Optimal Transport and the Monge Ampère equation: Difference between revisions

From Optimal Transport Wiki
Jump to navigation Jump to search
No edit summary
 
(57 intermediate revisions by 2 users not shown)
Line 1: Line 1:
The Monge Ampere equation<ref name="Santambrogio" />
The Monge Ampère equation<ref name="Santambrogio" /> is an nonlinear second-order elliptic partial differential equation. The [[Monge Problem]] optimizes a cost function over the set of transport maps that push forward a fixed probability measure, <math> \mu </math>, to another fixed probability measure, <math> \nu </math>. Given sufficient regularity conditions on the two measures, one can show that solving the corresponding Monge Ampère equation is equivalent to being a transport map for <math> \mu </math> and <math> \nu </math>.
== Deriving the Monge Ampère equation from the Monge Problem ==
The appropriate variant of the [[Monge Problem]] for this situation is
 
:<math> \inf_{T} \left \{ F(T) := \int_{X} |x - T(x)|^2 d \mu \right \} </math>
 
Where the infimum is taken over all transport maps, <math> T </math>, that push forward <math> \mu </math> to <math> \nu </math>. Consider the case when <math> \mu, \nu </math> are absolutely continuous, where <math> \mu </math> is the starting measure, and <math> \nu = T_\# \mu </math>. Say <math> f </math> and <math> g </math> are the densities of <math> \mu </math> and <math> \nu </math> respectively. Moreover, let <math> T: X \to X </math> be <math> C^1 </math> and injective. The change of variables formula tells us that <math>T</math> pushes forward <math> \mu </math> to <math> \nu </math> if and only if`
 
:<math>  g(y) = \frac{f(T^{-1}(y))}{\det (DT(T^{-1}(y)))} </math>
 
For this particular variant of the Monge problem, the cost function is quadratic. It can be shown that this implies when <math> T </math> is optimal, <math> T = \nabla u </math> where <math> u </math> is convex. If we require <math> u </math> to be strictly convex, <math> T </math> is guaranteed to be injective. Once <math> \nabla u </math> is substituted for <math> T </math> in the change of variables formula, one obtains
 
:<math> \det (D^2 u(x)) = \frac{f(x)}{g(\nabla u(x))} </math>
The above equation is a type of Monge Ampère equation. Note that since <math> u </math> from above is assumed to be convex, the Jacobian term is positive. Moreover, <math> \det D^2(u(x)) </math> has a monotonicity property when <math> D^2(u(x)) \le D^2(u(y)) </math>.
The specific boundary problem that is relevant to our Monge Problem is <math> \nabla u(\Omega) = \Omega' </math>. In this case, <math> \Omega </math> is the domain for the measure <math> \mu </math>, and <math> \Omega' </math> is the domain for the measure <math> \nu </math>. When <math> u </math> is a homeomorphism, this implies that <math> u(\partial\Omega) = \partial\Omega' </math>. Solutions to this boundary value problem and the Monge Ampère equation gives us information about the optimal transport map. For example, regularity of the solutions to our boundary value problem implies regularity for the optimal transport map.
 
== Notable Properties of the Monge Ampère equation ==
Properties of solutions to the Monge Ampère equation give us information about the optimal transport map. This relationship stems from the following regularity result by Caffarelli.
 
: '''Theorem.'''<ref name=Villani /> If <math> f </math> and <math> g </math> are <math> C^{0, \alpha}(\Omega) </math> and are both bounded from above and from below on the whole <math> \Omega </math> by positive constants and <math> \Omega </math> is a convex open set, then the unique Brenier solution of <math> u </math> of the Monge Ampère equation belongs to <math> C^{2, \alpha} (\Omega) \cap C^{1, \alpha} {\overline{\Omega}} </math>, and <math> u </math> satisfies the equation in the classical sense.
 
<math> u </math> satisfies the Monge Ampère equation in the Brenier sense if <math> (\nabla u)_\# (f \cdot \mathcal{L}^d) = (g \cdot \mathcal{L}^d) </math>. <math> u </math> is a classical solution if it satisfies the Monge Ampère equation at every point in <math> \Omega </math> and the corresponding boundary value conditions. Note that being a Brenier solution implies that <math> \nabla u </math> is a transport map for appropriate <math> f </math> and <math> g </math>. In particular, we would like <math> f </math> and <math> g </math> to define probability measures absolutely continuous to the Lebesgue measure. This implies that given the appropriate regularity conditions on <math> \mu </math> and <math> \nu </math> for our Monge Problem, we can study classical solutions to the corresponding Monge Ampère equation instead.


==References==
==References==
<references>
<references>
<ref name="Santambrogio">[https://link.springer.com/book/10.1007/978-3-319-20828-2 F. Santambrogio, ''Optimal Transport for Applied Mathematicians'', Chapter 1.]</ref>
<ref name="Santambrogio">[https://link.springer.com/book/10.1007/978-3-319-20828-2 F. Santambrogio, ''Optimal Transport for Applied Mathematicians'', p. 54-57]</ref>
<ref name="Villani">[https://people.math.gatech.edu/~gangbo/Cedric-Villani.pdf C. Villani, ''Topics in Optimal Transportation'', p. 137-141]</ref>
</references>
</references>

Latest revision as of 04:36, 28 February 2022

The Monge Ampère equation[1] is an nonlinear second-order elliptic partial differential equation. The Monge Problem optimizes a cost function over the set of transport maps that push forward a fixed probability measure, , to another fixed probability measure, . Given sufficient regularity conditions on the two measures, one can show that solving the corresponding Monge Ampère equation is equivalent to being a transport map for and .

Deriving the Monge Ampère equation from the Monge Problem

The appropriate variant of the Monge Problem for this situation is

Where the infimum is taken over all transport maps, , that push forward to . Consider the case when are absolutely continuous, where is the starting measure, and . Say and are the densities of and respectively. Moreover, let be and injective. The change of variables formula tells us that pushes forward to if and only if`

For this particular variant of the Monge problem, the cost function is quadratic. It can be shown that this implies when is optimal, where is convex. If we require to be strictly convex, is guaranteed to be injective. Once is substituted for in the change of variables formula, one obtains

The above equation is a type of Monge Ampère equation. Note that since from above is assumed to be convex, the Jacobian term is positive. Moreover, has a monotonicity property when . The specific boundary problem that is relevant to our Monge Problem is . In this case, is the domain for the measure , and is the domain for the measure . When is a homeomorphism, this implies that . Solutions to this boundary value problem and the Monge Ampère equation gives us information about the optimal transport map. For example, regularity of the solutions to our boundary value problem implies regularity for the optimal transport map.

Notable Properties of the Monge Ampère equation

Properties of solutions to the Monge Ampère equation give us information about the optimal transport map. This relationship stems from the following regularity result by Caffarelli.

Theorem.[2] If and are and are both bounded from above and from below on the whole by positive constants and is a convex open set, then the unique Brenier solution of of the Monge Ampère equation belongs to , and satisfies the equation in the classical sense.

satisfies the Monge Ampère equation in the Brenier sense if . is a classical solution if it satisfies the Monge Ampère equation at every point in and the corresponding boundary value conditions. Note that being a Brenier solution implies that is a transport map for appropriate and . In particular, we would like and to define probability measures absolutely continuous to the Lebesgue measure. This implies that given the appropriate regularity conditions on and for our Monge Problem, we can study classical solutions to the corresponding Monge Ampère equation instead.

References