4,835 research outputs found

    A Caratheodory theorem for the bidisk via Hilbert space methods

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    If \ph is an analytic function bounded by 1 on the bidisk \D^2 and \tau\in\tb is a point at which \ph has an angular gradient \nabla\ph(\tau) then \nabla\ph(\la) \to \nabla\ph(\tau) as \la\to\tau nontangentially in \D^2. This is an analog for the bidisk of a classical theorem of Carath\'eodory for the disk. For \ph as above, if \tau\in\tb is such that the lim inf\liminf of (1-|\ph(\la)|)/(1-\|\la\|) as \la\to\tau is finite then the directional derivative D_{-\de}\ph(\tau) exists for all appropriate directions \de\in\C^2. Moreover, one can associate with \ph and τ\tau an analytic function hh in the Pick class such that the value of the directional derivative can be expressed in terms of hh

    Facial behaviour of analytic functions on the bidisk

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    We prove that if ϕ\phi is an analytic function bounded by 1 on the bidisk and τ\tau is a point in a face of the bidisk at which ϕ\phi satisfies Caratheodory's condition then both ϕ\phi and the angular gradient ϕ\nabla\phi exist and are constant on the face. Moreover, the class of all ϕ\phi with prescribed ϕ(τ)\phi(\tau) and ϕ(τ)\nabla\phi(\tau) can be parametrized in terms of a function in the two-variable Pick class. As an application we solve an interpolation problem with nodes that lie on faces of the bidisk.Comment: 18 pages. We have replaced an erroneous proof of Theorem 5.4(1) by a valid proo

    Operator monotone functions and L\"owner functions of several variables

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    We prove generalizations of L\"owner's results on matrix monotone functions to several variables. We give a characterization of when a function of dd variables is locally monotone on dd-tuples of commuting self-adjoint nn-by-nn matrices. We prove a generalization to several variables of Nevanlinna's theorem describing analytic functions that map the upper half-plane to itself and satisfy a growth condition. We use this to characterize all rational functions of two variables that are operator monotone

    Taking a Free Ride in Morphophonemic Learning

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    As language learners begin to analyze morphologically complex words, they face the problem of projecting underlying representations from the morphophonemic alternations that they observe. Research on learnability in Optimality Theory has started to address this problem, and this article deals with one aspect of it. When alternation data tell the learner that some surface [B]s are derived from underlying /A/s, the learner will under certain conditions generalize by deriving all [B]s, even nonalternating ones, from /A/s. An adequate learning theory must therefore incorporate a procedure that allows nonalternating [B]s to take a «free ride» on the /A/ →[B] unfaithful map
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