Nonlinear Perron–Frobenius conjecture for statistical Hamiltonians

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Let Hγ(p,z)H_{\boldsymbol{\gamma}}({\boldsymbol{p}},{\boldsymbol{z}}) be a biased Hamiltonian describing a nonlinear Markov process, and consider its stationary Hamilton–Jacobi equation at energy EE. Assume that the absolute maximum of Hmin⁡(z)H_{\min}({\boldsymbol{z}}) is non-degenerate, with H0⋆(γ)>H1⋆(γ)H_0^\star(\boldsymbol{\gamma})>H_1^\star(\boldsymbol{\gamma}), and write

H0⋆(γ)=max⁡zmin⁡pHγ(p,z).H_0^\star(\boldsymbol{\gamma})=\max_{{\boldsymbol{z}}}\min_{{\boldsymbol{p}}}H_{\boldsymbol{\gamma}}({\boldsymbol{p}},{\boldsymbol{z}}).

Nonlinear Perron–Frobenius conjecture. There exists a value E⋆(γ)E^\star(\boldsymbol{\gamma}) such that: for E>E⋆(γ)E>E^\star(\boldsymbol{\gamma}), all orbits tend towards the system boundaries in forward and backward time and contain no critical manifold; for E<E⋆(γ)E<E^\star(\boldsymbol{\gamma}), the Hamilton–Jacobi equation has no global solution and the reduced action along every bounded orbit is non-negative; and for E=E⋆(γ)E=E^\star(\boldsymbol{\gamma}), the equation has at least two global solutions up to an additive constant, exactly one globally stable solution Ws(z,γ)W_{\mathrm{s}}({\boldsymbol{z}},\boldsymbol{\gamma}) and exactly one globally unstable solution Wu(z,γ)W_{\mathrm{u}}({\boldsymbol{z}},\boldsymbol{\gamma}), which coincide on each critical manifold. The dominant fixed point (p0⋆,z0⋆)({\boldsymbol{p}}_0^\star,{\boldsymbol{z}}_0^\star) lies on both solutions, and

E⋆(γ)=max⁡zmin⁡pHγ(p,z)=H0⋆(γ).E^\star(\boldsymbol{\gamma})=\max_{{\boldsymbol{z}}}\min_{{\boldsymbol{p}}}H_{\boldsymbol{\gamma}}({\boldsymbol{p}},{\boldsymbol{z}})=H_0^\star(\boldsymbol{\gamma}).

This is proposed as a nonlinear analogue of the Perron–Frobenius theorem, replacing positivity and uniqueness properties of dominant eigenvectors by global stable and unstable Hamilton–Jacobi solutions. The conjecture is used to identify the dominant long-time trajectories and remains unproved in the stated generality.

References

Primary source

Lydia Chabane, Alexandre Lazarescu and Gatien Verley, “Effective Hamiltonians and Lagrangians for conditioned Markov processes at large volume”, arXiv:2109.06830 (2021).

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