{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T23:45:59Z","timestamp":1777419959280,"version":"3.51.4"},"reference-count":25,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Model. Simul. Sci. Comput."],"published-print":{"date-parts":[[2010,6]]},"abstract":"<jats:p> In this paper, an efficient numerical procedure is presented to implement the Gaussian Runge\u2013Kutta (GRK) methods (also called Gauss methods). The GRK technique first discretizes each marching step of the initial value problem using collocation formulations based on Gaussian quadrature. As is well known, it preserves the geometric structures of Hamiltonian systems. Existing analysis shows that the GRK discretization with s nodes is of order 2s, A-stable, B-stable, symplectic and symmetric, and hence \"optimal\" for solving initial value problems of general ordinary differential equations (ODEs). However, as the unknowns at different collocation points are coupled in the discretized system, direct solution of the resulting algebraic equations is in general inefficient. Instead, we use the Krylov deferred correction (KDC) method in which the spectral deferred correction (SDC) scheme is applied as a preconditioner to decouple the original system, and the resulting preconditioned nonlinear system is solved efficiently using Newton\u2013Krylov schemes such as Newton\u2013GMRES method. The KDC accelerated GRK methods have been applied to several Hamiltonian systems and preliminary numerical results are presented to show the accuracy, stability, and efficiency features of these methods for different accuracy requirements in short- and long-time simulations. <\/jats:p>","DOI":"10.1142\/s1793962310000171","type":"journal-article","created":{"date-parts":[[2010,6,22]],"date-time":"2010-06-22T11:16:57Z","timestamp":1277205417000},"page":"277-301","source":"Crossref","is-referenced-by-count":4,"title":["IMPLEMENTING ARBITRARILY HIGH-ORDER SYMPLECTIC METHODS VIA KRYLOV DEFERRED CORRECTION TECHNIQUE"],"prefix":"10.1142","volume":"01","author":[{"given":"QUANDONG","family":"FENG","sequence":"first","affiliation":[{"name":"College of Science, Beijing Forestry University, Beijing 100083, China"},{"name":"LSEC, ICMSEC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"JINGFANG","family":"HUANG","sequence":"additional","affiliation":[{"name":"Department of Mathematics, University of North Carolina at Chapel Hill, Phillips Hall, CB #3250, NC 27599, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"NINGMING","family":"NIE","sequence":"additional","affiliation":[{"name":"LSEC, ICMSEC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"ZAIJIU","family":"SHANG","sequence":"additional","affiliation":[{"name":"Institute of Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"YIFA","family":"TANG","sequence":"additional","affiliation":[{"name":"LSEC, ICMSEC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2012,1,25]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1088\/0951-7715\/3\/2\/001"},{"key":"rf3","first-page":"173","volume":"65","author":"Feng K.","journal-title":"Comput. 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