Existence and uniqueness of minimizers of general least gradient problems

Motivated by problems arising in conductivity imaging, we prove existence, uniqueness, and comparison theorems - under certain sharp conditions - for minimizers of the general least gradient problem $\inf_{u\in BV_f(Ω)} \int_Ωφ(x,Du),$ where $f:\partial Ω\to \R$ is continuous, \[ BV_f(Ω):=\{v\in BV(Ω): \ \ \forall x\in \partial Ω, \ \ \lim_{r\to 0} \ \esssup_{y\in Ω, |x-y|<r} |f(x) - v(y)| = 0 \ \} %BV_f(Ω)=\{u\in BV(Ω): {0.1cm} u|_{\partial Ω}=f {0.1cm} \hbox{and} {0.1cm} {0.1cm} u {0.1cm} \hbox{is continuous at} {0.1cm} \partial Ω\}. \] and $φ(x,ξ)$ is a function that, among other properties, is convex and homogeneous of degree 1 with respect to the $ξ$ variable. In particular we prove that if $a\in C^{1,1}(Ω)$ is bounded away from zero, then minimizers of the weighted least gradient problem $\inf_{u \in BV_f}\int_Ω a|Du|$ are unique in $BV_f(Ω)$. We construct counterexamples to show that the regularity assumption $a\in C^{1,1}$ is sharp, in the sense that it can not be replaced by $a\in C^{1,α}(Ω)$ with any $α<1$.

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