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Mar 28, 2016 at 9:06 comment added Aryeh Kontorovich Thanks again. I guess there's a reason why the Hardy-Krause extension to higher dimensions is so complicated.
Mar 27, 2016 at 21:09 comment added Willie Wong The scaling is still not right in two dimensions. Again let $f(x,y) = x$ on $[0,1]\times[0,1]$. The lattice of multiples of $1/k$ forms more-or-less a $1/k$-net. For each of the squares you have $\sup f - \inf f = 1/k$. And you have a total of $k^2$ squares. Take $k\to \infty$ you still get blow-up. The $\sup f - \inf f$ definition captures what I feel more like a 1 dimension effect. Summing over a 2-dimensional (or higher) grid will always lead to blow-up.
Mar 26, 2016 at 17:08 comment added Aryeh Kontorovich @WillieWong One last attempt before giving this a rest. What if we consider an $\epsilon$-net (i.e., minimal cover/maximal packing), and then take $\mathcal{P}_n$ to be the Voronoi regions induced by the net points?
Mar 22, 2016 at 20:11 comment added Christian Remling Maybe a better way to go about it is to recall that $f\in BV$ if and only if (the distribution) $f'$ is a measure, and then generalize this condition.
Mar 22, 2016 at 16:29 comment added Willie Wong JFYI: the paper on arXiv you linked to in your last comment, in spite of the title, actually considers metric measure spaces, and not just metric spaces.
Mar 22, 2016 at 15:33 comment added Aryeh Kontorovich Very nice example, @WillieWong, and thanks Suvrit for the link. I was also pointed to arxiv.org/pdf/1301.6897v1.pdf . So I guess it's time to quite amateur conjecturing and start reading...
Mar 22, 2016 at 15:31 comment added Suvrit On a related note, have you already considered the following: archive.numdam.org/ARCHIVE/ASNSP/ASNSP_1990_4_17_3/…
Mar 22, 2016 at 15:17 comment added Willie Wong For your EDIT II: let your metric space be $[0,1]\times[0,1]$ and let $f(x,y) = x$. Let $n > 1$. Take $(x_i,y_i) = (0, i / (n-1))$ for $i < n$. Then for the $\mathcal{P}_n$ adapted to $\{(x_i,y_i)\}_{i = 0, \ldots, n-1}$ you have that $$ \sum_{A\in \mathcal{P}_n} (\sup_A f - \inf_A f) = n $$ So after taking the sup in $n$ you get that this function has infinite total variation by your definition.
Mar 22, 2016 at 15:13 comment added Willie Wong There is some notion of BV functions for metric measure spaces, which seems more natural when looking at the definition for BV in several real variables. Google gives a bunch of results, two of which are cvgmt.sns.it/paper/2738 and sciencedirect.com/science/article/pii/S0021782403000369
Mar 22, 2016 at 14:00 history edited Aryeh Kontorovich CC BY-SA 3.0
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Mar 22, 2016 at 13:16 comment added Aryeh Kontorovich Thank you for that example, @MartinHairer. Rather than risk further embarrassment with additional edits, let me try to continue in the comments. Suppose I define $\mathcal{P}_n$ to be the Voronoi partition induced by some $n$ points, and define the variation to be the supremum over all $\mathcal{P}_n$. Does this still admit pathological examples?
Mar 22, 2016 at 13:02 comment added Martin Hairer Blocks in a partition don't need to be connected. In particular, one can easily have a partition of $[0,1]$ into $1/\epsilon^2$ blocks of diameter $\epsilon$, so the identity map still has infinite variation with the new definition. There is a notion of BV for functions of several real variables (see Wikipedia), but I am not sure that it generalises well. One naive generalisation would be to ask that $f\circ g$ is BV, uniformly over all $g \colon \mathbb{R} \to X$ having Lipschitz constant $1$.
Mar 22, 2016 at 12:49 comment added Aryeh Kontorovich You're of course right, @AugustCleaner! I tried to fix this in the edited version.
Mar 22, 2016 at 12:48 history edited Aryeh Kontorovich CC BY-SA 3.0
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Mar 22, 2016 at 10:14 comment added August Cleaner I turn your attention to the fact that the suggested notion is quite different from the classical, e.g. the function $y=x$ on $[0,1]$ has infinite variation. Also this notion does not depend on the metric.
Mar 22, 2016 at 9:36 history asked Aryeh Kontorovich CC BY-SA 3.0