Basic question about certain second order PDE's

In summary: A_{22} = Γ^{1}_{22}## ##B_{22} = Γ^{2}_{22}##In summary, the given second order equation, ##X_{uv} = A(u,v)X_{u} + B(u,v)X_{v}##, defined on a domain ##(u,v)## in the plane with ##X## being a three dimensional vector and ##A## and ##B## being arbitrary smooth functions, determines a surface in ##R^3## when the Jacobian of the map ##(u,v) \rightarrow X(u,v)## has rank 2 everywhere. The regular value theorem states that if (u,v) is a regular value of a smooth function,
  • #1
lavinia
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Given is the second order equation,

##X_{uv} = A(u,v)X_{u} + B(u,v)X_{v}## defined on a domain ##(u,v)## in the plane.

##X## is a three dimensional vector and ##A## and ##B## are arbitrary smooth functions.

When does such an equation determine a surface in ##R^3## and what in general can be said about the set of solutions?

Same question for ##X_{uu} = A(u,v)X_{u} + B(u,v)X_{v}##
 
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  • #2
A standard result, the regular value theorem, is that if (u,v) is a regular value of a smooth function, then : https://en.wikipedia.org/wiki/Preimage_theorem , i.e., given a smooth map, the inverse image of a regular value is a submanifold. Let me see if I can apply that to your situation.

I assume you are using X=Y =##\mathbb R^3 ##
 
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  • #3
WWGD said:
A standard result, the regular value theorem, is that if (u,v) is a regular value of a smooth function, then : https://en.wikipedia.org/wiki/Preimage_theorem , i.e., given a smooth map, the inverse image of a regular value is a submanifold. Let me see if I can apply that to your situation.

I assume you are using X=Y =##\mathbb R^3 ##
Right. So the Jacobian of the map ##(u,v) \rightarrow X(u,v)## has to have rank 2 everywhere. Since each of the components of ##X(u,v)## is a scalar solution to the equation, this says something about the independence of these solutions. Do such triples of scalar solutions always exist?

Here is where this question came from. If one is given a parameterized surface, ##X(u,v)## in ##R^3## then one has the tangent vectors, ##X_{u}## and ##X_{v}## and the induced Riemannian metric, which in classical notation is ##X_{u}⋅X_{u} = E##, ##X_{u}⋅X_{v} = F##, ##X_{v}⋅X_{v} = G##.

##X_{u}## and ##X_{v}## are a basis for the tangent space and together with a positively oriented unit normal,##N##, form a moving frame. In terms of this frame one can write down the second derivatives of ##X(u,v)## and one gets three equations,

## X_{uu} = A_{11}(u,v)X_{u} + B_{11}(u,v)X_{v} + eN##
##X_{uv} = A_{12}(u,v)X_{u} + B_{12}(u,v)X_{v} + fN##
##X_{vv} = A_{22}(u,v)X_{u} + B_{22}(u,v)X_{v} + gN##

The ##A##'s and the ##B##'s are actually the Christoffel symbols of the Riemannian metric and ##e## ##f## and ##g## are the coefficients of the second fundamental form in ##(u,v)## coordinates. If ##f## is zero then the parameter curves ##u=## a constant and ##v=## are said to be conjugate.

But if ##f = 0## the one has the first differential equation that I asked about. So the second part of the question can be thought of as how much of a surface can be retrieved from the Christoffel symbols, ##A_{12}## and ##B_{12}## if the coordinate lines are assumed to be conjugate.

I suppose come to think of it, the answer is trivial. It is all surfaces expressed in conjugate coordinates. This was mentioned in Struik's book but I just didn't get it until reasoning through in this post.

BTW: ##A_{12} = Γ^{1}_{12}## ##B_{12} = Γ^{2}_{12}## ##A_{11} = Γ^{1}_{11}## ##B_{11} = Γ^{2}_{11}##
 
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Related to Basic question about certain second order PDE's

1. What is a second order partial differential equation (PDE)?

A second order PDE is a mathematical equation that involves two independent variables and second-order derivatives of an unknown function. It is commonly used to model physical phenomena in fields such as physics, engineering, and finance.

2. How do you solve a second order PDE?

The method for solving a second order PDE depends on the specific equation and boundary conditions. Some common techniques include separation of variables, the method of characteristics, and numerical methods such as finite difference or finite element methods.

3. What are the types of second order PDEs?

There are three main types of second order PDEs: elliptic, parabolic, and hyperbolic. Elliptic PDEs involve the Laplace operator and have no time dependence. Parabolic PDEs involve the heat equation and have one time derivative. Hyperbolic PDEs involve the wave equation and have two time derivatives.

4. What are some applications of second order PDEs?

Second order PDEs have many applications in fields such as physics, engineering, finance, and biology. They are commonly used to model diffusion, heat transfer, wave propagation, and fluid flow, among others.

5. What are the differences between first and second order PDEs?

The main difference between first and second order PDEs is the number of independent variables and derivatives involved. First order PDEs have one independent variable and first-order derivatives, while second order PDEs have two independent variables and second-order derivatives. Additionally, first order PDEs are typically easier to solve and have a wider range of solution techniques compared to second order PDEs.

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