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Exact(1)
If we want equality for every pair (t, s), we need to require the slope to be an upper gradient.
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In general, it is not true that the slope is an upper gradient, but we will give conditions to guarantee that it is.
This representation as a (sup ) allows to prove semicontinuity of the slope.4 It is also possible (see [2], for instance) to prove that the slope is an upper gradient.
usual convex combinations (mu _s 1-s mu _s 1-s mu), which is meaningful in the set of probability measures), such that (|nabla ^-F |) is an upper gradient for F and such that (|nabla ^- F|^2) is convex, then for every initial measure (bar{mu }) there exists at most one gradient flow (mu (t)) in the EDE sense for the functional F satisfying (mu (0)=bar{mu }).
On the one hand, functions smooth enough could satisfy the assumptions on the semi-continuity of F and of (|nabla ^-F|) and the fact that (|nabla ^-F|) is an upper gradient independently of convexity; on the other hand the discrete scheme already provides a method, well-posed under much weaker assumptions, to find a limit curve.
Indeed, we have two good points: the slope is automatically l.s.c., and it is automatically an upper gradient.
"It's an upper.
"There's an upper bound.
Now it should be a gradient field.
You want there to be a gradient.
This also indicates that the gradient is an activity gradient, not an expression gradient.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com