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A special class of doubly stochastic (Markov) operators is constructed. These operators come from measure preserving transformations and inherit some of their properties, namely ergodicity and positivity of entropy, yet they may have no…

Dynamical Systems · Mathematics 2019-01-08 Bartosz Frej

The phenomenon "hypo-coercivity," i.e., the increased rate of contraction for a semi-group upon adding a large skew-adjoint part to the generator, is considered for 1D semigroups generated by the Schr\"odinger operators $-\partial^2_x + x^2…

Mathematical Physics · Physics 2015-12-11 Jeffrey Schenker

We give properties of strict pseudocontractions and demicontractions defined on a Hilbert space, which constitute wide classes of operators that arise in iterative methods for solving fixed point problems. In particular, we give necessary…

Optimization and Control · Mathematics 2023-07-17 Andrzej Cegielski

We study a Markov process with two components: the first component evolves according to one of finitely many underlying Markovian dynamics, with a choice of dynamics that changes at the jump times of the second component. The second…

Probability · Mathematics 2015-04-14 Bertrand Cloez , Martin Hairer

In this work, we consider a class of second order uniformly elliptic operators with smooth and bounded coefficients. We provide some estimates on the norm of the semigroup generated by these operators acting on weighted Sobolev spaces,…

Analysis of PDEs · Mathematics 2022-12-06 Maxime Hauray , Yen V. Vuong

We appeal to results from combinatorial random matrix theory to deduce that various random graph $\mathrm{C}^*$-algebras are asymptotically almost surely Kirchberg algebras with trivial $K_1$. This in particular implies that, with high…

Operator Algebras · Mathematics 2025-05-22 Bhishan Jacelon , Igor Khavkine

The classical Schrodinger bridge seeks the most likely probability law for a diffusion process, in path space, that matches marginals at two end points in time; the likelihood is quantified by the relative entropy between the sought law and…

Mathematical Physics · Physics 2015-06-19 Tryphon T. Georgiou , Michele Pavon

We present a streamlined approach for generalized strong and norm convergence of self-adjoint operators in different Hilbert spaces. In particular, we establish convergence of associated (semi-)groups, (essential) spectra and spectral…

Spectral Theory · Mathematics 2026-01-16 Gerald Teschl , Yifei Wang , Bing Xie , Zhe Zhou

We study power boundedness and related properties such as mean ergodicity for (weighted) composition operators on function spaces defined by local properties. As a main application of our general approach we characterize when (weighted)…

Functional Analysis · Mathematics 2019-03-27 Thomas Kalmes

Regularity estimates for an integral operator with a symmetric continuous kernel on a convex bounded domain are derived. The covariance of a mean-square continuous random field on the domain is an example of such an operator. The estimates…

Probability · Mathematics 2022-04-25 Mihály Kovács , Annika Lang , Andreas Petersson

This work interprets and generalizes consensus-type algorithms as switching dynamics leading to symmetrization of some vector variables with respect to the actions of a finite group. We show how the symmetrization framework we develop…

Quantum Physics · Physics 2015-06-17 Luca Mazzarella , Francesco Ticozzi , Alain Sarlette

This paper considers the speed of convergence (mixing) of a finite Markov kernel $P$ with respect to the Kullback-Leibler divergence (entropy). Given a Markov kernel one defines either a discrete-time Markov chain (with the $n$-step…

Probability · Mathematics 2024-09-13 Pietro Caputo , Zongchen Chen , Yuzhou Gu , Yury Polyanskiy

In this article we develop a new abstract strategy for proving ergodicity with explicit computable rate of convergence for diffusions associated with a degenerate Kolmogorov operator L. A crucial point is that the evolution operator L may…

Functional Analysis · Mathematics 2016-01-04 Martin Grothaus , Patrik Stilgenbauer

We construct relativistic quantum Markov semigroups from covariant completely positive maps. We proceed by generalizing a step in Stinespring's dilation to a general system of imprimitivity and basing it on Poincar\'e group. The resulting…

Quantum Physics · Physics 2021-02-22 Radhakrishnan Balu

We introduce a statistical mechanics formalism for the study of constrained graph evolution as a Markovian stochastic process, in analogy with that available for spin systems, deriving its basic properties and highlighting the role of the…

Disordered Systems and Neural Networks · Physics 2015-05-13 A. C. C. Coolen , A. De Martino , A. Annibale

We study the problem of solving fixed-point equations for seminorm-contractive operators and establish foundational results on the non-asymptotic behavior of iterative algorithms in both deterministic and stochastic settings. Specifically,…

Machine Learning · Computer Science 2025-02-21 Zaiwei Chen , Sheng Zhang , Zhe Zhang , Shaan Ul Haque , Siva Theja Maguluri

We prove quantum ergodicity for a family of graphs that are obtained from ergodic one-dimensional maps of an interval using a procedure introduced by Pakonski et al (J. Phys. A, v. 34, 9303-9317 (2001)). As observables we take the L^2…

Mathematical Physics · Physics 2011-10-19 G. Berkolaiko , J. P. Keating , U. Smilansky

On a compact group the Haar probability measure plays the role of uniform distribution. The entropy and rate distortion theory for this uniform distribution is studied. New results and simplified proofs on convergence of convolutions on…

Information Theory · Computer Science 2010-05-27 Peter Harremoes

This paper deals with homogenization problem for convolution type non-local operators in random statistically homogeneous ergodic media. Assuming that the convolution kernel has a finite second moment and satisfies the uniform ellipticity…

Functional Analysis · Mathematics 2018-07-19 Andrey Piatnitski , Elena Zhizhina

We consider how to connect a set of disjoint networks to optimize the performance of the resulting composite network. We quantify this performance by the coherence of the composite network, which is defined by an $H_2$ norm of the system.…

Optimization and Control · Mathematics 2017-04-11 Erika Mackin , Stacy Patterson