08 Jun 2026

V: Survival Curvature Beyond the Linear Covariance Response

survival probability energy variance exceptional Hermite states non-Gaussian dynamics covariance limitations

When all first-order cross-covariance rates vanish, it is tempting to call the post-quench state stationary. That inference is false. The survival probability probes the state vector directly and reveals an exact quadratic response that covariance symmetry can miss.

Fixed-confinement quench and domain assumption

We retain the conventions

\[\hbar=2M=1, \qquad \omega_c=\frac{q_{\mathrm{el}}B}{2Mc},\]

with signed $\omega_c$. The preparation coordinates define the bipartition

\[A\equiv +,\qquad B\equiv -.\]

A real, definite-parity product eigenstate is prepared exactly,

\[\lvert\Psi_0\rangle =\lvert m_+,\ell_+\rangle_A \otimes\lvert m_-,\ell_-\rangle_B,\]

under the additive Hamiltonian $H_{\mathrm{sep}}^{\mathrm{RE}}$. At $t=0$, only the angular coupling is activated:

\[H_f=H_{\mathrm{sep}}^{\mathrm{RE}}-\omega_cL_z, \qquad L_z=q_+p_- -q_-p_+.\]

The diamagnetically dressed coordinate confinement is unchanged. This is not a literal quench of the complete electromagnetic field.

For the fourth-order remainder below, assume explicitly

\[\lvert\Psi_0\rangle\in D(H_f^2).\]

The regular even-seed exceptional-Hermite inputs satisfy this condition: their rational-polynomial derivatives remain Gaussian-decaying, so the required fourth energy moment is finite.

Survival probability and energy variance

Define

\[\mathcal S(t)= \left|\langle\Psi_0|e^{-iH_ft}|\Psi_0\rangle\right|^2.\]

Because survival probability is even in time and the domain assumption supplies the needed moments,

\[\mathcal S(t)=1-\operatorname{Var}_0(H_f)t^2+O(t^4).\]

The initial state is an eigenstate of $H_{\mathrm{sep}}^{\mathrm{RE}}$, while reality and parity give

\[\langle L_z\rangle_0=0.\]

Therefore the entire energy variance comes from the quenched angular term:

\[\operatorname{Var}_0(H_f) =\omega_c^2\langle L_z^2\rangle_0.\]

Introduce the local second moments

\[V_{q,\alpha}=\langle q_\alpha^2\rangle_0, \qquad V_{p,\alpha}=\langle p_\alpha^2\rangle_0.\]

Expanding $L_z^2$, factorizing expectations between $A=+$ and $B=-$, and using

\[\langle q_\alpha p_\alpha\rangle_0=\frac{i}{2}, \qquad \langle p_\alpha q_\alpha\rangle_0=-\frac{i}{2},\]

gives

\[\langle L_z^2\rangle_0 =V_{q,+}V_{p,-}+V_{q,-}V_{p,+}-\frac12.\]

The $-1/2$ is an ordering contribution: the two crossed products in $L_z^2$ each contribute $1/4$ beneath a minus sign. Defining

\[\boxed{ \Lambda_0 =V_{q,+}V_{p,-}+V_{q,-}V_{p,+}-\frac12, }\]

we obtain the exact local expansion

\[\boxed{ \mathcal S(t)=1-\omega_c^2\Lambda_0t^2+O(t^4). }\]

The coefficient $\Lambda_0$ is independent of the sign of the field, while first-order covariance flows are odd in $\omega_c$. Thus field reversal reverses the direction of the linear covariance response but not the initial survival loss.

A mode-exchange-symmetric counterexample

Suppose the two factors have the same codimension, excitation, and coordinate scale. Their second moments are then mode-exchange symmetric:

\[V_{q,+}=V_{q,-}=V_q, \qquad V_{p,+}=V_{p,-}=V_p.\]

Every first-order cross-covariance rate vanishes, because those rates are proportional to the corresponding variance differences. Define the one-mode uncertainty product

\[U_m=\Delta q\,\Delta p=\sqrt{V_qV_p}.\]

The survival coefficient reduces to

\[\boxed{ \Lambda_0=2U_m^2-\frac12. }\]

For two equal ordinary oscillator vacua, $U_0=1/2$, so $\Lambda_0=0$. This is consistent with rotational invariance. For two equal codimension-two added states, however,

\[U_2=0.5172471466\ldots\]

and hence

\[\Lambda_0 =2(0.5172471466\ldots)^2-\frac12 =0.03508922135\ldots>0.\]

The state therefore leaves its initial ray quadratically in time whenever $\omega_c\neq0$, even though all linear cross-covariance rates vanish. This is a direct counterexample to the implication

\[\text{zero linear covariance response} \quad\Longrightarrow\quad \text{stationary state}.\]

The correct conclusion is narrower: mode-exchange-symmetric second moments suppress the linear covariance channel. They do not suppress higher moments or the full non-Gaussian state dynamics.

Maxima-verified benchmark

For the unequal-scale codimension-two benchmark

\[\Omega_+=\frac54, \qquad \Omega_-=\frac{17}{20}, \qquad \omega_c=\frac34,\]

the bare-confinement stability margins are

\[\Omega_+^2-\omega_c^2=1, \qquad \Omega_-^2-\omega_c^2=\frac4{25},\]

and Maxima evaluates

\[\Lambda_0=0.07537829213164765\ldots.\]

The corresponding finite-time propagation gives a nonzero survival loss and reproduces the analytic curvature near $t=0$. This numerical evolution is performed in a systematically enlarged exceptional-product basis. It does not rely on Gaussian closure, and no finite cutoff is claimed to be exact.

Scope of the result

The formula for $\Lambda_0$ is exact for the stated real definite-parity product input and fixed-confinement angular quench. The displayed Taylor polynomial remains a short-time expansion, not a global solution. Later-time dynamics require propagation of the full state or an independently controlled approximation.

Survival curvature and covariance answer different questions. Covariance detects selected quadratic flows; survival detects departure from the complete initial state. Their disagreement in the symmetric codimension-two example is therefore not a paradox—it is a concrete signature of information outside the linear covariance response.

Series navigation

  1. Magnetic oscillator: stability and coordinate reduction
  2. Exceptional-Hermite state preparation
  3. A fixed-confinement angular-momentum quench
  4. Exact first-order covariance response
  5. Survival curvature beyond covariance
  6. Spectral propagation and synchronization
  7. Non-Gaussian mutual information
© Rajesh Kumar, SKMU · Physics Lecture Notes · rajeshphy.github.io

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