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Expansions of the Characteristic Polynomial of a Perturbed Positive Semidefinite Matrix and Convergence Analysis of Alternating Projections

Hiroyuki Ochiai, Yoshiyuki Sekiguchi, Hayato Waki

TL;DR

This work studies convergence of alternating projections between the positive semidefinite cone and a line E = {A + tB} under the singleton intersection condition E ∩ S_+^n = {A}. By expanding the characteristic polynomial of the perturbed matrix A + tB via adjugates and compound matrices and applying the Newton diagram/polytope framework, the authors bound the leading eigenvalue terms that govern convergence. They prove that the iteration converges with rate ∥U_k − A∥ = O(k^{-1/2}) independent of singularity degree, and they provide a sufficient rank-condition for linear convergence, with a discussion of tightness in singularity-degree-2 cases. The approach bypasses conventional error-bound arguments and directly analyzes the defining projection equations through eigenvalue dynamics, offering a precise link between perturbation theory, Newton-type diagrams, and projection methods in semidefinite settings.

Abstract

We observe that the characteristic polynomial of a linearly perturbed semidefinite matrix can be used to give the convergence rate of alternating projections for the positive semidefinite cone and a line. As a consequence, we show that such alternating projections converge at $O(k^{-1/2})$, independently of the singularity degree. A sufficient condition for the linear convergence is also obtained. Our method directly analyzes the defining equation for an alternating projection sequence and does not use error bounds.

Expansions of the Characteristic Polynomial of a Perturbed Positive Semidefinite Matrix and Convergence Analysis of Alternating Projections

TL;DR

This work studies convergence of alternating projections between the positive semidefinite cone and a line E = {A + tB} under the singleton intersection condition E ∩ S_+^n = {A}. By expanding the characteristic polynomial of the perturbed matrix A + tB via adjugates and compound matrices and applying the Newton diagram/polytope framework, the authors bound the leading eigenvalue terms that govern convergence. They prove that the iteration converges with rate ∥U_k − A∥ = O(k^{-1/2}) independent of singularity degree, and they provide a sufficient rank-condition for linear convergence, with a discussion of tightness in singularity-degree-2 cases. The approach bypasses conventional error-bound arguments and directly analyzes the defining projection equations through eigenvalue dynamics, offering a precise link between perturbation theory, Newton-type diagrams, and projection methods in semidefinite settings.

Abstract

We observe that the characteristic polynomial of a linearly perturbed semidefinite matrix can be used to give the convergence rate of alternating projections for the positive semidefinite cone and a line. As a consequence, we show that such alternating projections converge at , independently of the singularity degree. A sufficient condition for the linear convergence is also obtained. Our method directly analyzes the defining equation for an alternating projection sequence and does not use error bounds.
Paper Structure (17 sections, 14 theorems, 65 equations, 8 figures)

This paper contains 17 sections, 14 theorems, 65 equations, 8 figures.

Key Result

Theorem 1.1

Let $\{U_k\}$ be the alternating projections for $\mathbb{S}^n_+$ and a line $E = \{A + tB:t\in \mathbb{R}\}$, where $A\in \mathbb{S}^n_+$ and $B\in \mathbb{S}$. If $\mathbb{S}^n_+ \cap E = \{A\}$, then $\|U_{k} - A\| = O(k^{-\frac{1}{2}})$.

Figures (8)

  • Figure 1: $D_0$ and the Newton polytope, where $Q$ is $(2n-2m+r,2m-r-n)$. The left and the right figures correspond to the case $m-r < n-m$ and to the case $m-r> n-m$ respectively.
  • Figure 2: the Newton polytope in Example \ref{['ex:newton_polytope']}
  • Figure 3: the Newton polytope in a degenerate case
  • Figure 4: The Newton diagram associated with the characteristic polynomial, which is obtained by rotating the left of Figure \ref{['fig:newton_polygon']}.
  • Figure 5: The Newton diagram associated with the characteristic polynomial in Example \ref{['ex:diagram']}. The case of $c\neq0$ corresponds to the left figure. The point at $(2,3)$ might be located above $\Gamma_1$. The case $c=0$ with $b = 0$ corresponds to the center figure, $c=0$ with $b \neq 0$ corresponds to the right figure.
  • ...and 3 more figures

Theorems & Definitions (35)

  • Theorem 1.1
  • Example 2.1
  • Example 2.2
  • Example 2.3
  • Lemma 3.1: HJ
  • Proposition 3.2
  • Example 3.3
  • proof : Proof of Proposition $\ref{['prop:expansion']}$
  • Lemma 3.4
  • proof
  • ...and 25 more