Optimal Transport in One Dimension: Difference between revisions
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== Distance Cost Example == | == Distance Cost Example == | ||
Consider the cost function <math> c(x,y) = |x-y|</math> along with probability measures (on <math> \mathbb{R} </math>) <math> \mu </math> and <math> \nu . Then, for any <math> (x,y) \in spt(\mu) \times spt(\nu) </math> we see that <math> c(x,y) = y-x </math>, which then immediately puts us back in the linear cost position, so any transport map/plan is also optimal for such costs. | Consider the cost function <math> c(x,y) = |x-y|</math> along with probability measures (on <math> \mathbb{R} </math>) <math> \mu </math> and <math> \nu </math>. Then, for any <math> (x,y) \in spt(\mu) \times spt(\nu) </math> we see that <math> c(x,y) = y-x </math>, which then immediately puts us back in the linear cost position, so any transport map/plan is also optimal for such costs. | ||
==Book Shifting Example== | ==Book Shifting Example== | ||
Consider the cost function | Consider the cost function |
Revision as of 04:21, 12 February 2022
In this article, we explore the optimal transport problem on the real line along with some examples.
Linear Cost Example
For this example, consider the cost function along with a given linear map . Moreover, if let be any transport plan, then by direct computation we see that
which suggests that this result only depends on the marginals of (wherein and are compactly supported probability measures). In fact, in such cases, every transport plan/map is optimal.
Distance Cost Example
Consider the cost function along with probability measures (on ) and . Then, for any we see that , which then immediately puts us back in the linear cost position, so any transport map/plan is also optimal for such costs.
Book Shifting Example
Consider the cost function