The continuity equation: Difference between revisions

From Optimal Transport Wiki
Jump to navigation Jump to search
(Created page with "Chorin-Marsden (1-11); Santambrogio (123-126); Ambrosio-Brué-Semola (183-189)")
 
No edit summary
Line 1: Line 1:
Chorin-Marsden (1-11); Santambrogio (123-126); Ambrosio-Brué-Semola (183-189)
== Introduction ==
 
The continuity equation is an important equation in many science fields, for example, electromagnetism, computer vision, fluid dynamics etc. However, in the field of optimal transport, the formulation from fluid dynamics is of a large significance. This form helps to explain dynamics formulation of special cases of Wasserstein metric. 
 
 
There are many ways that we can describe [https://en.wikipedia.org/wiki/Wasserstein_metric Wasserstein metric]. One of them is to characterize absolutely continuos curves (AC)(p.188<ref name=Santambrogio />) and provide a dynamic formulation of the special case <math> W_{2}^{2} </math> Namely, it is possible to see <math> W_{2}^{2}(\mu, \nu) </math> as an infimum of the lengts of curves that satisfy [https://en.wikipedia.org/wiki/Continuity_equation Continuity equation].
 
== Continuity equation in fluid dynamics ==
 
First, we will introduce definition of the geodesic in general metric space <math> (X,d) </math>. In the following sections. we are going to follow a presentation from the book by Santambrogio<ref name="Santambrogio" /> with some digression, here and there.
 
For the starting point, we need to introduce length of the curve in our metric space <math> (X,d) </math>.
 
: '''Definition.''' A length of the curve <math> \omega:[0,1] \rightarrow X</math> is defined by
                  <math> L(\omega)=\sup\{ \sum_{j=0}^{n-1} d(\omega(t_{j}),\omega(t_{j+1})) | \quad n \geq 2,\quad 0=t_{0}<t_{1}<...<t_{n-1}=1 \} </math>
 
Secondly, we use the definition of length of a curve to introduce a geodesic curve.
 
: '''Definition.''' A curve <math> c:[0,1] \rightarrow X</math> is said to be geodesic between <math> x </math> and <math> y </math> in <math> X </math> if it minimizes the length <math> L(\omega)</math> among all the curves <math> \omega:[0,1] \rightarrow X</math> <br> such that <math> x=\omega(0)</math> and <math> y=\omega(1)</math>.
 
Since we have a definition of a geodesic in the general metric space, it is natural to think of Riemannian structure. It can be formally defined. More about this topic can be seen in the following article [http://34.106.105.83/wiki/ Formal Riemannian Structure of the Wasserstein_metric].
 
Now, we proceed with necessary definitions in order to be able to understand Wasserstein metric in a different way.
: '''Definition.''' A metric space <math> (X,d) </math> is called a length space if it holds
                    <math> d(x,y)=\inf \{ L(\omega) | \quad  \omega \in AC(X), \quad \omega(0)=x \quad \omega(1)=y \}.</math>
 
A space <math> (X,d) </math> is called geodesic space if the distance <math> d(x,y) </math> is attained for some curve <math> \omega </math>.
 
: '''Definition.''' In a length space, a curve <math> \omega:[0,1]\rightarrow X </math> is said to be constant speed geodesic between <math> \omega(0)</math> and <math> \omega(1)</math> in <math> X </math> if it satisfies
 
                    <math> d(\omega(s),\omega(t))=|t-s|d(\omega(0),\omega(1)) </math> for all <math> t,s \in [0,1]</math>
 
It is clear that constant-speed geodesic curve <math> \omega </math> connecting <math> x  </math> and <math> y </math> is a geodesic curve. This is very important definition since we have that every constant-speed geodesic <math> \omega </math> is also in <math> AC(X) </math> where <math> |\omega'(t)|=d(\omega(0),\omega(1)) </math> almost everywhere in <math> [0,1] </math>. <br>
In addition, minimum of the set <math> \{ \int_{0}^{1}|c'(t)|^{p}dt |  c:[0,1]\rightarrow X, c(0)=x, c(1)=y \} </math> is attained by our constant-speed geodesic curve <math> \omega.</math> Last fact is important since it is connected to Wasserstein <math>p</math> metric. For more information, please take a look at [https://en.wikipedia.org/wiki/Wasserstein_metric Wasserstein metric].
 
For more information on constant-speed geodesics, especially how they depend on uniqueness of the plan that is induced by transport and characterization of a constant-speed geodesic look at the book by L.Ambrosio, N.Gilgi, G.Savaré <ref name="Ambrosio" /> or the book by Santambrogio<ref name="Santambrogio" />.
 
== Continuity equation in optimal transport ==
 
Finally, we can rephrase Wasserstein metrics in dynamic language as mentioned in the Introduction.
 
Whenever <math> \Omega \subseteq \mathcal{R}^{d} </math> is convex set, <math> W_{p}(\Omega) </math> is a geodesic space. Proof can be found in the book by Santambrogio<ref name="Santambrogio" />.
 
: '''Theorem.'''<ref name=Santambrogio /> Let <math> \mu, \nu \in \mathcal{P}_{2}(R^{d}) </math>. Then
      <math> W_{p}^{p}(\mu, \nu)=\inf_{(\mu(t).\nu(t))} \{\int_{0}^{1} |v(,t)|_{L^{p}(\mu(t))}^{p}dt \quad | \quad \partial_{t}\mu+\nabla\cdot(v\mu)=0,\quad \mu(0)=\mu,\quad \mu(1)=\nu \}. </math>
 
In special case, when <math> \Omega </math> is compact, infimum is attained by some constant-speed geodesic.
 
