What Conditions on f Ensure a Good Solution for u(s, t)?

In summary, the question is about the conditions necessary for a good solution of a set of partial differential equations involving an unknown function u(s,t) and two variables s and t, with the focus on cases where the functions f and g may or may not explicitly depend on s, t, and u. The key condition for a solution to exist is that the two partial differential equations are compatible, and the two cases of interest are when f and g are independent of u, and when they are also independent of t and s.
  • #1
CompuChip
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Hi.

I'm not so well-versed in the topic of partial differential equations, but the following question has arisen.

Suppose that for some unknown function u(s, t) of two variables, we have a set of differential equations
[tex]\left\{ \begin{matrix} u_s(s, t) & {} = f(s, t, u(s, t)) \\ u_t(s, t) & {} = g(s, t, u(s, t)) \end{matrix} \right. [/tex]
where us denotes the partial derivative of u(s, t) w.r.t. s.

My question is, what the conditions on f would have to be in order to have a good solution for u(s, t). For example, we can integrate the first one to get u(s, T) for fixed t = T, and similarly the second one will give u(S, t) for fixed s = S, but of course u(S, T) must be well-defined (i.e. single-valued).

I am particularly interested in the case where f and g do not depend on s and t explicitly (i.e. only through u(s, t)) and the case where they do not depend on u(s, t) explicitly.

Thanks for sharing your thoughts.
 
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  • #2
CompuChip said:
Hi.

I'm not so well-versed in the topic of partial differential equations, but the following question has arisen.

Suppose that for some unknown function u(s, t) of two variables, we have a set of differential equations
[tex]\left\{ \begin{matrix} u_s(s, t) & {} = f(s, t, u(s, t)) \\ u_t(s, t) & {} = g(s, t, u(s, t)) \end{matrix} \right. [/tex]
where us denotes the partial derivative of u(s, t) w.r.t. s.

My question is, what the conditions on f would have to be in order to have a good solution for u(s, t). For example, we can integrate the first one to get u(s, T) for fixed t = T, and similarly the second one will give u(S, t) for fixed s = S, but of course u(S, T) must be well-defined (i.e. single-valued).

I am particularly interested in the case where f and g do not depend on s and t explicitly (i.e. only through u(s, t)) and the case where they do not depend on u(s, t) explicitly.

Thanks for sharing your thoughts.
For a solution to exist you certainly want that your two PDEs are compatible, i.e.

[tex]u_{ts} = u_{st}[/tex] which gives [tex]f_t + g f_u = g_s + g_u f[/tex]

The two cases your interested in

(i) f and g independent of u [text]f_t = g_s[/tex]
(ii) f and g independent of t and s so [tex]g f_u = f g_u[/tex] so [tex]f = c \;g[/tex] for some constant c.
 

FAQ: What Conditions on f Ensure a Good Solution for u(s, t)?

What are partial differential equations (PDEs)?

Partial differential equations are mathematical equations that involve multiple independent variables and their partial derivatives. They are used to model complex systems and phenomena in physics, engineering, and other scientific fields.

What are the applications of PDEs?

PDEs have a wide range of applications in various fields such as fluid dynamics, quantum mechanics, heat transfer, and financial mathematics. They can be used to model and understand complex systems and phenomena in these fields.

What is the difference between ordinary differential equations (ODEs) and PDEs?

The main difference between ODEs and PDEs is that ODEs involve only one independent variable, while PDEs involve multiple independent variables. ODEs are often used to model systems that change over time, while PDEs are used to model systems that change over both space and time.

What are the different types of PDEs?

There are several types of PDEs, including elliptic, parabolic, and hyperbolic equations. Elliptic equations describe steady-state behavior, parabolic equations describe time-dependent behavior, and hyperbolic equations describe wave-like behavior.

How are PDEs solved?

PDEs are typically solved using analytical or numerical methods. Analytical methods involve finding a closed-form solution using mathematical techniques such as separation of variables or Fourier transforms. Numerical methods involve approximating the solution using numerical algorithms and computer simulations.

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