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In this short paper, the commutator of monomials of operators obeying constant commutation relations is expressed in terms of anticommutators. The formula involves Bernoulli numbers or Euler polynomials evaluated in zero. The role of…

Mathematical Physics · Physics 2020-04-14 Jean-Christophe Pain

It is known that non-commuting observables in quantum mechanics do not have joint probability. This statement refers to the precise (additive) probability model. I show that the joint distribution of any non-commuting pair of variables can…

Quantum Physics · Physics 2015-09-02 A. E. Allahverdyan

Given discrete time observations over a fixed time interval, we study a nonparametric Bayesian approach to estimation of the volatility coefficient of a stochastic differential equation. We postulate a histogram-type prior on the volatility…

Methodology · Statistics 2019-04-01 Shota Gugushvili , Frank van der Meulen , Moritz Schauer , Peter Spreij

We propose a generalization of Heisenberg picture quantum mechanics in which a Lagrangian and Hamiltonian dynamics is formulated directly for dynamical systems on a manifold with non--commuting coordinates, which act as operators on an…

High Energy Physics - Theory · Physics 2010-11-01 Stephen L. Adler

We study analytic models of operators of class $C_{\cdot 0}$ with natural positivity assumptions. In particular, we prove that for an $m$-hypercontraction $T \in C_{\cdot 0}$ on a Hilbert space $\mathcal{H}$, there exists a Hilbert space…

Functional Analysis · Mathematics 2016-02-26 Monojit Bhattacharjee , Jaydeb Sarkar

We propose a natural strategy to deal with compatible and incompatible binary questions, and with their time evolution. The strategy is based on the simplest, non-commutative, Hilbert space $\mathcal{H}=\mathbb{C}^2$, and on the (commuting…

Physics and Society · Physics 2019-06-26 Fabio Bagarello

We consider discrete nonparametric priors which induce Gibbs-type exchangeable random partitions and investigate their posterior behavior in detail. In particular, we deduce conditional distributions and the corresponding Bayesian…

Probability · Mathematics 2008-08-22 Antonio Lijoi , Igor Prünster , Stephen G. Walker

Gibbs-type random probability measures and the exchangeable random partitions they induce represent the subject of a rich and active literature. They provide a probabilistic framework for a wide range of theoretical and applied problems…

Statistics Theory · Mathematics 2015-04-06 Sergio Bacallado , Stefano Favaro , Lorenzo Trippa

We present a simple operator perturbation theory in the backward Heisenberg picture. Compared with the well-known Heisenberg picture, the revised picture is based on the backward time instead of the forward time. The unique feature of the…

Quantum Physics · Physics 2012-04-24 Fei Liu , Ding-yang Liu

We obtain the Baxter Q-operators in the $U_q(\hat{sl}_2)$ invariant integrable models as a special limits of the quantum transfer matrices corresponding to different spins in the auxiliary space both from the functional relations and from…

Mathematical Physics · Physics 2015-06-23 A. A. Ovchinnikov

We present a generalization of bilateral weighted shift operators for the noncommutative multivariable setting. We discover a notion of periodicity for these shifts, which has an appealing diagramatic interpretation in terms of an infinite…

Operator Algebras · Mathematics 2007-05-23 David W. Kribs

This paper presents a few additions to commutant lifting theory. An operator interpolation problem is introduced and shown to be equivalent to the relaxed commutant lifting problem. Using this connection a description of all solutions of…

Functional Analysis · Mathematics 2007-05-23 A. E. Frazho , S. ter Horst , M. A. Kaashoek

We consider the approximation of the inverse square root of regularly accretive operators in Hilbert spaces. The approximation is of rational type and comes from the use of the Gauss-Legendre rule applied to a special integral formulation…

Numerical Analysis · Mathematics 2022-02-04 Eleonora Denich , Paolo Novati

We consider Bayesian inverse problems wherein the unknown state is assumed to be a function with discontinuous structure a priori. A class of prior distributions based on the output of neural networks with heavy-tailed weights is…

Machine Learning · Computer Science 2021-12-21 Chen Li , Matthew Dunlop , Georg Stadler

A quality-Bayesian approach, combining the direct sampling method and the Bayesian inversion, is proposed to reconstruct the locations and intensities of the unknown acoustic sources using partial data. First, we extend the direct sampling…

Numerical Analysis · Mathematics 2020-04-10 Zhaoxing Li , Yanfang Liu , Jiguang Sun , Liwei Xu

We consider a two-point spatial lattice approximation to an open string moving in a flat background with B field. It gives a constrained dipole system under the influence of a vector potential. Solving and quantizing this system recover all…

High Energy Physics - Theory · Physics 2009-10-31 Zheng Yin

In these notes, we investigate the tail behaviour of the norm of subgaussian vectors in a Hilbert space. The subgaussian variance proxy is given as a trace class operator, allowing for a precise control of the moments along each dimension…

Probability · Mathematics 2023-10-04 Mattes Mollenhauer , Claudia Schillings

Uncertainty relations between two general non-commuting self-adjoint operators are derived in a Krein space. All of these relations involve a Krein space induced fundamental symmetry operator, $J$, while some of these generalized relations…

Quantum Physics · Physics 2021-03-09 Sirous Homayouni , Angelo B. Mingarelli

A key notion bridging the gap between {\it quantum operator algebras} \cite{LZ10} and {\it vertex operator algebras} \cite{Bor}\cite{FLM} is the definition of the commutativity of a pair of quantum operators (see section 2 below). This is…

q-alg · Mathematics 2008-02-03 Bong H. Lian , Gregg J. Zuckerman

In the Bayesian approach, the a priori knowledge about the input of a mathematical model is described via a probability measure. The joint distribution of the unknown input and the data is then conditioned, using Bayes' formula, giving rise…

Statistics Theory · Mathematics 2015-06-15 Sebastian J. Vollmer