Difference between revisions of "Properties of the Linear Schrodinger Equation"

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  | previous chapter = [[Introduction to the Inverse Scattering Transform]]
 
  | previous chapter = [[Introduction to the Inverse Scattering Transform]]
 
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The linear Schrodinger equation
 
<center><math>
 
\partial_{x}^{2}w+uw=-\lambda w
 
</math></center>
 
has two kinds of solutions for <math>u\rightarrow0</math> as <math>x\rightarrow\pm\infty.</math> The
 
first are waves and the second are bound solutions. It is well known that
 
there are at most a finite number of bound solutions (provided <math>u\rightarrow0</math>
 
as <math>x\pm\infty</math> sufficiently rapidly) and a continum of solutions for the
 
incident waves. This is easiest seen through the following examples
 
 
=Properties of the Linear Schrodinger Equation=
 
  
 
The linear Schrodinger equation
 
The linear Schrodinger equation

Revision as of 10:16, 23 September 2010

Nonlinear PDE's Course
Current Topic Properties of the Linear Schrodinger Equation
Next Topic Properties of the Linear Schrodinger Equation
Previous Topic Introduction to the Inverse Scattering Transform


The linear Schrodinger equation

[math]\displaystyle{ \partial_{x}^{2}w+uw=-\lambda w }[/math]

has two kinds of solutions for [math]\displaystyle{ u\rightarrow0 }[/math] as [math]\displaystyle{ x\rightarrow\pm\infty. }[/math] The first are waves and the second are bound solutions. It is well known that there are at most a finite number of bound solutions (provided [math]\displaystyle{ u\rightarrow0 }[/math] as [math]\displaystyle{ x\pm\infty }[/math] sufficiently rapidly) and a continum of solutions for the incident waves. This is easiest seen through the following examples

Example [math]\displaystyle{ \delta }[/math] function potential

We consider here the case when [math]\displaystyle{ u\left( x,0\right) =\delta\left( x\right) . }[/math] Note that this function can be thought of as the limit as of the potential

[math]\displaystyle{ u\left( x\right) =\left\{ \begin{matrix} 0 & x\notin\left[ -\varepsilon,\varepsilon\right] \\ \frac{u_{0}}{2\varepsilon} & x\in\left[ -\varepsilon,\varepsilon\right] \end{matrix} \right. }[/math]

In this case we need to solve

[math]\displaystyle{ \partial_{x}^{2}w+u_{0}\delta\left( x\right) w=-\lambda x }[/math]

We consider the case of [math]\displaystyle{ \lambda\lt 0 }[/math] and [math]\displaystyle{ \lambda\gt 0 }[/math] separately. For the first case we write [math]\displaystyle{ \lambda=-k^{2} }[/math] and we obtain

[math]\displaystyle{ w\left( x\right) =\left\{ \begin{matrix} ae^{kx}, & x\lt 0\\ be^{kx}, & x\gt 0 \end{matrix} \right. }[/math]

We have two conditions at [math]\displaystyle{ x=0, }[/math] [math]\displaystyle{ w }[/math] must be continuous at [math]\displaystyle{ 0 }[/math] and [math]\displaystyle{ \partial_{x}w\left( 0^{+}\right) -\partial_{x}w\left( 0^{-}\right) +u_{0}w\left( 0\right) =0.\lt math\gt This gives the condition that }[/math]a=b</math> and [math]\displaystyle{ k=u_{0}/2. }[/math] We need to normalise the eigenfunctions so that

[math]\displaystyle{ \int_{-\infty}^{\infty}\left( w\left( x\right) \right) ^{2}dx=1. }[/math]

Therefore

[math]\displaystyle{ 2\int_{0}^{\infty}\left( ae^{-u_{0}x/2}\right) ^{2}dx=1 }[/math]

which means that [math]\displaystyle{ a=\sqrt{u_{0}/2}. }[/math] Therefore, there is only one discrete spectral point which we denote by [math]\displaystyle{ k_{1}=u_{0}/2 }[/math]

