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Finite-rate fluctuation response and Green–Kubo inverse

Statement

Assume the Axiom of Choice The Axiom of Choice, countable choice The Axiom of Countable Choice (ACω), and the rate model E,π,w,Q of Finite reversible stochastic rate model. Let Xt be the stationary two-sided chain of Nonexplosive finite continuous-time chain and reversible spectral gap, with transition semigroup Pt=etQ. For any real observables A,B:E→R, write Ac=A−π(A) and Bc=B−π(B), and define CBA(t):=⟨Bc,PtAc⟩π,t≥0. Define Cov⁡π(A,B):=π(AB)−π(A)π(B), where AB is pointwise multiplication. For any finite horizon tf>0, let h:[0,tf]→R be continuous and let ϵ be dimensionless. For 0≤t≤tf, prescribe rates wabϵ(t)=wabexp⁡ ⁣(βϵh(t)2(Bb−Ba)),a≠b, with negative row sums on the diagonal, and let pϵ(0)=π evolve by the resulting finite forward equation. For 0≤t≤tf, the derivative of the observable mean at ϵ=0 is ∂∂ϵ∑apaϵ(t)Aa∣ϵ=0=∫0th(s)RAB(t−s) ds,RAB(u)=−β dduCBA(u). For a constant field h, define the normalized perturbed Gibbs vector by πaϵ:=πaeβϵhBa∑c∈EπceβϵhBc. It is stationary and its static susceptibility is βh Cov⁡π(A,B).

For any bounded vector observable G:E→Rd, set Gc=G−π(G) and Cij(s):=⟨(Gc)i,Ps(Gc)j⟩π. These correlations are absolutely integrable. The Green–Kubo covariance limit is lim⁡T→∞Cov⁡π(∫0TG(Xs) ds)2T=D,Dij=∫0∞Cij(s) ds=⟨(Gc)i,(−Q)−1(Gc)j⟩π, where (−Q)−1 is the inverse on the mean-zero subspace and D is positive semidefinite.

Facts & Assumptions

Given: Choice, countable choice, and the connected finite reversible rate model.

[A1]

The Axiom of Choice: every family of nonempty sets has a choice function.

[A2]

The Axiom of Countable Choice (ACω): for every sequence of nonempty sets (Xn)n∈N, there is a choice function selecting one member of each Xn.

[F1]

Finite reversible stochastic rate model: π(f)=∑aπafa and ⟨f,g⟩π=∑aπafaga; Qab=wab for a≠b, Qaa=−∑b≠awab, π is a positive probability vector, the positive-rate graph is connected, and πawab=πbwba.

[F2]

Nonexplosive finite continuous-time chain and reversible spectral gap: Pt=etQ is stochastic; Q is self-adjoint on L2(E,π) with a one-dimensional constant kernel and a positive gap; from initial law π there is a jointly measurable two-sided stationary chain.

[F3]

Green–Kubo covariance limit under absolute integrability: for a jointly measurable, centered, second-order stationary process on a two-sided time axis with absolutely integrable covariances, the covariance of its time integral divided by 2T converges to the symmetrized integrated covariance matrix, which is positive semidefinite.

Proof

Given: [A1]–[A2] and [F1]–[F3].

1.1A1A2F1F2F3algebra

By [F2], choose an orthonormal eigenbasis of Q with ϕ0=1 and Qϕj=−λjϕj for j≥1, where λj>0. For centered A,B, expand Ac=∑j≥1ajϕj and Bc=∑j≥1bjϕj. Then CBA(t)=∑j=1r−1bjaje−λjt and ∫0∞CBA(t) dt=∑j=1r−1ajbj/λj=⟨Bc,(−Q)−1Ac⟩π. The sum is finite, so the correlation is absolutely integrable. Applying the same expansion to each component of Gc gives Dij=∑j′=1r−1gi,j′gj,j′/λj′, a symmetric positive-semidefinite matrix. The two-sided stationary chain in [F2] has bounded, jointly measurable Gc(Xt); its covariance is absolutely integrable by this expansion, so [F3] gives the stated covariance limit and agrees with this matrix.

2.1A1F1F2step 1.1constructalgebra

For a finite time interval, the controlled off-diagonal rate matrix has the uniform expansion Qϵ(t)=Q+ϵh(t)K+O(ϵ2), where Kab=β2wab(Bb−Ba) for a≠b and each diagonal entry makes its row sum zero. The remainder is uniform because E is finite and h is bounded. The finite forward equation p′=pQϵ(t) has a unique solution: its Picard series converges uniformly, since the nth iterated integral is bounded by Mntfn/n! when ∥Qϵ(t)∥≤M. Since E is finite, h is bounded, and the exponential factors are bounded uniformly for t∈[0,tf] and ∣ϵ∣≤1, choose one Λ larger than every controlled exit rate on this set. Then Qϵ(t)+ΛI has nonnegative entries; after r(t)=eΛtpϵ(t), its Picard series has nonnegative terms, so pϵ(t)≥0 for all such ϵ. The row sums of Qϵ are zero, hence total mass remains one. Subtracting the unperturbed equation and using πQ=0 gives pϵ−π=O(ϵ) on [0,tf] by successive substitution in the bounded linear integral equation. Put yϵ=(pϵ−π)/ϵ; then yϵ(t)=∫0tyϵ(s)Q ds+∫0tpϵ(s)(Qϵ(s)−Q)/ϵ ds. The second integrand converges uniformly to πh(s)K, since pϵ→π uniformly and (Qϵ−Q)/ϵ→hK uniformly. Subtracting the limiting integral equation bounds ∥yϵ−q∥ by a term tending uniformly to zero plus M∫0t∥yϵ−q∥,ds; successive substitution bounds this difference by the forcing error times eMtf. Thus q=∂ϵpϵ∣0 exists and satisfies q′=qQ+hπK, q(0)=0. Variation of constants, verified by differentiation, gives q(t)=∫0th(s)πKPt−s ds.

3.1F1F2step 2.1algebra

For each state b, detailed balance in [F1] and the definition of K give (πK)b=β2∑a≠bπawab(Bb−Ba)−β2πb∑c≠bwbc(Bc−Bb)=−βπb(QB)b. Indeed, replacing πawab by πbwba makes the first sum the negative of the second before its prefactor is applied. Thus q(t)A=∫0th(s)(πK)Pt−sA ds=−β∫0th(s)⟨QBc,Pt−sAc⟩π ds. Self-adjointness of Q and Pu′=QPu imply CBA′(u)=⟨QBc,PuAc⟩π, proving the response formula.

4.1F1step 1.1algebra∎

For constant h, put Zϵ:=∑c∈EπceβϵhBc>0 and πaϵ=Zϵ−1πaeβϵhBa. Multiplying this by wabϵ gives a common edge factor proportional to πawabeβϵh(Ba+Bb)/2, symmetric in a,b by detailed balance. Hence πϵ is stationary. Differentiating its finite normalization sum at ϵ=0 gives ∂ϵ∑aπaϵAa∣0=βh(π(AB)−π(A)π(B)), the stated static susceptibility.

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