1. Preliminaries
Definition 1 (Hilbert Space Contraction).
A bounded linear operator \(T: H_1 \to H_2\) between Hilbert spaces is called a contraction if
\[ \|Tx\|_{H_2} \leq \|x\|_{H_1} \quad \forall x \in H_1 \]
Equivalently, \(\|T\| \leq 1\).
Definition 2 (Stationary Process).
A stochastic process \(\{Y(t)\}_{t \in \mathbb{R}}\) is stationary if for any finite set of time points \(\{t_1,\ldots,t_n\}\) and any \(h \in \mathbb{R}\), the joint distribution of
\[ \{Y(t_1+h),\ldots,Y(t_n+h)\} \]
is identical to that of \(\{Y(t_1),\ldots,Y(t_n)\}\).
Definition 3 (Stationary Dilation).
Given a non-stationary process \(X(t)\), a stationary dilation is a stationary process \(Y(s)\) together with a family of bounded operators \(\{\phi(t,\cdot)\}_{t \in \mathbb{R}}\) such that
\[ X(t) = \int_{\mathbb{R}} \phi(t,s)Y(s)ds \]
where \(\phi(t,s)\) is a measurable function satisfying:
- \(\|\phi(t,\cdot)\|_{\infty} \leq 1\) for all \(t\)
- The map \(t \mapsto \phi(t,\cdot)\) is strongly continuous
Remark.
The conditions on \(\phi(t,s)\) ensure that the integral is well-defined and the resulting process \(X(t)\) inherits appropriate regularity properties from \(Y(s)\).
2. Main Results
Proposition 1 (Properties of Scaling Function).
The scaling function \(\phi(t,s)\) in a stationary dilation satisfies:
- \(\|\phi(t,s)\| \leq 1\) for all \(t,s \in \mathbb{R}\)
- For fixed \(t\), \(s \mapsto \phi(t,s)\) is measurable
- For fixed \(s\), \(t \mapsto \phi(t,s)\) is continuous
Theorem 1 (Equivalence of Containment).
For a non-stationary process \(X(t)\) and a stationary process \(Y(s)\), the following are equivalent:
- \(Y(s)\) is a stationary dilation of \(X(t)\)
- There exists a contractive mapping \(\Phi\) from the space generated by \(Y\) to the space generated by \(X\) such that \(X(t) = (\Phi Y)(t)\) for all \(t\)
Proof.
(\(1 \Rightarrow 2\)): Define \(\Phi\) by \[ (\Phi Y)(t) = \int_{\mathbb{R}} \phi(t,s)Y(s)ds \] For any finite linear combination \(\sum_i \alpha_i Y(t_i)\): \begin{align*} \|\Phi(\sum_i \alpha_i Y(t_i))\|^2 &= \|\sum_i \alpha_i \int_{\mathbb{R}} \phi(t_i,s)Y(s)ds\|^2 \\ &\leq \|\sum_i \alpha_i Y(t_i)\|^2 \end{align*} where the inequality follows from the bound on \(\|\phi(t,s)\|\) and the Cauchy-Schwarz inequality. (\(2 \Rightarrow 1\)): The contractive mapping \(\Phi\) induces a family of operators \(\phi(t,s)\) via the Kernel theorem for Hilbert spaces. The stationarity of \(Y\) and the contractivity of \(\Phi\) ensure that these operators satisfy the required properties.
(\(1 \Rightarrow 2\)): Define \(\Phi\) by \[ (\Phi Y)(t) = \int_{\mathbb{R}} \phi(t,s)Y(s)ds \] For any finite linear combination \(\sum_i \alpha_i Y(t_i)\): \begin{align*} \|\Phi(\sum_i \alpha_i Y(t_i))\|^2 &= \|\sum_i \alpha_i \int_{\mathbb{R}} \phi(t_i,s)Y(s)ds\|^2 \\ &\leq \|\sum_i \alpha_i Y(t_i)\|^2 \end{align*} where the inequality follows from the bound on \(\|\phi(t,s)\|\) and the Cauchy-Schwarz inequality. (\(2 \Rightarrow 1\)): The contractive mapping \(\Phi\) induces a family of operators \(\phi(t,s)\) via the Kernel theorem for Hilbert spaces. The stationarity of \(Y\) and the contractivity of \(\Phi\) ensure that these operators satisfy the required properties.
