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Nonlinear matrix equations and canonical factorizations Beatrice - - PowerPoint PPT Presentation

Some examples Canonical factorization Canonical factorization and matrix equations Nonlinear matrix equations and canonical factorizations Beatrice Meini joint work with Dario A. Bini Dipartimento di Matematica, Universit` a di Pisa, Italy


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Some examples Canonical factorization Canonical factorization and matrix equations

Nonlinear matrix equations and canonical factorizations

Beatrice Meini joint work with Dario A. Bini

Dipartimento di Matematica, Universit` a di Pisa, Italy

Structured numerical linear algebra problems Cortona, Sept. 19–24, 2004

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations

Outline

1

Some examples Quadratic matrix equations Matrix pth root: X p = A Power series matrix equations

2

Canonical factorization

3

Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations

Outline

1

Some examples Quadratic matrix equations Matrix pth root: X p = A Power series matrix equations

2

Canonical factorization

3

Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations

Outline

1

Some examples Quadratic matrix equations Matrix pth root: X p = A Power series matrix equations

2

Canonical factorization

3

Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations Quadratic matrix equations Matrix pth root Power series matrix equations

Outline

1

Some examples Quadratic matrix equations Matrix pth root: X p = A Power series matrix equations

2

Canonical factorization

3

Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations Quadratic matrix equations Matrix pth root Power series matrix equations

Quadratic matrix equations

Given the m × m matrix polynomial A(z) = A−1 + zA0 + z2A1 such that det A(z) has zeros |ξ1| ≤ · · · ≤ |ξm| < |ξm+1| ≤ · · · ≤ |ξ2m| compute the solution G of A−1 + A0X + A1X 2 = 0 such that λ(G) = {ξ1, . . . , ξm}. Such G is called the minimal solvent (Gohberg, Lancaster, Rodman ’82) Applications Quadratic eigenvalue problems (damped vibration problems), polynomial factorization, Markov chains, etc.

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations Quadratic matrix equations Matrix pth root Power series matrix equations

Functional interpretation (Gohberg, Lancaster, Rodman ’82)

1 The

matrix function S(z) = z−1A−1+A0+zA1 can be factorized as S(z) = (A0 + zA1G)(I − z−1G) where

det(A0 + zA1G) = 0 for |z| ≤ 1; det(I − z−1G) = 0 for |z| ≥ 1.

2 Conversely: if

S(z) = (U0 + zU1)(L0 + z−1L−1) = U(z)L(z) where det U(z) = 0 for |z| ≤ 1 and det L(z) = 0 for |z| ≥ 1, then G = −L−1

0 L−1 is the minimal right solvent.

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations Quadratic matrix equations Matrix pth root Power series matrix equations

Functional interpretation (Gohberg, Lancaster, Rodman ’82)

1 The

matrix function S(z) = z−1A−1+A0+zA1 can be factorized as S(z) = (A0 + zA1G)(I − z−1G) where

det(A0 + zA1G) = 0 for |z| ≤ 1; det(I − z−1G) = 0 for |z| ≥ 1.

2 Conversely: if

S(z) = (U0 + zU1)(L0 + z−1L−1) = U(z)L(z) where det U(z) = 0 for |z| ≤ 1 and det L(z) = 0 for |z| ≥ 1, then G = −L−1

0 L−1 is the minimal right solvent.

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Some examples Canonical factorization Canonical factorization and matrix equations Quadratic matrix equations Matrix pth root Power series matrix equations

Matrix pth root

Assumptions A ∈ Cm×m with no eigenvalues on the closed negative real axis. Definition The principal matrix pth root of A, A1/p, is the unique matrix X such that:

1 X p = A. 2 The eigenvalues of X lie in the segment

{ z : −π/p < arg(z) < π/p }. Applications Computation of the matrix logarithm, computation

  • f the matrix sector function (control theory).

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Some examples Canonical factorization Canonical factorization and matrix equations Quadratic matrix equations Matrix pth root Power series matrix equations

Functional interpretation

Theorem (Bini, Higham, Meini 04) Assume p = 2q, where q is odd. Let S(z) = z−q

p

  • j=0

zj p j

  • A + (−1)j+1I
  • .

If U(z) = U0 + zU1 + · · · + zqUq is such that det U(z) = 0 for |z| ≤ 1, and S(z) = U(z)U(z−1) then A1/p = −σ−1(qI + 2U′(−1)U(−1)−1) where σ = 1 + 2 ⌊q/2⌋

j=1

cos(2πj/p).

