In this paper we discuss reduced order models for the approximation of parametric eigenvalue problems. In particular, we are interested in the presence of intersections or clusters of eigenvalues. The singularities originating by these phenomena make it hard a straightforward generalization of well known strategies normally used for standards PDEs. We investigate how the known results extend (or not) to higher order frequencies.

翻译：本文讨论参数化特征值问题的降阶模型近似。我们特别关注特征值存在交叉或簇的情况。由此类现象产生的奇异性使得标准偏微分方程领域常用策略的直接推广面临困难。我们研究了已知结论如何（或不）扩展至高阶频率。