Browsing Mathematics, Statistics, and Physics by Title
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Preface  Inverse Problems for Partial Differential Equations Third Edition Preface
(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
(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
(American Mathematical Society, 200701)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
(Springer Nature, 20210416)The Deep Underground Neutrino Experiment (DUNE) will be a powerful tool for a variety of physics topics. The highintensity proton beams provide a large neutrino flux, sampled by a near detector system consisting of a ... 
Protostellar collapse using multigroup radiation hydrodynamics
(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
(Taylor & Francis, 20181221)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 nonnegative coefficients. For the mean vectors ... 
Quantum machine learning: Preface
(De Gruyter, 20200608)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
(IEEE, 20130417)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
(Wichita State University, 202005)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 ... 
Qutritinspired fully selfsupervised shallow quantum learning network for brain tumor segmentation
(Institute of Electrical and Electronics Engineers, 20210513)Classical selfsupervised 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
(The Royal Society, 20080708)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
(Pacific Journal of Mathematics, 20160622)Consider a solution f is an element of C2 (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 R2 is a domain whose boundary ... 
Radial limits of capillary surfaces at corners
(Pacific Journal of Mathematics, 201705)Consider a solution f is an element of C2(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 R2, where Omega is a domain whose boundary ... 
Rational covariance functions for nonstationary random fields
(IEEE, 200802)This correspondence propose rationaltype 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 spatiotemporal covariance models
(SpringerVerlag, 2008)This paper briefly surveys some recent advances on how to construct spatiotemporal 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
(American Institute of Mathematical Sciences, 201403)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 timedependent volatility in option pricing model
(IOP Publishing Ltd, 20160929)In this paper we investigate an inverse problem of determining the timedependent 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
(Pacific Journal of Mathematics at the University of California, 20040601)We study mapping properties of the heat operator etA of an mth order elliptic bdifferential operator in appropriately defined spaces of whole and fractional (Hölder) derivatives. An application is made to short time ... 
Regularization via Cheeger deformations
(Springer Netherlands, 201512)We show that Cheeger deformations regularize Ginvariant metrics in a very strong sense. 
Reinforcement and backpropagation training for an optical neural network using selflensing effects
(IEEE, 200011)The optical bench training of an optical feedforward neural network, developed by the authors, is presented. The network uses an optical nonlinear material for neuron processing and a trainable applied optical pattern as ...