Lemma 1 (Minimal Dilation Property).
If \(Y(s)\) is a minimal stationary dilation of \(X(t)\), then the scaling function \(\phi(t,s)\) achieves the bound
\[ \sup_{t,s} \|\phi(t,s)\| = 1 \]
Proof.
If \(\sup_{t,s} \|\phi(t,s)\| < 1\), we could construct a smaller dilation by scaling \(Y(s)\), contradicting minimality.
If \(\sup_{t,s} \|\phi(t,s)\| < 1\), we could construct a smaller dilation by scaling \(Y(s)\), contradicting minimality.
3. Structure Theory
Theorem 2 (Sz.-Nagy Dilation).
For any contraction \(T\) on a Hilbert space \(H\), there exists a minimal unitary dilation \(U\) on a larger space \(K \supseteq H\) such that:
\[ T^n = P_H U^n|_H \quad \forall n \geq 0 \]
where \(P_H\) is the orthogonal projection onto \(H\).
Lemma 2 (Defect Operators).
For a contraction \(T\), the defect operators defined by:
\[ D_T = (I - T^*T)^{1/2} \]
\[ D_{T^*} = (I - TT^*)^{1/2} \]
satisfy:
- \(\|D_T\| \leq 1\) and \(\|D_{T^*}\| \leq 1\)
- \(D_T = 0\) if and only if \(T\) is an isometry
- \(D_{T^*} = 0\) if and only if \(T\) is a co-isometry
4. Convergence Properties
Theorem 3 (Strong Convergence).
For a contractive stationary dilation, the following limit exists in the strong operator topology:
\[ \lim_{n \to \infty} T^n = P_{ker(I-T^*T)} \]
where \(P_{ker(I-T^*T)}\) is the orthogonal projection onto the kernel of \(I-T^*T\).
Proof.
For any \(x\) in the Hilbert space:
For any \(x\) in the Hilbert space:
- The sequence \(\{\|T^n x\|\}\) is decreasing since \(T\) is a contraction
- It is bounded below by 0
- Therefore, \(\lim_{n \to \infty} \|T^n x\|\) exists
- The limit operator must be the projection onto the space of vectors \(x\) satisfying \(\|Tx\| = \|x\|\)
- This space is precisely \(ker(I-T^*T)\)
Corollary 1 (Asymptotic Behavior).
If \(T\) is a strict contraction (i.e., \(\|T\| < 1\)), then
\[ \lim_{n \to \infty} T^n = 0 \]
in the strong operator topology.
5. Partial Isometries: The Mathematical Scalpel
Definition 4 (Partial Isometry).
An operator \(A\) on a Hilbert space \(H\) is a partial isometry if \(A^*A\) is an orthogonal projection.
Remark (Geometric Intuition).
A partial isometry is like a mathematical scalpel that carves out a section of space:
- It acts as a perfect rigid motion (isometry) on a specific subspace
- It completely annihilates the rest of the space
Proposition 2 (Key Properties of Partial Isometries).
Let \(A\) be a partial isometry. Then:
- \(A\) is an isometry when restricted to \((ker A)^\perp\)
- \(A(ker A)^\perp = ran A\)
- \(A^*\) is also a partial isometry
- \(AA^*A = A\) and \(A^*AA^* = A^*\)
Theorem 4 (Geometric Characterization).
For a partial isometry \(A\):
\[ A^*A = P_{(ker A)^\perp} \quad \text{and} \quad AA^* = P_{ran A} \]
where \(P_S\) denotes the orthogonal projection onto subspace \(S\).
Proof.
The action of \(A\) can be decomposed as:
The action of \(A\) can be decomposed as:
- Project onto \((ker A)^\perp\) (this is \(A^*A\))
- Apply a perfect rigid motion to the projected space
Remark (The "Not So Partial" Nature).
Despite the name, there's nothing incomplete about a partial isometry. It performs a complete operation:
- It's a full isometry on its initial space (\((ker A)^\perp\))
- It perfectly maps this initial space onto its final space (\(ran A\))
- It precisely annihilates everything else
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