Even though capacity of modern computers keeps growing, it has become evident over the past decades that the complexity of practically relevant problems from science and engineering has grown even faster. Without highly efficient, reliable and robust numerical methods there will be no progress in many areas. The complexity of relevant problems in turn has lead to systems of equations with an extremely large number of unknowns that need to be handled numerically. Without a significant reduction of the dimension of such systems accompanied with a mathematical analysis of accuracy, efficiency and robustness, several real-world problems will be out of reach also within the near future. This is exactly where model order reduction comes into play.

@ARTICLE{BennerOhlbergerPateraRozzaSorensenUrban2015,
author = {Benner, P. and Ohlberger, M. and Patera, A.T. and Rozza, G. and Sorensen,
D.C. and Urban, K.},
title = {Model order reduction of parameterized systems ({MoRePaS}): Preface
to the special issue of advances in computational mathematics},
journal = {Advances in Computational Mathematics},
year = {2015},
volume = {41},
pages = {955--960},
number = {5},
doi = {10.1007/s10444-015-9443-y}
}