<p>We investigate critical points of eigencurves of bivariate matrix pencils <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(A+\lambda B +\mu C\)</EquationSource> </InlineEquation>. Points <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\((\lambda ,\mu )\)</EquationSource> </InlineEquation> for which <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\det (A+\lambda B+\mu C)=0\)</EquationSource> </InlineEquation> form algebraic curves in <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\({\mathbb {C}}^2\)</EquationSource> </InlineEquation> and we focus on points where <InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(\mu '(\lambda )=0\)</EquationSource> </InlineEquation>. Such points are referred to as zero-group-velocity (ZGV) points, following terminology from engineering applications. We provide a general theory for the ZGV points and show that they form a subset (with equality in the generic case) of the 2D points <InlineEquation ID="IEq6"> <EquationSource Format="TEX">\((\lambda _0,\mu _0)\)</EquationSource> </InlineEquation>, where <InlineEquation ID="IEq7"> <EquationSource Format="TEX">\(\lambda _0\)</EquationSource> </InlineEquation> is a multiple eigenvalue of the pencil <InlineEquation ID="IEq8"> <EquationSource Format="TEX">\((A+\mu _0 C)+\lambda B\)</EquationSource> </InlineEquation>, or, equivalently, there exist nonzero <i>x</i> and <i>y</i> such that <InlineEquation ID="IEq9"> <EquationSource Format="TEX">\((A+\lambda _0 B+\mu _0 C)x=0\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq10"> <EquationSource Format="TEX">\(y^H(A+\lambda _0 B+\mu _0 C)=0\)</EquationSource> </InlineEquation>, and <InlineEquation ID="IEq11"> <EquationSource Format="TEX">\(y^HBx=0\)</EquationSource> </InlineEquation>. We introduce three numerical methods for computing 2D and ZGV points. The first method calculates all 2D (ZGV) points from the eigenvalues of a related singular two-parameter eigenvalue problem. The second method employs a projected regular two-parameter eigenvalue problem to compute either all eigenvalues or only a subset of eigenvalues close to a given target. The third approach is a locally convergent Gauss–Newton-type method that computes a single 2D point from an inital approximation, the later can be provided for all 2D points via the method of fixed relative distance by Jarlebring, Kvaal, and Michiels. In our numerical examples we use these methods to compute 2D-eigenvalues, solve double eigenvalue problems, determine ZGV points of a parameter-dependent quadratic eigenvalue problem, evaluate the distance to instability of a stable matrix, and find critical points of eigencurves of a two-parameter Sturm–Liouville problem.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

On properties and numerical computation of critical points of eigencurves of bivariate matrix pencils

  • Bor Plestenjak

摘要

We investigate critical points of eigencurves of bivariate matrix pencils \(A+\lambda B +\mu C\) . Points \((\lambda ,\mu )\) for which \(\det (A+\lambda B+\mu C)=0\) form algebraic curves in \({\mathbb {C}}^2\) and we focus on points where \(\mu '(\lambda )=0\) . Such points are referred to as zero-group-velocity (ZGV) points, following terminology from engineering applications. We provide a general theory for the ZGV points and show that they form a subset (with equality in the generic case) of the 2D points \((\lambda _0,\mu _0)\) , where \(\lambda _0\) is a multiple eigenvalue of the pencil \((A+\mu _0 C)+\lambda B\) , or, equivalently, there exist nonzero x and y such that \((A+\lambda _0 B+\mu _0 C)x=0\) , \(y^H(A+\lambda _0 B+\mu _0 C)=0\) , and \(y^HBx=0\) . We introduce three numerical methods for computing 2D and ZGV points. The first method calculates all 2D (ZGV) points from the eigenvalues of a related singular two-parameter eigenvalue problem. The second method employs a projected regular two-parameter eigenvalue problem to compute either all eigenvalues or only a subset of eigenvalues close to a given target. The third approach is a locally convergent Gauss–Newton-type method that computes a single 2D point from an inital approximation, the later can be provided for all 2D points via the method of fixed relative distance by Jarlebring, Kvaal, and Michiels. In our numerical examples we use these methods to compute 2D-eigenvalues, solve double eigenvalue problems, determine ZGV points of a parameter-dependent quadratic eigenvalue problem, evaluate the distance to instability of a stable matrix, and find critical points of eigencurves of a two-parameter Sturm–Liouville problem.