[math]\displaystyle{ w_{1}\left( x\right) =\left\{ \begin{matrix} \sqrt{k_{1}}e^{k_{1}x}, & x\lt 0\\ \sqrt{k_{1}}e^{-k_{1}x}, & x\gt 0 \end{matrix} \right. }[/math]

The continuous eigenfunctions correspond to [math]\displaystyle{ \lambda=k^{2}\gt 0 }[/math] are of the form

[math]\displaystyle{ w\left( x\right) =\left\{ \begin{matrix} \mathrm{e}^{-\mathrm{i}kx}+r\mathrm{e}^{\mathrm{i}kx}, & x\lt 0\\ a\mathrm{e}^{-\mathrm{i}kx}, & x\gt 0 \end{matrix} \right. }[/math]

Again we have the conditions that [math]\displaystyle{ w }[/math] must be continuous at [math]\displaystyle{ 0 }[/math] and [math]\displaystyle{ \partial_{x}w\left( 0^{+}\right) -\partial_{x}w\left( 0^{-}\right) +u_{0}w\left( 0\right) =0. }[/math] This gives us

[math]\displaystyle{ \begin{matrix} 1+r & =a\\ -ika+ik-ikr & =-au_{0} \end{matrix} }[/math]

which has solution

[math]\displaystyle{ \begin{matrix} r & =\frac{u_{0}}{2ik-u_{0}}\\ a & =\frac{2ik}{2ik-u_{0}} \end{matrix} }[/math]


Example: Scattering by a Well

The properties of the eigenfunction is prehaps seem most easily through the following example

[math]\displaystyle{ u\left( x\right) =\left\{ \begin{matrix} 0 & x\notin\left[ -\varepsilon,\varepsilon\right] \\ b & x\in\left[ -\varepsilon,\varepsilon\right] \end{matrix} \right. }[/math]

where [math]\displaystyle{ b\gt 0. }[/math]

\paragraph{Case when [math]\displaystyle{ \lambda\gt 0 }[/math]}

If we solve this equation for the case when [math]\displaystyle{ \lambda\lt 0, }[/math] [math]\displaystyle{ \lambda=-k^{2} }[/math] we get

[math]\displaystyle{ w\left( x\right) =\left\{ \begin{matrix} a_{1}e^{kx}, & x\lt -\varepsilon\\ b_{1}\cos\kappa x+b_{2}\sin\kappa x & -\varepsilon\lt x\lt \varepsilon\\ a_{2}e^{-kx} & x\gt \varepsilon \end{matrix} \right. }[/math]

where [math]\displaystyle{ \kappa=\sqrt{b-k^{2}} }[/math] which means that [math]\displaystyle{ 0\leq k\leq\sqrt{b} }[/math] (there is no solution for [math]\displaystyle{ k\gt \sqrt{b}). }[/math] We then match [math]\displaystyle{ w }[/math] and its derivative at [math]\displaystyle{ x=\pm\varepsilon }[/math] to solve for [math]\displaystyle{ a }[/math] and [math]\displaystyle{ b }[/math]. This leads to two system of equation, one for the even ([math]\displaystyle{ a_{1}=a_{2} }[/math] and [math]\displaystyle{ b_{2}=0 }[/math] ) and one for the odd solutions ([math]\displaystyle{ a_{1}=-a_{2} }[/math] and [math]\displaystyle{ b_{1}=0) }[/math]. The solution for the even solutions is

[math]\displaystyle{ \left( \begin{matrix} e^{-k\varepsilon} & -\cos\kappa\varepsilon\\ ke^{-k\varepsilon} & -\kappa\sin\kappa\varepsilon \end{matrix} \right) \left( \begin{matrix} a_{1}\\ b_{1} \end{matrix} \right) =\left( \begin{matrix} 0\\ 0 \end{matrix} \right) }[/math]