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Some examples Canonical factorization Canonical factorization and matrix equations Quadratic matrix equations Matrix pth root Power series matrix equations

Power series matrix equations

An application M/G/1-type Markov chains, introduced by

  • M. F. Neuts in the 80’s, which model a large variety
  • f queueing problems.

Problem Given nonnegative matrices Ai ∈ Rm×m, i ≥ −1, such that +∞

i=−1 Ai is stochastic, compute the

minimal component-wise solution G, among the nonnegative solutions, of X = A−1 + A0X + A1X 2 + · · ·

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations Quadratic matrix equations Matrix pth root Power series matrix equations

Some properties of G

Let φ(z) = zI − +∞

i=−1 zi+1Ai.

If the M/G/1-type Markov chain is positive recurrent, then: G is row stochastic. det φ(z) has exactly m zeros in the closed unit disk. The eigenvalues of G are the zeros of det φ(z) in the closed unit disk. Therefore G is the spectral minimal solution, i.e., ρ(G) ≤ ρ(X) for any other possible solution X.

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Some examples Canonical factorization Canonical factorization and matrix equations Quadratic matrix equations Matrix pth root Power series matrix equations

The induced factorization

The function S(z) = I − +∞

i=−1 ziAi can be factorized as

S(z) =

  • I −

+∞

  • i=0

ziUi

  • (I − z−1G),

|z| = 1, where: U(z) = I − +∞

i=0 ziUi is analytic for |z| < 1, convergent for

|z| ≤ 1, and det U(z) = 0 for |z| ≤ 1; L(z) = I − z−1G is analytic for |z| > 1, convergent for |z| ≥ 1, and det L(z) = 0 for |z| > 1, det L(1) = 0.

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Some examples Canonical factorization Canonical factorization and matrix equations Quadratic matrix equations Matrix pth root Power series matrix equations

The induced factorization

The function S(z) = I − +∞

i=−1 ziAi can be factorized as

S(z) =

  • I −

+∞

  • i=0

ziUi

  • (I − z−1G),

|z| = 1, where: U(z) = I − +∞

i=0 ziUi is analytic for |z| < 1, convergent for

|z| ≤ 1, and det U(z) = 0 for |z| ≤ 1; L(z) = I − z−1G is analytic for |z| > 1, convergent for |z| ≥ 1, and det L(z) = 0 for |z| > 1, det L(1) = 0.

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Some examples Canonical factorization Canonical factorization and matrix equations Quadratic matrix equations Matrix pth root Power series matrix equations

The induced factorization

The function S(z) = I − +∞

i=−1 ziAi can be factorized as

S(z) =

  • I −

+∞

  • i=0

ziUi

  • (I − z−1G),

|z| = 1, where: U(z) = I − +∞

i=0 ziUi is analytic for |z| < 1, convergent for

|z| ≤ 1, and det U(z) = 0 for |z| ≤ 1; L(z) = I − z−1G is analytic for |z| > 1, convergent for |z| ≥ 1, and det L(z) = 0 for |z| > 1, det L(1) = 0.

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations

Outline

1

Some examples Quadratic matrix equations Matrix pth root: X p = A Power series matrix equations

2

Canonical factorization

3

Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations

Wiener algebra

Definition (W) The Wiener algebra W is the set of complex m × m matrix valued functions A(z) = +∞

i=−∞ ziAi such that +∞ i=−∞ |Ai| is finite.

Definition (W+ and W−) The set W+ ( W−) is the subalgebra of W made up by power series of the kind +∞

i=0 ziAi (+∞ i=0 z−iAi).

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Some examples Canonical factorization Canonical factorization and matrix equations

Canonical factorization

Definition (Canonical factorization) Let A(z) = +∞

i=−∞ ziAi ∈ W. A canonical factorization of A(z) is

a decomposition A(z) = U(z)L(z), |z| = 1, where U(z) = +∞

i=0 ziUi ∈ W+ and L(z) = +∞ i=0 z−iL−i ∈ W−

are invertible for |z| ≤ 1 and 1 ≤ |z| ≤ ∞, respectively. Definition (Weak canonical factorization) The above decomposition is a weak canonical factorization if U(z) = +∞

i=0 ziUi ∈ W+ and L(z) = +∞ i=0 z−iL−i ∈ W− are

invertible for |z| < 1 and 1 < |z| ≤ ∞, respectively.

