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Werner Liniger

Researcher at IBM

Publications -  28
Citations -  2892

Werner Liniger is an academic researcher from IBM. The author has contributed to research in topics: Backward differentiation formula & Linear multistep method. The author has an hindex of 12, co-authored 28 publications receiving 2695 citations.

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Exact analysis of an interacting bose gas. i. the general solution and the ground state

TL;DR: In this paper, the ground-state energy as a function of γ was derived for all γ, except γ = 0, and it was shown that Bogoliubov's perturbation theory is valid when γ is small.
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Efficient integration methods for stiff systems of ordinary differential equations

TL;DR: In this article, linear one-step methods of a novel design are given for the numerical solution of stiff systems of ordinary differential equations, which permit fast integration with increments h of the independent variable adjusted to the slowly varying, dominant solutions.
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Symbolic Generation of an Optimal Crout Algorithm for Sparse Systems of Linear Equations

TL;DR: An efficient implementation of the Crout elimination method in solving large sparse systems of linear algebraic equations of arbitrary structure is described and is particularly powerful when a system of fixed sparseness structure must be solved repeatedly with different numerical values.
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Contractive methods for stiff differential equations part I

TL;DR: In this paper, the authors developed a theory of contractivity for methods applied to stiff and non-stiff, linear and nonlinear problems, leading to the design of a collection of specific contractive Adams-type methods of different orders of accuracy which are optimal with respect to certain measures of accuracy and/or contractivity.
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Stability of Two-Step Methods for Variable Integration Steps

TL;DR: In this paper, it was shown that there exists a one-parameter family of two-step, second-order one-leg methods which are stable for any dissipative nonlinear system and for any test problem of the form δ = δ (t)x, δ(t) \leq 0, using arbitrary step sequences.