Recent progress in generalized Hamiltonian gradient flow: Singularities
Wei Cheng, Jiahui Hong

TL;DR
This survey explores the generalized Hamiltonian gradient flow framework for Hamilton-Jacobi equations, highlighting new variational constructions, dynamical characterizations of measures, and open problems in singular dynamics and optimal transport.
Contribution
It introduces a variational scheme for generalized characteristics, characterizes Mather measures via semi-flow dynamics, and discusses open problems connecting singular dynamics with ergodic theory and optimal transport.
Findings
Constructed generalized characteristics via a variational minimizing movement scheme.
Proved invariant measures of the GHGF semi-flow are precisely Mather measures.
Identified open problems related to uniqueness, stability, and extensions of the framework.
Abstract
This paper is a survey of the generalized Hamiltonian gradient flow (GHGF) framework for Hamilton-Jacobi equations, with an emphasis on the propagation of singularities and its connections to weak KAM theory, optimal transport and mean field control. In addition to reviewing the main ideas and known results, we present two new contributions. First, we provide a variational construction of generalized characteristics via a minimizing movement scheme; by taking the weak limit of approximate solutions and using Young measure compactness, we show that the limiting curve satisfies the generalized characteristic differential inclusion. Second, we lift the forward dynamics of strict singular characteristics to a semi-flow on the space of trajectories and study its invariant probability measures. We prove that the only invariant measures of the GHGF semi-flow that attain the critical value…
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