[{"author":[{"id":"33931","first_name":"Bernhard","last_name":"Bachmann","orcid":"0000-0002-4339-0438","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4339-0438/work/202504183","full_name":"Bachmann, Bernhard"},{"full_name":"Bonaventura, Luca","last_name":"Bonaventura","first_name":"Luca"},{"full_name":"Casella, Francesco","first_name":"Francesco","last_name":"Casella"},{"first_name":"Soledad","last_name":"Fernández-García","full_name":"Fernández-García, Soledad"},{"full_name":"Gómez-Mármol, Macarena","last_name":"Gómez-Mármol","first_name":"Macarena"},{"id":"221456","first_name":"Philip","last_name":"Hannebohm","orcid":"0009-0003-8902-9079","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0003-8902-9079/work/202504184","full_name":"Hannebohm, Philip"}],"_id":"6445","intvolume":"       105","citation":{"chicago":"Bachmann, Bernhard, Luca Bonaventura, Francesco Casella, Soledad Fernández-García, Macarena Gómez-Mármol, and Philip Hannebohm. “Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework.” <i>Journal of Scientific Computing</i> 105, no. 1 (2025). <a href=\"https://doi.org/10.1007/s10915-025-03049-y\">https://doi.org/10.1007/s10915-025-03049-y</a>.","apa":"Bachmann, B., Bonaventura, L., Casella, F., Fernández-García, S., Gómez-Mármol, M., &#38; Hannebohm, P. (2025). Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework. <i>Journal of Scientific Computing</i>, <i>105</i>(1). <a href=\"https://doi.org/10.1007/s10915-025-03049-y\">https://doi.org/10.1007/s10915-025-03049-y</a>","bibtex":"@article{Bachmann_Bonaventura_Casella_Fernández-García_Gómez-Mármol_Hannebohm_2025, title={Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework}, volume={105}, DOI={<a href=\"https://doi.org/10.1007/s10915-025-03049-y\">10.1007/s10915-025-03049-y</a>}, number={130}, journal={Journal of Scientific Computing}, publisher={Springer Science and Business Media LLC}, author={Bachmann, Bernhard and Bonaventura, Luca and Casella, Francesco and Fernández-García, Soledad and Gómez-Mármol, Macarena and Hannebohm, Philip}, year={2025} }","ama":"Bachmann B, Bonaventura L, Casella F, Fernández-García S, Gómez-Mármol M, Hannebohm P. Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework. <i>Journal of Scientific Computing</i>. 2025;105(1). doi:<a href=\"https://doi.org/10.1007/s10915-025-03049-y\">10.1007/s10915-025-03049-y</a>","short":"B. Bachmann, L. Bonaventura, F. Casella, S. Fernández-García, M. Gómez-Mármol, P. Hannebohm, Journal of Scientific Computing 105 (2025).","alphadin":"<span style=\"font-variant:small-caps;\">Bachmann, Bernhard</span> ; <span style=\"font-variant:small-caps;\">Bonaventura, Luca</span> ; <span style=\"font-variant:small-caps;\">Casella, Francesco</span> ; <span style=\"font-variant:small-caps;\">Fernández-García, Soledad</span> ; <span style=\"font-variant:small-caps;\">Gómez-Mármol, Macarena</span> ; <span style=\"font-variant:small-caps;\">Hannebohm, Philip</span>: Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework. In: <i>Journal of Scientific Computing</i> Bd. 105, Springer Science and Business Media LLC (2025), Nr. 1","mla":"Bachmann, Bernhard, et al. “Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework.” <i>Journal of Scientific Computing</i>, vol. 105, no. 1, 30, Springer Science and Business Media LLC, 2025, doi:<a href=\"https://doi.org/10.1007/s10915-025-03049-y\">10.1007/s10915-025-03049-y</a>.","ieee":"B. Bachmann, L. Bonaventura, F. Casella, S. Fernández-García, M. Gómez-Mármol, and P. Hannebohm, “Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework,” <i>Journal of Scientific Computing</i>, vol. 105, no. 1, 2025."},"main_file_link":[{"open_access":"1"}],"language":[{"iso":"eng"}],"publication_identifier":{"eissn":["1573-7691"],"issn":["0885-7474"]},"user_id":"250307","publication_status":"published","date_created":"2026-01-14T16:03:23Z","date_updated":"2026-06-09T07:23:49Z","publication":"Journal of Scientific Computing","status":"public","project":[{"_id":"f432a2ee-bceb-11ed-a251-a83585c5074d","name":"Institute for Data Science Solutions"}],"title":"Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework","oa":"1","publisher":"Springer Science and Business Media LLC","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"volume":105,"issue":"1","doi":"10.1007/s10915-025-03049-y","type":"journal_article","year":"2025","article_type":"original","article_number":"30"}]