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations

Canonical factorization

Definition (Canonical factorization) Let A(z) = +∞

i=−∞ ziAi ∈ W. A canonical factorization of A(z) is

a decomposition A(z) = U(z)L(z), |z| = 1, where U(z) = +∞

i=0 ziUi ∈ W+ and L(z) = +∞ i=0 z−iL−i ∈ W−

are invertible for |z| ≤ 1 and 1 ≤ |z| ≤ ∞, respectively. Definition (Weak canonical factorization) The above decomposition is a weak canonical factorization if U(z) = +∞

i=0 ziUi ∈ W+ and L(z) = +∞ i=0 z−iL−i ∈ W− are

invertible for |z| < 1 and 1 < |z| ≤ ∞, respectively.

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Some examples Canonical factorization Canonical factorization and matrix equations

An example: S(z) = +∞

i=−1 ziAi

Location of the zeros of det(zS(z)) Canonical factorization Weak canonical factorization

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Outline

1

Some examples Quadratic matrix equations Matrix pth root: X p = A Power series matrix equations

2

Canonical factorization

3

Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Some questions

Let S(z) = +∞

i=−1 ziAi ∈ W and define A(z) = zS(z). Consider +∞

  • i=−1

AiX i+1 = 0 (1)

1 Existence of a canonical factorization =

⇒ existence of a spectral minimal solution? Viceversa?

2 What can we say if the canonical factorization is weak? 3 Can we transform a weak canonical factorization into a

canonical factorization?

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Existence of solutions and canonical factorization

Theorem If there exists a c.f. S(z) = U(z)L(z), L(z) = L0 + z−1L−1, |z| = 1, then G = −L−1

0 L−1 is the unique solution of (1) such that

ρ(G) < 1, and it is the spectral minimal solution. Conversely, if there exists a solution G of (1) such that ρ(G) < 1 and if A(z) has exactly m roots in the open unit disk, det A(z) = 0 for |z| = 1, then S(z) has a c.f. S(z) = (U0 + zU1 + · · · )(I − z−1G), |z| = 1.

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Existence of solutions and canonical factorization

Theorem If there exists a c.f. S(z) = U(z)L(z), L(z) = L0 + z−1L−1, |z| = 1, then G = −L−1

0 L−1 is the unique solution of (1) such that

ρ(G) < 1, and it is the spectral minimal solution. Conversely, if there exists a solution G of (1) such that ρ(G) < 1 and if A(z) has exactly m roots in the open unit disk, det A(z) = 0 for |z| = 1, then S(z) has a c.f. S(z) = (U0 + zU1 + · · · )(I − z−1G), |z| = 1.

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Existence of solutions and weak factorization

Theorem If there exists a weak c.f. S(z) = U(z)L(z), L(z) = L0 + z−1L−1, |z| = 1, such that G = −L−1

0 L−1 is power bounded, then G is a spectral

minimal solution of (1) such that ρ(G) ≤ 1. Conversely, if S′(z) ∈ W, if there exists a power bounded solution G of (1) such that ρ(G) = 1, and if all the zeros of det A(z) in the

  • pen unit disk are eigenvalues of G then there exists a weak c.f. of

S(z). In general, weak c.f. = ⇒ unique spectral minimal solution. Can we transform a weak c.f. into a c.f?

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Existence of solutions and weak factorization

Theorem If there exists a weak c.f. S(z) = U(z)L(z), L(z) = L0 + z−1L−1, |z| = 1, such that G = −L−1

0 L−1 is power bounded, then G is a spectral

minimal solution of (1) such that ρ(G) ≤ 1. Conversely, if S′(z) ∈ W, if there exists a power bounded solution G of (1) such that ρ(G) = 1, and if all the zeros of det A(z) in the

  • pen unit disk are eigenvalues of G then there exists a weak c.f. of

S(z). In general, weak c.f. = ⇒ unique spectral minimal solution. Can we transform a weak c.f. into a c.f?

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Existence of solutions and weak factorization

Theorem If there exists a weak c.f. S(z) = U(z)L(z), L(z) = L0 + z−1L−1, |z| = 1, such that G = −L−1

0 L−1 is power bounded, then G is a spectral

minimal solution of (1) such that ρ(G) ≤ 1. Conversely, if S′(z) ∈ W, if there exists a power bounded solution G of (1) such that ρ(G) = 1, and if all the zeros of det A(z) in the

  • pen unit disk are eigenvalues of G then there exists a weak c.f. of

S(z). In general, weak c.f. = ⇒ unique spectral minimal solution. Can we transform a weak c.f. into a c.f?

