Now showing items 278-297 of 394

    • Preface -- Inverse Problems for Partial Differential Equations First Edition Preface 

      Isakov, Victor, 1947- (Springer, 2017)
      This book describes the contemporary state of the theory and some numerical aspects of inverse problems in partial differential equations. The topic is of substantial and growing interest for many scientists and engineers ...
    • Preface -- Inverse Problems for Partial Differential Equations Second Edition Preface 

      Isakov, Victor, 1947- (Springer, 2017)
      In 8 years after the publication of the first version of this book, the rapidly progressing field of inverse problems witnessed changes and new developments. Parts of the book were used at several universities, and many ...
    • Preface -- Inverse Problems for Partial Differential Equations Third Edition Preface 

      Isakov, Victor, 1947- (Springer, 2017)
      In 10 years after the publication of the second edition of this book, the changing field of inverse problems witnessed further new developments. Parts of the book were used at several universities, and many colleagues and ...
    • Programming quantum annealing computers using machine learning 

      Behrman, Elizabeth C.; Steck, James E. (IEEE, 2017)
      Commercial quantum annealing (QA) machines are now being built with hundreds of quantum bits (qubits). These are used as analog computers, to solve optimization problems by annealing to an unknown ground state (the solution), ...
    • Properties of fixed point sets and a characterization of the ball in Cn 

      Fridman, Buma L.; Ma, Daowei (American Mathematical Society, 2007-01)
      We study the fixed point sets of holomorphic selfmaps of a bounded domain in Cn. Specifically we investigate the least number of fixed points in general position in the domain that forces any automorphism (or endomorphism) ...
    • Prospects for beyond the Standard Model physics searches at the Deep Underground Neutrino Experiment: DUNE collaboration 

      Abi, B.; Acciarri, R.; Acero, Mario A.; Meyer, Holger; Muether, Mathew; Solomey, Nickolas (Springer Nature, 2021-04-16)
      The Deep Underground Neutrino Experiment (DUNE) will be a powerful tool for a variety of physics topics. The high-intensity proton beams provide a large neutrino flux, sampled by a near detector system consisting of a ...
    • Protostellar collapse using multigroup radiation hydrodynamics 

      Vaytet, Neil; Chabrier, Gilles; Audit, Edouard; Commercon, Benoit; Masson, Jacques; Gonzalez, Matthias; Ferguson, Jason W.; Delahaye, Franck (Astronomical Society of the Pacific, 2015)
      Many simulations of protostellar collapse make use of a grey treatment of radiative transfer coupled to the hydrodynamics. However, interstellar gas and dust opacities present large variations as a function of frequency. ...
    • A pseudo restricted MLE under multivariate order restrictions and its algorithm 

      Hu, Xiaomi (Taylor & Francis, 2018-12-21)
      It is shown in this paper that a quasi order for the vectors in Rp is a cone induced if and only if the order is preservable under limits and under linear combinations with non-negative coefficients. For the mean vectors ...
    • Quantum machine learning: Preface 

      Bhattacharyya, Siddhartha; Pan, Indrajit; Mani, Ashish; De, Sourav; Behrman, Elizabeth C.; Chakrabarti, Susanta (De Gruyter, 2020-06-08)
      Imparting intelligence to the machines has always been a challenging thoroughfare. Over the years, several intelligent tools have been invented or proposed to deal with the uncertainties encountered by human beings with ...
    • A quantum neural network computes its own relative phase 

      Behrman, Elizabeth C.; Steck, James E. (IEEE, 2013-04-17)
      Complete characterization of the state of a quantum system made up of subsystems requires determination of relative phase, because of interference effects between the subsystems. For a system of qubits used as a quantum ...
    • Quantum neural networks 

      Nguyen, Nam H. (Wichita State University, 2020-05)
      Quantum computing is becoming a reality, at least on a small scale. However, designing a good quantum algorithm is still a challenging task. This has been a huge major bottleneck in quantum computation for years. In this ...
    • Qutrit-inspired fully self-supervised shallow quantum learning network for brain tumor segmentation 

      Konar, Debanjan; Bhattacharyya, Siddhartha; Panigrahi, Bijaya K.; Behrman, Elizabeth C. (Institute of Electrical and Electronics Engineers, 2021-05-13)
      Classical self-supervised networks suffer from convergence problems and reduced segmentation accuracy due to forceful termination. Qubits or bilevel quantum bits often describe quantum neural network models. In this article, ...
    • Radial and circular slit maps of unbounded multiply connected circle domains 

      DeLillo, Thomas K.; Driscoll, T. A.; Elcrat, Alan R.; Pfaltzgraff, J. A. (The Royal Society, 2008-07-08)
      Infinite product formulae for conformally mapping an unbounded multiply connected circle domain to an unbounded canonical radial or circular slit domain, or to domains with both radial and circular slit boundary components ...
    • Radial limits of bounded nonparametric prescribed mean curvature surfaces 

      Entekhabi, Mozhgan (Nora); Lancaster, Kirk E. (Pacific Journal of Mathematics, 2016-06-22)
      Consider a solution f is an element of C-2 (Omega)of a prescribed mean curvature equation div del f/root 1+vertical bar del f vertical bar(2) = 2H(x, f) in Omega, where Omega subset of R-2 is a domain whose boundary ...
    • Radial limits of capillary surfaces at corners 

      Entekhabi, Mozhgan (Nora); Lancaster, Kirk E. (Pacific Journal of Mathematics, 2017-05)
      Consider a solution f is an element of C-2(Omega) of a prescribed mean curvature equation div del f/root 1+vertical bar del f vertical bar(2) = 2H (x, f) in Omega subset of R-2, where Omega is a domain whose boundary ...
    • Rational covariance functions for nonstationary random fields 

      Ma, Chunsheng (IEEE, 2008-02)
      This correspondence propose rational-type covariance functions for nonstationary Gaussian stochastic processes or random fields, which are rational functions of given variograms, typically have long range dependence, ...
    • Recent developments on the construction of spatio-temporal covariance models 

      Ma, Chunsheng (Springer-Verlag, 2008)
      This paper briefly surveys some recent advances on how to construct spatio-temporal covariance functions, with the emphasis on the methods which can be used to derive covariance functions but not on a summary list of ...
    • Recovery of time dependent volatility coefficient by linearization 

      Isakov, Victor, 1947- (American Institute of Mathematical Sciences, 2014-03)
      We study the problem of reconstruction of special time dependent local volatility from market prices of options with different strikes at two expiration times. For a general diffusion process we apply the linearization ...
    • Recovery of time-dependent volatility in option pricing model 

      Deng, Zui-Cha; Hon, Y. C.; Isakov, Victor, 1947- (IOP Publishing Ltd, 2016-09-29)
      In this paper we investigate an inverse problem of determining the time-dependent volatility from observed market prices of options with different strikes. Due to the non linearity and sparsity of observations, an analytical ...
    • Regularity of the heat operator on a manifold with cylindrical ends 

      Jeffres, Thalia D.; Loya, Paul (Pacific Journal of Mathematics at the University of California, 2004-06-01)
      We study mapping properties of the heat operator etA of an m-th order elliptic b-differential operator in appropriately defined spaces of whole and fractional (Hölder) derivatives. An application is made to short time ...