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We present some general results on minimal barriers in the sense of De Giorgi for geometric evolution problems. We also compare minimal barriers with viscosity solutions for fully nonlinear geometric problems of the form $u_t+F\left(t,x,\nabla u,{\nabla }^{2}u\right)=0$. If $F$ is not degenerate elliptic, it turns out that we obtain the same minimal barriers if we replace $F$ with $F^{+}$, which is defined as the smallest degenerate elliptic function above $F$.

We survey some recent results on the gradient flow of an anisotropic surface energy, the integrand of which is one-homogeneous in the normal vector. We discuss the reasons for assuming convexity of the anisotropy, and we review some known results in the smooth, mixed and crystalline case. In particular, we recall the notion of calibrability and the related facet-breaking phenomenon. Minimal barriers as weak solutions to the gradient flow in case of nonsmooth anisotropies are proposed. Furthermore,...

In questa Nota presentiamo alcuni teoremi di confronto tra il movimento secondo la curvatura media ottenuto con il metodo delle minime barriere di De Giorgi e i movimenti definiti con i metodi di Evans-Spruck, Chen-Giga-Goto, Giga-Goto-Ishii-Sato.

The numerical minimization of the functional $\mathcal{F}\left(u\right)={\int }_{\mathrm{\Omega }}\varphi \left(x,{\nu }_u\right)\left|Du\right|+{\int }_{\partial \mathrm{\Omega }}\mu ud{\mathcal{H}}^{n-1}-{\int }_{\mathrm{\Omega }}\kappa udx$, $u\in BV\left(\mathrm{\Omega };\left\{-1,1\right\}\right)$ is addressed. The function $\varphi$ is continuous, has linear growth, and is convex and positively homogeneous of degree one in the second variable. We prove that $\mathcal{F}$ can be equivalently minimized on the convex set $BV\left(\mathrm{\Omega };\left[-1,1\right]\right)$ and then regularized with a sequence ${\left\{{\mathcal{F}}_{ϵ}\left(u\right)\right\}}_{ϵ}$, of stricdy convex functionals defined on $BV\left(\mathrm{\Omega };\left[-1,1\right]\right)$. Then both $\mathcal{F}$ and ${\mathcal{F}}_{ϵ}$, can be discretized by continuous linear finite elements. The convexity property of the functionals on $BV\left(\mathrm{\Omega };\left[-1,1\right]\right)$ is useful in the numerical minimization...

We show that the classical solution of the heat equation can be seen as the minimizer of a suitable functional defined in space-time. Using similar ideas, we introduce a functional $ℱ$ on the class of space-time tracks of moving hypersurfaces, and we study suitable minimization problems related with $ℱ$. We show some connections between minimizers of $ℱ$ and mean curvature flow.

We provide two examples of a regular curve evolving by curvature with a forcing term, which degenerates in a set having an interior part after a finite time.

Given an anisotropy ɸ on R3, we discuss the relations between the ɸ-calibrability of a facet F ⊂ ∂E of a solid crystal E, and the capillary problem on a capillary tube with base F. When F is parallel to a facet ̃︀ BFɸ of the unit ball of ɸ, ɸ-calibrability is equivalent to show the existence of a ɸ-subunitary vector field in F, with suitable normal trace on @F, and with constant divergence equal to the ɸ-mean curvature of F. Assuming E convex at F, ̃︀ BFɸ a disk, and F (strictly) ɸ-calibrable, such...

The numerical approximation of the minimum problem: ${min}_{A\subseteq \mathrm{\Omega }}\tilde{\mathcal{F}}\left(A\right)$, is considered, where $\tilde{\mathcal{F}}\left(A\right)=P_{\mathrm{\Omega }}\left(A\right)+\cos \left(\theta \right){\mathcal{H}}^{n-1}\left(\partial A\cap \partial \mathrm{\Omega }\right)-{\int }_A\kappa$. The solution to this problem is a set $A\subseteq \mathrm{\Omega }\subset {\mathbb{R}}^n$ with prescribed mean curvature $\kappa$ and contact angle $\theta$ at the intersection of $\partial A$ with $\partial \mathrm{\Omega }$. The functional $\tilde{\mathcal{F}}$ is first relaxed with a sequence of nonconvex functionals defined in $H^1\left(\mathrm{\Omega }\right)$ which, in turn, are discretized by finite elements. The $\mathrm{\Gamma }$-convergence of the discrete functionals to $\tilde{\mathcal{F}}$ as well as the compactness of any sequence of discrete absolute minimizers are proven.

We address the numerical minimization of the functional $\mathcal{F}\left(v\right)={\int }_{\mathrm{\Omega }}\left|Dv\right|+{\int }_{\partial \mathrm{\Omega }}\mu vd{\mathcal{H}}^{n-1}-{\int }_{\mathrm{\Omega }}xvdx$, for $v\in BV\left(\mathrm{\Omega };\left\{-1,1\right\}\right)$. We note that $\mathcal{F}$ can be equivalently minimized on the larger, convex, set $BV\left(\mathrm{\Omega };\left[-1,1\right]\right)$ and that, on that space, $\mathcal{F}$ may be regularized with a sequence $\mathit{\left\{}\mathcal{F}{}_{ϵ}\right(v)=\int {}_{\mathrm{\Omega }}\sqrt{{ϵ}^2+{\left|Dv\right|}^2}+\int {}_{\partial \mathrm{\Omega }}\mu vd\mathcal{H}{}^{n-1}-\int {}_{\mathrm{\Omega }}xvdx\mathit{\}}{}_{ϵ}$of regular functionals. Then both $\mathcal{F}$ and ${\mathcal{F}}_{ϵ}$ can be discretized by continuous linear finite elements. The convexity of the functionals in $BV\left(\mathrm{\Omega };\left[-1,1\right]\right)$ is useful for the numerical minimization of $\mathcal{F}$. We prove the $\mathrm{\Gamma }-L^1\left(\mathrm{\Omega }\right)$-convergence of the discrete functionals to $\mathcal{F}$ and present a few numerical examples.