scholarly journals Holographic operator mapping indS/CFTand cluster decomposition

2015 ◽  
Vol 92 (8) ◽  
Author(s):  
Atreya Chatterjee ◽  
David A. Lowe
Keyword(s):  
Operator Mapping

On the boundary operator in electromagnetic scattering

1986 ◽  
Vol 103 (1-2) ◽  
pp. 91-98 ◽  
Author(s):  
Rainer Kress
Keyword(s):  
Magnetic Field ◽  
Electric Field ◽  
Electromagnetic Scattering ◽  
Maxwell Equations ◽  
Boundary Operator ◽  
Hölder Continuous ◽  
Operator Mapping ◽  
Time Harmonic ◽  
Continuous Surface ◽  
The Magnetic Field

SynopsisFor radiating solutions to the time-harmonic Maxwell equations, it is shown that the boundary operator mapping the tangential components of the electric field into the tangential components of the magnetic field is a bounded bijective operator from the space of Holder continuous tangential fields with Hölder continuous surface divergence onto itself.

The renewal-process stationary-excess operator

1985 ◽  
Vol 22 (01) ◽  
pp. 156-167 ◽  
Author(s):  
Ward Whitt
Keyword(s):  
Renewal Process ◽  
Stochastic Order ◽  
Expected Value ◽  
Operator Mapping ◽  
Usual Stochastic Order ◽  
Convergence Results ◽  
Decreasing Functions ◽  
Interval Distribution

This paper describes the operator mapping a renewal-interval distribution into its associated stationary-excess distribution. This operator is monotone for some kinds of stochastic order, but not for the usual stochastic order determined by the expected value of all non-decreasing functions. Conditions for a renewal-interval distribution to be larger or smaller than its associated stationary-excess distribution for several kinds of stochastic order are determined in terms of familiar notions of ageing. Convergence results are also obtained for successive iterates of the operator, which supplement Harkness and Shantaram (1969), (1972) and van Beek and Braat (1973).

The renewal-process stationary-excess operator

1985 ◽  
Vol 22 (1) ◽  
pp. 156-167 ◽  
Author(s):  
Ward Whitt
Keyword(s):  
Renewal Process ◽  
Stochastic Order ◽  
Expected Value ◽  
Operator Mapping ◽  
Usual Stochastic Order ◽  
Convergence Results ◽  
Decreasing Functions ◽  
Interval Distribution

This paper describes the operator mapping a renewal-interval distribution into its associated stationary-excess distribution. This operator is monotone for some kinds of stochastic order, but not for the usual stochastic order determined by the expected value of all non-decreasing functions. Conditions for a renewal-interval distribution to be larger or smaller than its associated stationary-excess distribution for several kinds of stochastic order are determined in terms of familiar notions of ageing. Convergence results are also obtained for successive iterates of the operator, which supplement Harkness and Shantaram (1969), (1972) and van Beek and Braat (1973).

scholarly journals A New Essential Norm Estimate of Composition Operators from Weighted Bloch Space into -Bloch Spaces

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
René E. Castillo ◽  
Julio C. Ramos-Fernández ◽  
Edixon M. Rojas
Keyword(s):  
Weight Function ◽  
Unit Disk ◽  
Composition Operator ◽  
Special Function ◽  
Composition Operators ◽  
Bloch Space ◽  
Essential Norm ◽  
Bloch Spaces ◽  
Norm Estimate ◽  
Operator Mapping

Let be any weight function defined on the unit disk and let be an analytic self-map of . In the present paper, we show that the essential norm of composition operator mapping from the weighted Bloch space to -Bloch space is comparable to where for ,   is a certain special function in the weighted Bloch space. As a consequence of our estimate, we extend the results about the compactness of composition operators due to Tjani (2003).

scholarly journals Quantum information scrambling through a high-complexity operator mapping

2019 ◽  
Vol 100 (3) ◽  
Author(s):  
Xiaopeng Li ◽  
Guanyu Zhu ◽  
Muxin Han ◽  
Xin Wang
Keyword(s):  
Quantum Information ◽  
High Complexity ◽  
Operator Mapping

scholarly journals RESOURCE ALLOCATION STRATEGIES FOR CONSTRUCTIVE IN-NETWORK STREAM PROCESSING

2011 ◽  
Vol 22 (03) ◽  
pp. 621-638 ◽  
Author(s):  
ANNE BENOIT ◽  
VERONIKA REHN-SONIGO ◽  
YVES ROBERT ◽  
HENRI CASANOVA
Keyword(s):  
Steady State ◽  
Relational Databases ◽  
Stream Processing ◽  
Mapping Problem ◽  
Operator Mapping ◽  
Multiple Data ◽  
Np Complete ◽  
Data Objects ◽  
The Cost ◽  
Allocation Strategies

In this paper we consider the operator mapping problem for in-network stream processing applications. In-network stream processing consists in applying a tree of operators in steady-state to multiple data objects that are continually updated at various locations on a network. Examples of in-network stream processing include the processing of data in a sensor network, or of continuous queries on distributed relational databases. We study the operator mapping problem in a "constructive" scenario, i.e., a scenario in which one builds a platform dedicated to the application by purchasing processing servers with various costs and capabilities. The objective is to minimize the cost of the platform while ensuring that the application achieves a minimum steady-state throughput. The first contribution of this paper is the formalization of a set of relevant operator-placement problems, and a proof that even simple versions of the problem are NP-complete. Our second contribution is the design of several polynomial time heuristics, which are evaluated via extensive simulations and compared to theoretical bounds for optimal solutions.

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