Reduced order and surrogate models for gravitational waves

Abstract We present an introduction to some of the state art in reduced order and surrogate modeling gravitational-wave (GW) science. Approaches that we cover include principal component analysis, proper orthogonal (singular value) decompositions, basis approach, empirical interpolation method, quadratures, compressed likelihood evaluations. divide review into three parts: representation/compression known data, predictive models, data analysis. The targeted audience is practitioners GW science, a field which building models analysis tools are both accurate fast evaluate, especially when dealing with large amounts intensive computations, necessary yet can be challenging. As such, practical presentations and, sometimes, heuristic approaches here preferred over rigor latter not available. This aims self-contained, within reasonable page limits, little previous knowledge (at undergraduate level) requirements mathematics, scientific computing, related disciplines. Emphasis placed on optimality, as well curse dimensionality might have promise beating it. also most surrogates. Some numerical algorithms, conditioning details, scalability, parallelization other points discussed. presented extent non-intrusive (in sense no differential equations invoked) data-driven therefore applicable close open challenges high dimension surrogates, unique