynamical systems preserving an infinite measure, we determine the asymptotic behaviour of iterates $L^n$ of the transfer…

Dynamical Systems · Mathematics 2015-05-19 Ian Melbourne , Dalia Terhesiu

General methods of quantitative and qualitative continuity analysis of characteristics of composite quantum systems are described. Several modifications of the Alicki-Fannes-Winter method are considered, which make it applicable to a wide…

Quantum Physics · Physics 2025-02-18 M. E. Shirokov

Machine learning with density operators, the mathematical foundation of quantum mechanics, is gaining prominence with rapid advances in quantum computing. Generative models based on density operators cannot yet handle tasks that are…

Machine Learning · Computer Science 2025-12-09 Adit Vishnu , Abhay Shastry , Dhruva Kashyap , Chiranjib Bhattacharyya

An algebraic approach to the study of entanglement entropy of quantum systems is reviewed. Starting with a state on a $C^*$-algebra, one can construct a density operator describing the state in the GNS representation state. Applications of…

Quantum Physics · Physics 2022-12-12 A. F. Reyes-Lega

Inferring unbiased treatment effects has received widespread attention in the machine learning community. In recent years, our community has proposed numerous solutions in standard settings, high-dimensional treatment settings, and even…

Machine Learning · Computer Science 2024-03-19 Krzysztof Kacprzyk , Samuel Holt , Jeroen Berrevoets , Zhaozhi Qian , Mihaela van der Schaar

The methods of quantum chemistry and solid state theory to solve the many-body problem are reviewed. We start with the definitions of reduced density matrices, their properties (contraction sum rules, spectral resolutions, cumulant…

Strongly Correlated Electrons · Physics 2007-05-23 P. Ziesche , F. Tasnadi

Techniques for finding regularized solutions to underdetermined linear systems can be viewed as imposing prior knowledge on the unknown vector. The success of modern techniques, which can impose priors such as sparsity and non-negativity,…

Optimization and Control · Mathematics 2020-02-13 Keith Dillon , Yeshaiahu Fainman

We study spectral properties of random operators in the general setting of groupoids and von Neumann algebras. In particular, we establish an explicit formula for the canonical trace of the von Neumann algebra of random operators and define…

Mathematical Physics · Physics 2016-08-16 D. Lenz , N. Peyerimhoff , I. Veselić

An efficient approximate version of implicit Taylor methods for initial-value problems of systems of ordinary differential equations (ODEs) is introduced. The approach, based on an approximate formulation of Taylor methods, produces a…

Numerical Analysis · Mathematics 2024-02-05 Antonio Baeza , Raimund Bürger , María del Carmen Martí , Pep Mulet , David Zorío

To describe non-equilibrium transport processes in a quantum device with infinite baths, we propose to formulate the problems as a reduced-order problem. Starting with the Liouville-von Neumann equation for the density-matrix, the…

Mesoscale and Nanoscale Physics · Physics 2019-11-04 Weiqi Chu , Xiantao Li

Observational entropy captures both the intrinsic uncertainty of a thermodynamic state and the lack of knowledge due to coarse-graining. We demonstrate two interpretations of observational entropy, one as the statistical deficiency…

Quantum Physics · Physics 2024-11-20 Ge Bai , Dominik Šafránek , Joseph Schindler , Francesco Buscemi , Valerio Scarani

The object of the present study is the integrated density of states of a quantum particle in multi-dimensional Euclidean space which is characterized by a Schr{\"o}dinger operator with magnetic field and a random potential which may be…

Mathematical Physics · Physics 2009-11-07 Thomas Hupfer , Hajo Leschke , Peter Müller , Simone Warzel

Probabilistic solvers for ordinary differential equations (ODEs) have emerged as an efficient framework for uncertainty quantification and inference on dynamical systems. In this work, we explain the mathematical assumptions and detailed…

Machine Learning · Statistics 2021-10-25 Nicholas Krämer , Nathanael Bosch , Jonathan Schmidt , Philipp Hennig