English

On a quantum-classical correspondence: from graphs to manifolds

Analysis of PDEs 2022-12-15 v2 Differential Geometry

Abstract

We establish conditions for which graph Laplacians Δλ,ϵ\Delta_{\lambda,\epsilon} on compact, boundaryless, smooth submanifolds M\mathcal{M} of Euclidean space are semiclassical pseudodifferential operators (Ψ\PsiDOs): essentially, that the graph Laplacian's kernel bandwidth (bias term\textit{bias term}) ϵ\sqrt{\epsilon} decays faster than the semiclassical parameter hh, i.e.\textit{i.e.}, hϵh \gg \sqrt{\epsilon} and we compute the symbol. Coupling this with Egorov's theorem and coherent states ψh\psi_h localized at (x0,ξ0)TM(x_0, \xi_0) \in T^*\mathcal{M}, we show that with Uλ,ϵt:=eitΔλ,ϵU_{\lambda,\epsilon}^t := e^{-i t \sqrt{\Delta}_{\lambda,\epsilon}} spectrally defined, the (co-)geodesic flow Γt\Gamma^t on TMT^*\mathcal{M} is approximated by Uλ,ϵtOph(a)Uλ,ϵtψh,ψh=aΓt(x0,ξ0)+O(h)\langle U_{\lambda,\epsilon}^{-t} \operatorname{Op}_h(a) U_{\lambda,\epsilon}^t \psi_h, \psi_h \rangle = a \circ \Gamma^t(x_0, \xi_0) + O(h). Then, we turn to the discrete setting: for Δλ,ϵ,N\Delta_{\lambda,\epsilon,N} a normalized graph Laplacian defined on a set of NN points x1,,xNx_1, \ldots, x_N sampled i.i.d.\textit{i.i.d.} from a probability distribution with smooth density, we establish Bernstein-type lower bounds on the probability that Uλ,ϵ,Nt[u]Uλ,ϵt[u]Lδ||U_{\lambda,\epsilon,N}^t[u] - U_{\lambda,\epsilon}^t[u]||_{L^{\infty}} \leq \delta with Uλ,ϵ,Nt:=eitΔλ,ϵ,NU_{\lambda,\epsilon,N}^t := e^{-i t \sqrt{\Delta}_{\lambda,\epsilon,N}}. We apply this to coherent states to show that the geodesic flow on M\mathcal{M} can be approximated by matrix dynamics on the discrete sample set, namely that with high probability\textit{with high probability}, ct,N1j=1NUλ,ϵ,Nt[ψh](xj)2u(xj)=u(xt)+O(h)c_{t,N}^{-1} \sum_{j=1}^N |U_{\lambda,\epsilon,N}^t[\psi_h](x_j)|^2 u(x_j) = u(x_t) + O(h) for ct,N:=j=1NUλ,ϵ,Nt[ψh](xj)2c_{t,N} := \sum_{j=1}^N |U_{\lambda,\epsilon,N}^t[\psi_h](x_j)|^2 and xtx_t the projection of Γt(x0,ξ0)\Gamma^t(x_0, \xi_0) onto M\mathcal{M}.

Keywords

Cite

@article{arxiv.2112.10748,
  title  = {On a quantum-classical correspondence: from graphs to manifolds},
  author = {Akshat Kumar},
  journal= {arXiv preprint arXiv:2112.10748},
  year   = {2022}
}

Comments

This is a companion paper to "Manifold learning via quantum dynamics"

R2 v1 2026-06-24T08:25:04.914Z