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Exact elimination of latent packets

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13 Exact elimination of latent packets

The central idea

Elimination removes hidden coordinates from the displayed state, but their future influence survives. The resolvent stores that influence as a self energy. The time description stores it as a memory kernel. Both descriptions refer to the same declared block system.

Let \(X=P X\oplus Q X\) and write

\[ A= \begin{pmatrix} A_{PP}&A_{PQ}\\ A_{QP}&A_{QQ} \end{pmatrix}. \]

Theorem 13.1: Schur–Feshbach projected resolvent

Assume both \(zI-A\) and \(zI-A_{QQ}\) are invertible. Define

\[ \boxed{ F_P(z) =zI-A_{PP}-A_{PQ}(zI-A_{QQ})^{-1}A_{QP}. } \]

Then

\[ \boxed{ \left.P(zI-A)^{-1}\right|_{{\operatorname{Ran}} P}=F_P(z)^{-1}. } \]

Proof of Theorem 13.1

Solve the hidden block equation

\[ (zI-A_{QQ})x_Q=A_{QP}x_P+y_Q \]

for \(x_Q\) and substitute it into the retained equation. The resulting retained coefficient is \(F_P(z)\). Invertibility of the full operator and of the hidden block implies invertibility of this Schur complement. Setting \(y_Q=0\) gives the stated identity as an operator on \({\operatorname{Ran}} P\). Equivalently, this is the block inverse formula.

The self-energy

\[ \Sigma_P(z)=A_{PQ}(zI-A_{QQ})^{-1}A_{QP} \]

contains the exact effect of the eliminated packets. A bare truncation \(A_{PP}\) discards this term and is generally not exact.

13.1 Time-domain memory

For the homogeneous system \(\dot x=Ax\), variation of constants gives

\[ x_Q(t)=e^{tA_{QQ}}x_Q(0) +\int_0^te^{(t-r)A_{QQ}}A_{QP}x_P(r)\,dr. \]

Substitution yields

\[ \dot x_P(t) =A_{PP}x_P(t)+A_{PQ}e^{tA_{QQ}}x_Q(0) +\int_0^t{\mathcal K}(t-r)x_P(r)\,dr, \]

where

\[ \boxed{ {\mathcal K}(t)=A_{PQ}e^{tA_{QQ}}A_{QP}. } \]

Theorem 13.2: Memory/self-energy correspondence

For finite complex block matrices, assume \(\operatorname{Re}z>\operatorname{Re}\lambda\) for every \(\lambda\in\sigma(A_{QQ})\). Then the following improper integral is absolutely convergent and

\[ \boxed{ \int_0^\infty e^{-zt}{\mathcal K}(t)\,dt =A_{PQ}(zI-A_{QQ})^{-1}A_{QP} =\Sigma_P(z). } \]

Proof of Theorem 13.2

Put \(B=A_{QQ}\) and \(T_z(t)=e^{-zt}e^{tB}=e^{t(B-zI)}\). The generalized-eigenspace decomposition in finite dimensions writes \(T_z\) as a finite sum of constant matrix coefficients times \(t^k e^{(\lambda-z)t}\). This follows by expanding the nilpotent part on each generalized eigenspace; equivalently, apply the decomposition to left multiplication by \(B\) on the matrix algebra and evaluate the exponential at \(I\). The strict spectral inequality makes every such term absolutely integrable on \((0,\infty)\) and forces it to tend to zero. Hence \(T_z\) is Bochner integrable and \(T_z(t)\to0\), including when \(B\) is nonnormal.

Let \(J=\int_0^\infty T_z(t)\,dt\). Integrating both derivative identities \(T_z'=(B-zI)T_z=T_z(B-zI)\) and using \(T_z(0)=I\) gives

\[ (zI-B)J=J(zI-B)=I. \]

Thus \(J=(zI-B)^{-1}\). Continuous left and right multiplication carry the Bochner integral through the two rectangular transfer blocks, yielding the claim.

The norm of the exact memory kernel produced by eliminated packets.
The norm of the exact memory kernel produced by eliminated packets.

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