This has non trivial solutions when

[math]\displaystyle{ \det\left( \begin{matrix} e^{-k\varepsilon} & -\cos\kappa\varepsilon\\ ke^{-k\varepsilon} & -\kappa\sin\kappa\varepsilon \end{matrix} \right) =0 }[/math]

which gives us the equation

[math]\displaystyle{ -\kappa e^{-k\varepsilon}\sin\kappa\varepsilon+k\cos\kappa\varepsilon e^{-k\varepsilon}=0 }[/math]

or

[math]\displaystyle{ \tan\kappa\varepsilon=\frac{k}{\kappa} }[/math]

We know that [math]\displaystyle{ 0\lt \kappa\lt \sqrt{b} }[/math] and if we plot this we see that we obtain a finite number of solutions.

The solution for the odd solutions is

[math]\displaystyle{ \left( \begin{matrix} e^{-k\varepsilon} & -\sin\kappa\varepsilon\\ ke^{-k\varepsilon} & \cos\kappa\varepsilon \end{matrix} \right) \left( \begin{matrix} a_{1}\\ b_{1} \end{matrix} \right) =\left( \begin{matrix} 0\\ 0 \end{matrix} \right) }[/math]

This can non trivial solutions when

[math]\displaystyle{ \det\left( \begin{matrix} e^{-k\varepsilon} & -\sin\kappa\varepsilon\\ ke^{-k\varepsilon} & \kappa\cos\kappa\varepsilon \end{matrix} \right) =0 }[/math]

which gives us the equation

[math]\displaystyle{ \kappa e^{-k}a\cos\kappa\varepsilon+k\sin\kappa\varepsilon e^{-k}=0 }[/math]

or

[math]\displaystyle{ \tan\kappa=-\frac{\kappa}{k} }[/math]


\paragraph{Case when [math]\displaystyle{ \lambda\gt 0 }[/math]}

When [math]\displaystyle{ \lambda\gt 0 }[/math] we write [math]\displaystyle{ \lambda=k^{2} }[/math] and we obtain solution

[math]\displaystyle{ w\left( x\right) =\left\{ \begin{matrix} \mathrm{e}^{-\mathrm{i}kx}+r\mathrm{e}^{\mathrm{i}kx}, & x\lt -\varepsilon\\ b_{1}\cos\kappa x+b_{2}\sin\kappa x & -\varepsilon\lt x\lt \varepsilon\\ a\mathrm{e}^{-\mathrm{i}kx} & x\gt \varepsilon \end{matrix} \right. }[/math]

where [math]\displaystyle{ \kappa=\sqrt{b+k^{2}}. }[/math] Matching [math]\displaystyle{ w }[/math] and its derivaties at [math]\displaystyle{ x=\pm1 }[/math] we obtain

[math]\displaystyle{ \left( \begin{matrix} -\mathrm{e}^{-\mathrm{i}k\varepsilon} & \cos\kappa\varepsilon & -\sin\kappa\varepsilon & 0\\ ik\mathrm{e}^{-\mathrm{i}k\varepsilon} & \kappa\sin\kappa\varepsilon & \kappa\cos\kappa \varepsilon & 0\\ 0 & \cos\kappa\varepsilon & \sin\kappa\varepsilon & -\mathrm{e}^{-\mathrm{i}k\varepsilon}\\ 0 & -\kappa\sin\kappa\varepsilon & \kappa\cos\kappa\varepsilon & ik\mathrm{e}^{-\mathrm{i}k\varepsilon} \end{matrix} \right) \left( \begin{matrix} r\\ b_{1}\\ b_{2}\\ a \end{matrix} \right) =\left( \begin{matrix} \mathrm{e}^{\mathrm{i}k}\\ ik\mathrm{e}^{-\mathrm{i}k}\\ 0\\ 0 \end{matrix} \right) }[/math]