Linear equations and superposition of wavefunctions

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dyn
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Hi. I have read many times that the Schrödinger equation is a linear equation and so if Ψ1 and Ψ2 are both solutions to the equation then so is Ψ1 + Ψ2. Is this use of the word linear the same as generally used for differential equations ? As the Schrödinger equation is also an eigenvalue equation for the Hamiltonian.

My main confusion is why a superposition of wavefunctions such as eikx + e-ikx is not a solution to the momentum eigenvalue equation as this also looks like a linear equation ?
Thanks
 
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dyn said:
Is this use of the word linear the same as generally used for differential equations ?
Yes.
dyn said:
My main confusion is why a superposition of wavefunctions such as eikx + e-ikx is not a solution to the momentum eigenvalue equation as this also looks like a linear equation ?
Because the summands correspond to different eigenvalues.
 
Thanks. So the condition that the superposition of wavefunctions also solves the eigenvalue equation is that it is both linear and the wavefunctions also have the same eigenvalues ?
 
dyn said:
Thanks. So the condition that the superposition of wavefunctions also solves the eigenvalue equation is that it is both linear and the wavefunctions also have the same eigenvalues ?
Yes. (Eigenvalue equations are usually linear, by the way. There does exist something called a "nonlinear eigenvalue problem", but that is not relevant here.)

The SE is a partial differential equation, but for your understanding perhaps consider the setting of a linear ordinary differential equation. In the simplest case (constant coefficients, homogeneous) a linear ODE can be written as
$$
\frac{dx}{dt}(t) = Ax(t) \qquad (\ast)
$$
(Think, for example, about the simple harmonic oscillator.) If ##x_1## and ##x_2## are both solutions, then their sum is also a solution and hence satisfies ##(\ast)##. This is superposition.

Regarding the corresponding eigenvalue problem, if ##\lambda## and ##\mu## are distinct eigenvalues of ##A## with eigenvectors ##u## and ##v##, then ##u + v## is not an eigenvector of ##A##. (Try it out.) In contrast, if ##\lambda = \mu## then it is true that
$$
A(u + v) = \lambda(u + v)
$$
In case of the SE similar remarks hold, but the matrices are replaced by (unbounded) operators that act on function spaces instead of ##\mathbb{R}^n## or ##\mathbb{C}^n##. Does this clarify matters a bit?
 
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Yes. Thanks for your help.