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Cone type majorization and its strong linear preservers
The Electronic Journal of Linear Algebra, 2020 This study introduces a novel notion, cone type majorization and characterizes the same. Further, the structure of linear preservers and strong linear preservers of this cone type majorization have been studied.
Kosuru, G. Sankara Raju, Saha, Subhajit
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SGLT-MAJORIZATION ON Mn,m AND ITS LINEAR PRESERVERS [PDF]
Journal of Mahani Mathematical Research, 2018 A matrix R is said to be g-row substochastic if Re ≤ e. For X, Y ∈ Mn,m, it is said that X is sglt-majorized by Y , X ≺sglt Y , if there exists an n-by-n lower triangular g-row substochastic matrix R such that X = RY .
Asma Ilkhanizadeh Manesh
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Strong Stability Preserving Runge–Kutta and Linear Multistep Methods
Bulletin of the Iranian Mathematical Society, 2022 AbstractThis paper reviews strong stability preserving discrete variable methods for differential systems. The strong stability preserving Runge–Kutta methods have been usually investigated in the literature on the subject, using the so-called Shu–Osher representation of these methods, as a convex combination of first-order steps by forward Euler ...
Izzo G., Jackiewicz Z.
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Linear Transformations Preserving the Strong $q$-log-convexity of Polynomials
The Electronic Journal of Combinatorics, 2015 In this paper, we give a sufficient condition for the linear transformation preserving the strong $q$-log-convexity. As applications, we get some linear transformations (for instance, Morgan-Voyce transformation, binomial transformation, Narayana transformations of two kinds) preserving the strong $q$-log-convexity.
Bao-Xuan Zhu, Hua Sun
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Strong-stability-preserving additive linear multistep methods
Mathematics of Computation, 2018 The analysis of strong-stability-preserving (SSP) linear multistep methods is extended to semi-discretized problems for which different terms on the right-hand side satisfy different forward Euler (or circle) conditions. Optimal perturbed and additive monotonicity-preserving linear multistep methods are studied in the context of such problems.
Yiannis Hadjimichael, David I. Ketcheson
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Strong Stability Preserving Explicit Linear Multistep Methods with Variable Step Size [PDF]
SIAM Journal on Numerical Analysis, 2016 Strong stability preserving (SSP) methods are designed primarily for time integration of nonlinear hyperbolic PDEs, for which the permissible SSP step size varies from one step to the next. We develop the first SSP linear multistep methods (of order two and three) with variable step size, and prove their optimality, stability, and convergence.
Yiannis Hadjimichael +3 more
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Implicit and Implicit–Explicit Strong Stability Preserving Runge–Kutta Methods with High Linear Order [PDF]
Journal of Scientific Computing, 2017 When evolving in time the solution of a hyperbolic partial differential equation, it is often desirable to use high order strong stability preserving (SSP) time discretizations. These time discretizations preserve the monotonicity properties satisfied by the spatial discretization when coupled with the first order forward Euler, under a certain time ...
Sidafa Conde +3 more
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Computation of Optimal Linear Strong Stability Preserving Methods Via Adaptive Spectral Transformations of Poisson–Charlier Measures [PDF]
Journal of Scientific Computing, 2021 50 pages, 5 ...
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Optimal explicit strong stability preserving Runge–Kutta methods with high linear order and optimal nonlinear order [PDF]
Mathematics of Computation, 2015 High order spatial discretizations with monotonicity properties are often desirable for the solution of hyperbolic PDEs. These methods can advantageously be coupled with high order strong stability preserving time discretizations. The search for high order strong stability time-stepping methods with large allowable strong stability
Sigal Gottlieb +2 more
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Strong linear preservers of symmetric doubly stochastic or doubly substochastic matrices
Linear Algebra and its Applications, 2004 The authors present some results about LOCC graphs, i.e. graphs with particular connected components, and by means of them improve some results due to \textit{C. K. Li, B. S. Tam}, and \textit{N. K. Tsing} [Linear Algebra Appl. 341, 5--22 (2002; Zbl 0998.15004)].
Lin, Shwu-Huey, Tam, Bit-Shun
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