Power-law diagonal variance conjecture

From papers

Let Ω\Omega be the billiard domain, let A^\hat{A} be multiplication by a test function AA, and define its spatial average by

A:=1vol(Ω)ΩA(r)dr.\overline{A}:=\frac{1}{\operatorname{vol}(\Omega)}\int_\Omega A({\mathbf r})\,{d{\mathbf r}}.

For eigenfunctions ϕn\phi_n of the Laplacian with eigenvalues EnE_n, define

VA(E):=1NL(E)n:En[E,E+L(E)]ϕn,A^ϕnA2,V_A(E):=\frac{1}{N_L(E)}\sum_{n:E_n\in[E,E+L(E)]}\left|\langle\phi_n,\hat{A}\phi_n\rangle-\overline{A}\right|^2,

where NL(E):=N(E+L(E))N(E)N_L(E):=N(E+L(E))-N(E) and N(E):=#{n:EnE}N(E):=\#\{n:E_n\leq E\}. Power-law diagonal variance conjecture. For ergodic flow, as EE\to\infty, there are constants aa and γ\gamma such that

VA(E)aEγ.V_A(E)\sim aE^{-\gamma}.

This conjecture quantifies the rate at which diagonal matrix elements approach their classical average. The paper tests it numerically; random-wave and Feingold–Peres heuristics predict γ=1/2\gamma=1/2, but the general asymptotic law is not established.

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Sources & referencesView supporting material

Primary source

Alex H. Barnett, “Asymptotic rate of quantum ergodicity in chaotic Euclidean billiards”, arXiv:math-ph/0512030 (2006).

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