[{"doi":"10.1016/S0168-9274(01)00126-X","page":"369-400","type":"journal_article","intvolume":" 41","_id":"1614348","user_id":"67994","status":"public","publication_identifier":{"issn":["0168-9274"]},"article_type":"original","quality_controlled":"1","date_updated":"2019-07-04T14:57:44Z","title":"Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data","author":[{"last_name":"Beyn","id":"12477","first_name":"Wolf-Jürgen","full_name":"Beyn, Wolf-Jürgen"},{"full_name":"Garay, Barnabas M.","first_name":"Barnabas M.","last_name":"Garay"}],"issue":"3","publisher":"ELSEVIER SCIENCE BV","citation":{"bio1":"Beyn W-J, Garay BM (2002)

Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data.

Applied Numerical Mathematics 41(3): 369-400.","mla":"Beyn, Wolf-Jürgen, and Garay, Barnabas M. “Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data”. *Applied Numerical Mathematics* 41.3 (2002): 369-400.","apa_indent":"Beyn, W. - J., & Garay, B. M. (2002). Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data. *Applied Numerical Mathematics*, *41*(3), 369-400. doi:10.1016/S0168-9274(01)00126-X

","ieee":" W.-J. Beyn and B.M. Garay, “Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data”, *Applied Numerical Mathematics*, vol. 41, 2002, pp. 369-400.","angewandte-chemie":"W. - J. Beyn, and B. M. Garay, “Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data”, *Applied Numerical Mathematics*, **2002**, *41*, 369-400.","chicago":"Beyn, Wolf-Jürgen, and Garay, Barnabas M. 2002. “Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data”. *Applied Numerical Mathematics* 41 (3): 369-400.

","ama":"Beyn W-J, Garay BM. Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data. *Applied Numerical Mathematics*. 2002;41(3):369-400.","frontiers":"Beyn, W. - J., and Garay, B. M. (2002). Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data. *Applied Numerical Mathematics* 41, 369-400.","default":"Beyn W-J, Garay BM (2002)

*Applied Numerical Mathematics* 41(3): 369-400.","wels":"Beyn, W. - J.; Garay, B. M. (2002): Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data *Applied Numerical Mathematics*,41:(3): 369-400.","apa":"Beyn, W. - J., & Garay, B. M. (2002). Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data. *Applied Numerical Mathematics*, *41*(3), 369-400. doi:10.1016/S0168-9274(01)00126-X","dgps":"Beyn, W.-J. & Garay, B.M. (2002). Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data. *Applied Numerical Mathematics*, *41*(3), 369-400. ELSEVIER SCIENCE BV. doi:10.1016/S0168-9274(01)00126-X.

","harvard1":"Beyn, W.-J., & Garay, B.M., 2002. Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data. *Applied Numerical Mathematics*, 41(3), p 369-400.","lncs":" Beyn, W.-J., Garay, B.M.: Estimates of variable stepsize Runge-Kutta methods for sectorial evolution equations with nonsmooth data. Applied Numerical Mathematics. 41, 369-400 (2002)."},"keyword":["sectorial operator equations","Runge-Kutta methods","nonsmooth data","variable stepsize"],"publication_status":"published","year":"2002","department":[{"_id":"10020"},{"_id":"10065"}],"publication":"Applied Numerical Mathematics","abstract":[{"lang":"eng","text":"We consider variable stepsize Runge-Kutta methods for semilinear evolution equations with a sectorial operator in the linear part. For nonsmooth initial data error estimates are derived that show the interplay of weak singularities and the classical order of convergence. There are no uniformity assumptions on the stepsizes, but we assume a Lipschitz condition for the nonlinearity and a stability function for the method that is less than I on the critical sector and vanishes at infinity. Using an extended operational calculus the proof combines a rearrangement trick with a discrete Gronwall estimate including weak singularities. Our main theorem complements respectively extends well-known results of Bakaev, Gonzalez, Lubich, Ostermann and Palencia. (C) 2001 IMACS. Published by Elsevier Science B.V. All rights reserved."}],"date_created":"2010-04-28T13:01:04Z","external_id":{"isi":["000175946500002"]},"volume":41,"language":[{"iso":"eng"}],"isi":1}]