Strict solutions to stochastic parabolic evolution equations in M-type 2 Banach spaces

We study a stochastic linear evolution equation $dX+A(t)Xdt=F(t)dt+ G(t)dw_t$ in a Banach space of M-type 2. We construct unique strict solutions to the equation on the basis of the theory of deterministic linear evolution equations. The abstract results are applied to stochastic diffusion equations.Comment: 27 pages, to appear in Funkcialaj Ekvacio

Enhanced quantum teleportation in the background of Schwarzschild spacetime by weak measurements

It is commonly believed that the fidelity of quantum teleportation in the gravitational field would be degraded due to the heat up by the Hawking radiation. In this paper, we point out that the Hawking effect could be eliminated by the combined action of pre- and post-weak measurements, and thus the teleportation fidelity is almost completely protected. It is intriguing to notice that the enhancement of fidelity could not be attributed to the improvement of entanglement, but rather to the probabilistic nature of weak measurements. Our work extends the ability of weak measurements as a quantum technique to battle against gravitational decoherence in relativistic quantum information.Comment: 9 pages, 5 figures, comments are welcom

A new class of frequently hypercyclic operators

We study a hypercyclicity property of linear dynamical systems: a bounded linear operator T acting on a separable infinite-dimensional Banach space X is said to be hypercyclic if there exists a vector x in X such that {T^{n}x : n>0} is dense in X, and frequently hypercyclic if there exists x in X such that for any non empty open subset U of X, the set {n>0 ; T^n x \in U} has positive lower density. We prove that if T is a bounded operator on X which has "sufficiently many" eigenvectors associated to eigenvalues of modulus 1 in the sense that these eigenvectors are perfectly spanning, then T is automatically frequently hypercyclic.Comment: 22 pages. To appear in Indiana Univ. Math.

How do diabetes models measure up? A review of diabetes economic models and ADA guidelines

Introduction: Economic models and computer simulation models have been used for assessing short-term cost-effectiveness of interventions and modelling long-term outcomes and costs. Several guidelines and checklists have been published to improve the methods and reporting. This article presents an overview of published diabetes models with a focus on how well the models are described in relation to the considerations described by the American Diabetes Association (ADA) guidelines. Methods: Relevant electronic databases and National Institute for Health and Care Excellence (NICE) guidelines were searched in December 2012. Studies were included in the review if they estimated lifetime outcomes for patients with type 1 or type 2 diabetes. Only unique models, and only the original papers were included in the review. If additional information was reported in subsequent or paired articles, then additional citations were included. References and forward citations of relevant articles, including the previous systematic reviews were searched using a similar method to pearl growing. Four principal areas were included in the ADA guidance reporting for models: transparency, validation, uncertainty, and diabetes specific criteria. Results: A total 19 models were included. Twelve models investigated type 2 diabetes, two developed type 1 models, two created separate models for type 1 and type 2, and three developed joint type 1 and type 2 models. Most models were developed in the United States, United Kingdom, Europe or Canada. Later models use data or methods from earlier models for development or validation. There are four main types of models: Markov-based cohort, Markov-based microsimulations, discrete-time microsimulations, and continuous time differential equations. All models were long-term diabetes models incorporating a wide range of compilations from various organ systems. In early diabetes modelling, before the ADA guidelines were published, most models did not include descriptions of all the diabetes specific components of the ADA guidelines but this improved significantly by 2004. Conclusion: A clear, descriptive short summary of the model was often lacking. Descriptions of model validation and uncertainty were the most poorly reported of the four main areas, but there exist conferences focussing specifically on the issue of validation. Interdependence between the complications was the least well incorporated or reported of the diabetes-specific criterion

Pointwise convergence of vector-valued Fourier series

We prove a vector-valued version of Carleson's theorem: Let Y=[X,H]_t be a complex interpolation space between a UMD space X and a Hilbert space H. For p\in(1,\infty) and f\in L^p(T;Y), the partial sums of the Fourier series of f converge to f pointwise almost everywhere. Apparently, all known examples of UMD spaces are of this intermediate form Y=[X,H]_t. In particular, we answer affirmatively a question of Rubio de Francia on the pointwise convergence of Fourier series of Schatten class valued functions.Comment: 26 page

On a functional contraction method

Methods for proving functional limit laws are developed for sequences of stochastic processes which allow a recursive distributional decomposition either in time or space. Our approach is an extension of the so-called contraction method to the space $\mathcal{C}[0,1]$ of continuous functions endowed with uniform topology and the space $\mathcal {D}[0,1]$ of c\`{a}dl\`{a}g functions with the Skorokhod topology. The contraction method originated from the probabilistic analysis of algorithms and random trees where characteristics satisfy natural distributional recurrences. It is based on stochastic fixed-point equations, where probability metrics can be used to obtain contraction properties and allow the application of Banach's fixed-point theorem. We develop the use of the Zolotarev metrics on the spaces $\mathcal{C}[0,1]$ and $\mathcal{D}[0,1]$ in this context. Applications are given, in particular, a short proof of Donsker's functional limit theorem is derived and recurrences arising in the probabilistic analysis of algorithms are discussed.Comment: Published at http://dx.doi.org/10.1214/14-AOP919 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

Probabilistic propositional temporal logics

We present two (closely-related) propositional probabilistic temporal logics based on temporal logics of branching time as introduced by Ben-Ari, Pnueli, and Manna (Acta Inform. 20 (1983), 207–226), Emerson and Halpern (“Proceedings, 14th ACM Sympos. Theory of Comput.,” 1982, pp. 169–179, and Emerson and Clarke (Sci. Comput. Program. 2 (1982), 241–266). The first logic, PTLf, is interpreted over finite models, while the second logic, PTLb, which is an extension of the first one, is interpreted over infinite models with transition probabilities bounded away from 0. The logic PTLf allows us to reason about finite-state sequential probabilistic programs, and the logic PTLb allows us to reason about (finite-state) concurrent probabilistic programs, without any explicit reference to the actual values of their state-transition probabilities. A generalization of the tableau method yields deterministic single-exponential time decision procedures for our logics, and complete axiomatizations of them are given. Several meta-results, including the absence of a finite-model property for PTLb, and the connection between satisfiable formulae of PTLb and finite state concurrent probabilistic programs, are also discussed