== Applications ==
 
There are many ways to generalize this fact. We will talk about a special case <math> p=2 </math> and a displacement convexity.
Here we follow again book by Santambrogio<ref name="Santambrogio1" />.
 
In general, the functional <math> \mu \rightarrow W_{2}^{2}(\mu,\nu) </math> is not a displacement convex. We can fix this by introducing a generalized geodesic.
 
: '''Definition.''' Let <math> \rho \in \mathcal{P}(\Omega) </math> be an absolutely continuous measure and <math> \mu_{0} </math> and <math> \mu_{1} </math> probability measures in <math> \mathcal{P}(\Omega) </math>. We say that <math> \mu_{t} = ((1-t)T_{0}+tT_{1})\#\rho </math> <br> is a generalized geodesic in <math> \mathcal{W}_{2}(\Omega) </math> with base <math> \rho </math>, where <math> T_{0} </math> is the optimal transport plan from <math> \rho </math> to <math> \mu_{0} </math> and <math> T_{1} </math> is the optimal transport plan from <math> \rho </math> to <math> \mu_{1} </math>.
 
By calculation, we have the following <math> W_{2}^{2}(\mu_{t},\rho) \leq (1-t)W_{2}^{2}(\mu_{0},\rho) + tW_{2}^{2}(\mu_{1},\rho). </math>
 
Therefore, along the generalized geodesic, the functional <math> t \rightarrow W_{2}^{2}(\mu_{t},\rho) </math> is convex.
 
This fact is very important in establishing uniqueness and existence theorems in the geodesic flows.
 
= References =
 
<references>
 
<ref name="Marsden"> [https://link.springer.com/book/10.1007/978-1-4612-0883-9 A.J.Chorin, J.E.Marsden, ''A Mathematical Introduction to Fluid Mechanics'', Chapter 1, pages 1-11] </ref>
 
<ref name="Santambrogio"> [https://link.springer.com/book/10.1007/978-3-319-20828-2 F. Santambrogio, ''Optimal Transport for Applied Mathematicians'', Chapter 4, pages 123-126] </ref>
 
<ref name="Ambrosio"> [https://link.springer.com/book/10.1007/978-3-030-72162-6 L.Ambrosio, E.Brué, D.Semola, ''
Lectures on Optimal Transport'', Lecture 16.1., pages 183-189] </ref>
 
</references>

Revision as of 03:52, 12 February 2022

Introduction

The continuity equation is an important equation in many science fields, for example, electromagnetism, computer vision, fluid dynamics etc. However, in the field of optimal transport, the formulation from fluid dynamics is of a large significance. This form helps to explain dynamics formulation of special cases of Wasserstein metric.


There are many ways that we can describe Wasserstein metric. One of them is to characterize absolutely continuos curves (AC)(p.188[1]) and provide a dynamic formulation of the special case Namely, it is possible to see as an infimum of the lengts of curves that satisfy Continuity equation.

Continuity equation in fluid dynamics

First, we will introduce definition of the geodesic in general metric space . In the following sections. we are going to follow a presentation from the book by Santambrogio[1] with some digression, here and there.

For the starting point, we need to introduce length of the curve in our metric space .

Definition. A length of the curve is defined by
                  

Secondly, we use the definition of length of a curve to introduce a geodesic curve.

Definition. A curve is said to be geodesic between and in if it minimizes the length among all the curves
such that and .

Since we have a definition of a geodesic in the general metric space, it is natural to think of Riemannian structure. It can be formally defined. More about this topic can be seen in the following article Formal Riemannian Structure of the Wasserstein_metric.

Now, we proceed with necessary definitions in order to be able to understand Wasserstein metric in a different way.

Definition. A metric space is called a length space if it holds
                    

A space is called geodesic space if the distance is attained for some curve .

Definition. In a length space, a curve is said to be constant speed geodesic between and in if it satisfies
                     for all 

It is clear that constant-speed geodesic curve connecting and is a geodesic curve. This is very important definition since we have that every constant-speed geodesic is also in where almost everywhere in .
In addition, minimum of the set is attained by our constant-speed geodesic curve Last fact is important since it is connected to Wasserstein metric. For more information, please take a look at Wasserstein metric.

For more information on constant-speed geodesics, especially how they depend on uniqueness of the plan that is induced by transport and characterization of a constant-speed geodesic look at the book by L.Ambrosio, N.Gilgi, G.Savaré [2] or the book by Santambrogio[1].

Continuity equation in optimal transport

Finally, we can rephrase Wasserstein metrics in dynamic language as mentioned in the Introduction.

Whenever is convex set, is a geodesic space. Proof can be found in the book by Santambrogio[1].

Theorem.[1] Let . Then
      

In special case, when is compact, infimum is attained by some constant-speed geodesic.

Applications

There are many ways to generalize this fact. We will talk about a special case and a displacement convexity. Here we follow again book by Santambrogio[3].

In general, the functional is not a displacement convex. We can fix this by introducing a generalized geodesic.

Definition. Let be an absolutely continuous measure and and probability measures in . We say that
is a generalized geodesic in with base , where is the optimal transport plan from to and is the optimal transport plan from to .

By calculation, we have the following

Therefore, along the generalized geodesic, the functional is convex.

This fact is very important in establishing uniqueness and existence theorems in the geodesic flows.

References

  1. 1.0 1.1 1.2 1.3 1.4 F. Santambrogio, Optimal Transport for Applied Mathematicians, Chapter 4, pages 123-126
  2. [https://link.springer.com/book/10.1007/978-3-030-72162-6 L.Ambrosio, E.Brué, D.Semola, Lectures on Optimal Transport, Lecture 16.1., pages 183-189]
  3. Cite error: Invalid <ref> tag; no text was provided for refs named Santambrogio1

Cite error: <ref> tag with name "Marsden" defined in <references> is not used in prior text.