Graduate Separation of variables possible in this problem?

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Separation of variables is not straightforward for the equation au_{xx} + bu_{yy} + cu_{xy} = u + k due to the mixed derivative term u_{xy} and the nonhomogeneous term k. To simplify, one can substitute u(x,y) = f(x,y) - k, transforming the equation into a homogeneous form. The mixed derivative can sometimes be addressed by first attempting separation of variables, then differentiating with respect to y to potentially yield a separable equation. Additionally, ensuring that boundary conditions are separable along constant x and y curves is crucial for applying this method. A change of variables can also lead to a separable equation after diagonalizing the left-hand side.
DuckAmuck
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Second order linear partial differential equation
Is it possible to use separation of variables on this equation?
au_{xx} + bu_{yy} + c u_{xy} = u + k
Where u is a function of x and y, abck are constant.
I tried the u(x,y) = X(x)Y(y) type of separation but I think something more clever is needed.

Thank you.
 
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Yes, something more clever will be required because presence of the ##u_{xy}## term as well as the nonhomogeneous term ##k## mean that straightforward separation of variables will not work. Getting rid of ##k## is easy: let ##u(x,y) = f(x,y) - k## and the equation for ##f## is homogeneous. Dealing with the ##u_{xy}## term isn't so easy, but sometimes a trick applies. First try separation of variables so you have an equation with terms such as ## \frac{X^{\prime\prime}(x)}{X(x)}##, etc. Then, differentiate that equation with respect to ##y##; the resulting equation might be separable.

Of course, even if the equation is separable you still need separable boundary conditions along curves of constant ##x## and ##y## in order for separation of variables to apply to your problem.

jason
 
By looking at the discriminant (C^2 - 4AB in this case) you can make a variable substitution and get a separable equation.
 
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Yes, after making a change of variables.

The left hand side is <br /> \begin{pmatrix} \frac{\partial}{\partial x} &amp; \frac{\partial}{\partial y} \end{pmatrix}<br /> \begin{pmatrix} a &amp; \frac12 b \\ \frac12 b &amp; c \end{pmatrix}<br /> \begin{pmatrix} \frac{\partial}{\partial x} \\ \frac{\partial}{\partial y} \end{pmatrix} u<br /> This can be diagonalized to <br /> \lambda_1 \frac{\partial^2 u}{\partial s^2} + \lambda_2 \frac{\partial^2 u}{\partial t^2} where s and t are linear combinations of x and y. Setting \phi = u + k now yields <br /> \lambda_1 \frac{\partial^2 \phi}{\partial s^2} + \lambda_2 \frac{\partial^2 \phi}{\partial t^2} = \phi which is separable.
 
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