2014
DOI: 10.1007/s11075-014-9825-0
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Efficient implementation of Gauss collocation and Hamiltonian boundary value methods

Abstract: In this paper we define an efficient implementation for the family of low-rank energy-conserving Runge-Kutta methods named Hamiltonian Boundary Value Methods (HBVMs), recently defined in the last years. The proposed implementation relies on the particular structure of the Butcher matrix defining such methods, for which we can derive an efficient splitting procedure. The very same procedure turns out to be automatically suited for the efficient implementation of Gauss-Legendre collocation methods, since these m… Show more

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Cited by 62 publications
(107 citation statements)
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“…Problem (51) can then be solved by using a HBVM(k, s) method, for which the accuracy results of Theorem 1 hold true. In particular, concerning the conservation of the semi-discrete Hamiltonian (52), the next result holds true, which follows from (11).…”
Section: Discretizationmentioning
confidence: 72%
“…Problem (51) can then be solved by using a HBVM(k, s) method, for which the accuracy results of Theorem 1 hold true. In particular, concerning the conservation of the semi-discrete Hamiltonian (52), the next result holds true, which follows from (11).…”
Section: Discretizationmentioning
confidence: 72%
“…having dimension s times larger than that of f ′ (y 0 ). It can be proved that this iteration can be conveniently replaced by a corresponding blended iteration [30,42,43] which, having set †…”
Section: Hamiltonian Boundary Value Methodsmentioning
confidence: 99%
“…This iteration, at first devised in [25,28] for block implicit methods, has been implemented in the computational codes BiM [26], for stiff ODE-IVPs, and BiMD [27], also solving DAEs. Later on, it has been considerd for HBVMs [9,16,22] and, more recently, for RKN-type methods [53]. It is worth mentioning that, in the case of HBVMs, it has allowed their usage as spectral methods in time [3,18,29], because the use of relatively large stepsizes has been made possible.…”
Section: Solving the Discrete Problemmentioning
confidence: 99%