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Shift technique: removing zeros of modulus 1

Before shifting After shifting

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Assumptions

S(z) = +∞

i=−N ziAi ∈ W and S′(z) ∈ W, where N ≥ 1.

There is only one simple zero λ of det S(λ) on the unit circle. v is a vector such that S(λ)v = 0, v = 0. In problems arising in Markov chains these assumptions are satisfied, moreover λ = 1 and v = (1, 1, . . . , 1)T.

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Shift technique

Define

  • S(z) = S(z)(I − z−1λQ)−1,

Q = vuT where u is any fixed vector such that vTu = 1. Let A(z) = zN S(z). Then:

  • S(z) = +∞

i=−N zi

Ai ∈ W. if z ∈ {0, λ}, then det A(z) = 0 ⇐ ⇒ det A(z) = 0; det A(0) = 0 and A(0)v = 0; det A(z) = 0 if |z| = 1.

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Shift technique

Define

  • S(z) = S(z)(I − z−1λQ)−1,

Q = vuT where u is any fixed vector such that vTu = 1. Let A(z) = zN S(z). Then:

  • S(z) = +∞

i=−N zi

Ai ∈ W. if z ∈ {0, λ}, then det A(z) = 0 ⇐ ⇒ det A(z) = 0; det A(0) = 0 and A(0)v = 0; det A(z) = 0 if |z| = 1.

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Shift technique

Define

  • S(z) = S(z)(I − z−1λQ)−1,

Q = vuT where u is any fixed vector such that vTu = 1. Let A(z) = zN S(z). Then:

  • S(z) = +∞

i=−N zi

Ai ∈ W. if z ∈ {0, λ}, then det A(z) = 0 ⇐ ⇒ det A(z) = 0; det A(0) = 0 and A(0)v = 0; det A(z) = 0 if |z| = 1.

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Shift technique

Define

  • S(z) = S(z)(I − z−1λQ)−1,

Q = vuT where u is any fixed vector such that vTu = 1. Let A(z) = zN S(z). Then:

  • S(z) = +∞

i=−N zi

Ai ∈ W. if z ∈ {0, λ}, then det A(z) = 0 ⇐ ⇒ det A(z) = 0; det A(0) = 0 and A(0)v = 0; det A(z) = 0 if |z| = 1.

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Shift technique

Define

  • S(z) = S(z)(I − z−1λQ)−1,

Q = vuT where u is any fixed vector such that vTu = 1. Let A(z) = zN S(z). Then:

  • S(z) = +∞

i=−N zi

Ai ∈ W. if z ∈ {0, λ}, then det A(z) = 0 ⇐ ⇒ det A(z) = 0; det A(0) = 0 and A(0)v = 0; det A(z) = 0 if |z| = 1.

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Weak − → canonical factorization

If S(z) has a weak canonical factorization S(z) = U(z)L(z) where det U(z) = 0 if |z| = 1, then S(z) has a canonical factorization

  • S(z) =

U(z) L(z), where

  • U(z) = U(z),
  • L(z) = L(z)(I − z−1λQ)−1

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Back to matrix equations

Let S(z) = +∞

i=−1 ziAi and let G, with ρ(G) = |λ|, be the

spectral minimal solution of +∞

i=−1 AiX i+1 = 0.

Then the matrix equation

+∞

  • i=−1
  • AiX i+1 = 0

has one minimal spectral solution

  • G = G − λQ.

Moreover ρ( G) = ρ2(G) < 1.

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Some examples Canonical factorization Canonical factorization and matrix equations Some questions Existence of solutions Shift technique

Computational issues

Shift technique = ⇒ larger isolation ratio of the roots of S(z) with respect to the unit circle. Experimentally, larger isolatio ratio = ⇒ faster speed of convergence of functional iterations, cyclic reduction. Experimentally, larger isolatio ratio = ⇒ better numerical stability A theorethical proof of the latter experimental observations is still missing

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New book

Numerical Methods for Structured Markov Chains D.A. Bini (University of Pisa)

  • G. Latouche (Universit´

e Libre de Bruxelles)

  • B. Meini (University of Pisa)

Oxford University Press, 2005

D.A. Bini and B. Meini Nonlinear matrix equations and canonical factorizations