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Generalized eigenvalue pencils and QZ methods — Examples
1 · Prerequisites
- Algebraic Closure, Embeddings, and Separability
- Algebraic Extensions, Extension Degree, and Finite Fields
- Binary Operations, Monoids, Groups and Subgroups
- Composition Series, the Jordan–Hölder Theorem and Solvable Groups
- Congruences, the Integers Modulo n and the Chinese Remainder Theorem
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Cyclic Groups and Direct Products
- Determinants of Matrices over a Commutative Ring
- Diagonalisation and the Minimal Polynomial
- Direct Matrix Factorisations: LU, Cholesky and QR
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Divisibility, Greatest Common Divisors and Bézout's Identity
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Eigenvalues, Eigenvectors and the Characteristic Polynomial
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Generalized eigenvalue pencils and QZ methods
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Group Homomorphisms and the Isomorphism Theorems
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Limits of Real Functions
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Order, Zorn's Lemma, and the Axiom of Choice
- Polynomial Rings, the Division Algorithm and Roots
- Primes, Euclid's Lemma and the Fundamental Theorem of Arithmetic
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Roots, Rational Powers, and Classical Inequalities
- Sequences and Limits
- Simple Field Extensions and the Construction of the Complex Numbers
- Splitting Fields
- Suprema and Infima
- Sylow's Theorems, p-Groups and Nilpotent Groups
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Determinant of a Linear Operator, Cofactors and Cramer's Rule
- The Fundamental Theorem of Algebra
- The Fundamental Theorem of Finite Abelian Groups
- The Galois Correspondence
- The Spectral Theorem, Positive Operators and Singular Value Decomposition
- The ZFC Axioms and the Basic Set Constructions
- Topology of ℝ
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
Examples
These calculations distinguish a Hermitian-definite mass-stiffness problem, an infinite eigenvalue caused by singular in an otherwise regular pencil, and an identically singular determinant pencil. The mass-stiffness example also checks the residual enclosure in the -dual norm.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
A singular B can give a regular pencil with an infinite generalized eigenvalue
Example
Take and . The matrix is singular, but the pencil is regular and has one finite eigenvalue and one infinite eigenvalue.
Facts & Assumptions
Given: The pair and the homogeneous eigenvalue convention of Regular matrix pencils and homogeneous generalized eigenvalues.
Regular matrix pencils and homogeneous generalized eigenvalues: regularity means is not identically zero, and homogeneous eigenpairs solve with .
Verification
Direct calculation gives , a nonzero polynomial, so the pencil is regular although .
The homogeneous determinant is Its projective roots are , the finite eigenvalue , and , the infinite eigenvalue.
A regular pencil and an identically singular determinant pencil
Example
The pair is regular and has only infinite generalized eigenvalues. The pair has an identically zero determinant pencil and is singular. Thus a singular second matrix is compatible with regularity, while the determinant polynomial decides pencil regularity.
Facts & Assumptions
Given: The regularity definition for finite square pencils in Regular matrix pencils and homogeneous generalized eigenvalues.
Regular matrix pencils and homogeneous generalized eigenvalues: a pencil is regular exactly when is not the zero polynomial.
Verification
For , , so the pencil is regular. Its homogeneous determinant is , which vanishes only at , the infinite eigenvalue pair.
For , for every , so the determinant polynomial is identically zero and the pencil is singular.
A mass-stiffness pencil has real B-orthogonal modes and a residual enclosure
Example
Let the stiffness and mass matrices be The generalized eigenvalues are and , with -orthogonal modes. The trial pair also illustrates a B-metric residual enclosure.
Facts & Assumptions
Given: The displayed real symmetric stiffness and mass matrices.
A Hermitian-definite pencil has a real spectrum and a B-orthonormal eigenbasis: a symmetric and positive-definite have real generalized eigenvalues and an -orthonormal eigenbasis.
A B-dual residual bounds distance to the spectrum of a Hermitian-definite pencil: a nonzero trial vector and real trial value have spectral distance bounded by the -dual residual norm divided by the -norm of the vector.
Regular matrix pencils and homogeneous generalized eigenvalues: the pencil is regular when its determinant polynomial is nonzero.
Verification
The matrix is positive definite because for . Also for . The determinant polynomial is so the pencil is regular and its eigenvalues are .
For , . For , . Their mass inner product is . Thus they are distinct generalized eigenmodes and are -orthogonal; [F1] gives the general real-spectrum and orthogonal-basis conclusion for this pencil.
For and , the residual is . Hence and, since , . The theorem [F2] therefore bounds the distance from to by ; indeed that distance is .
Sources
- Peter Arbenz, Lecture Notes on Solving Large Scale Eigenvalue Problems, §§12.8–12.9
- LAPACK Users' Guide, Generalized Nonsymmetric Eigenproblems
- Daniel Kressner, Numerical Methods and Software for General and Structured Eigenvalue Problems (PhD dissertation, 2004), Chapter 2: The QZ Algorithm
- LAPACK Users' Guide, Generalized Symmetric Definite Eigenproblems