Difference between revisions of "Properties of the Linear Schrodinger Equation"
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+u_0 w\left( 0\right) =0.</math> This final condition is obtained by integrating `across' zero as follows | +u_0 w\left( 0\right) =0.</math> This final condition is obtained by integrating `across' zero as follows | ||
<center><math>\begin{align} | <center><math>\begin{align} | ||
− | \int_{0^{-}}^{0^{+}} \left(\partial_x^2 w +\delta(x) w + \lambda w \right) \ \mathrm{d}x = 0. | + | \int_{0^{-}}^{0^{+}} \left(\partial_x^2 w +u_0\delta(x) w + \lambda w \right) \ \mathrm{d}x = 0. |
\end{align} | \end{align} | ||
</math></center> | </math></center> | ||
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\mathrm{e}^{-\mathrm{i}kx}+r\mathrm{e}^{\mathrm{i}kx}, & x<0\\ | \mathrm{e}^{-\mathrm{i}kx}+r\mathrm{e}^{\mathrm{i}kx}, & x<0\\ | ||
− | + | t\mathrm{e}^{-\mathrm{i}kx}, & x>0 | |
\end{matrix} | \end{matrix} | ||
\right. | \right. | ||
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+u_{0}w\left( 0\right) =0.</math> This gives us | +u_{0}w\left( 0\right) =0.</math> This gives us | ||
<center><math>\begin{matrix} | <center><math>\begin{matrix} | ||
− | 1+r & = | + | 1+r & =t\\ |
− | - | + | -ikt+ik-ikr & =-tu_{0} |
\end{matrix}</math></center> | \end{matrix}</math></center> | ||
which has solution | which has solution | ||
<center><math>\begin{matrix} | <center><math>\begin{matrix} | ||
r & =\frac{u_{0}}{2ik-u_{0}}\\ | r & =\frac{u_{0}}{2ik-u_{0}}\\ | ||
− | + | t & =\frac{2ik}{2ik-u_{0}} | |
\end{matrix}</math></center> | \end{matrix}</math></center> | ||
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\begin{matrix} | \begin{matrix} | ||
a_{1}e^{kx}, & x<-\varsigma,\\ | a_{1}e^{kx}, & x<-\varsigma,\\ | ||
− | b_{1}\cos\kappa x+b_{2}\sin\kappa x, & -\varsigma<x<\varsigma,\\ | + | b_{1}\cos\kappa x+b_{2}\sin\kappa x, & -\varsigma< x <\varsigma,\\ |
a_{2}e^{-kx}, & x>\varsigma, | a_{2}e^{-kx}, & x>\varsigma, | ||
\end{matrix} | \end{matrix} | ||
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\begin{matrix} | \begin{matrix} | ||
a_{1}e^{kx}, & x<-\varsigma,\\ | a_{1}e^{kx}, & x<-\varsigma,\\ | ||
− | b_{1}\cos\kappa, | + | b_{1}\cos\kappa x, & -\varsigma< x <\varsigma,\\ |
a_{1}e^{-kx}, & x>\varsigma, | a_{1}e^{-kx}, & x>\varsigma, | ||
\end{matrix} | \end{matrix} | ||
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w\left( x\right) =\left\{ | w\left( x\right) =\left\{ | ||
\begin{matrix} | \begin{matrix} | ||
− | a_{1}e^{kx}, & x<-\varsigma,\\ | + | a_{1}e^{kx}, & x <-\varsigma,\\ |
− | b_{2}\sin\kappa x, & -\varsigma<x<\varsigma,\\ | + | b_{2}\sin\kappa x, & -\varsigma< x <\varsigma,\\ |
− | -a_{1}e^{-kx} & x>\varsigma, | + | -a_{1}e^{-kx} & x > \varsigma, |
\end{matrix} | \end{matrix} | ||
\right. | \right. | ||
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\begin{matrix} | \begin{matrix} | ||
− | \mathrm{e}^{-\mathrm{i}kx}+r\mathrm{e}^{\mathrm{i}kx}, & x<-\varsigma\\ | + | \mathrm{e}^{-\mathrm{i}kx}+r\mathrm{e}^{\mathrm{i}kx}, & x <-\varsigma\\ |
− | b_{1}\cos\kappa x+b_{2}\sin\kappa x & -\varsigma<x<\varsigma\\ | + | b_{1}\cos\kappa x+b_{2}\sin\kappa x & -\varsigma< x <\varsigma\\ |
− | + | t\mathrm{e}^{-\mathrm{i}kx} & x>\varsigma | |
\end{matrix} | \end{matrix} | ||
\right. | \right. | ||
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b_{1}\\ | b_{1}\\ | ||
b_{2}\\ | b_{2}\\ | ||
− | + | t | |
\end{matrix} | \end{matrix} | ||
\right) =\left( | \right) =\left( | ||
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\right) | \right) | ||
</math></center> | </math></center> | ||
+ | |||
+ | == Lecture Videos == | ||
+ | |||
+ | === Part 1 === | ||
+ | |||
+ | {{#ev:youtube|anAThvCcpNw}} | ||
+ | |||
+ | === Part 2 === | ||
+ | |||
+ | {{#ev:youtube|SDPIx42VjLQ}} | ||
+ | |||
+ | === Part 3 === | ||
+ | |||
+ | {{#ev:youtube|OUmjeLZWr3M}} | ||
+ | |||
+ | === Part 4 === | ||
+ | |||
+ | {{#ev:youtube|hIfcO3a8_XU}} | ||
+ | |||
+ | === Part 5 === | ||
+ | |||
+ | {{#ev:youtube|z13lKSTficA}} | ||
+ | |||
+ | === Part 6 === | ||
+ | |||
+ | {{#ev:youtube|2XlQpEscxE4}} | ||
+ | |||
+ | === Part 7 === | ||
+ | |||
+ | {{#ev:youtube|iMMQ4NUdXNc}} | ||
+ | |||
+ | === Part 8 === | ||
+ | |||
+ | {{#ev:youtube|0F_dINNxMlw}} |
Latest revision as of 01:03, 24 September 2020
Nonlinear PDE's Course | |
---|---|
Current Topic | Properties of the Linear Schrodinger Equation |
Next Topic | Connection betwen KdV and the Schrodinger Equation |
Previous Topic | Introduction to the Inverse Scattering Transform |
The linear Schrodinger equation
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 1: [math]\displaystyle{ \delta }[/math] function potential
We consider here the case when [math]\displaystyle{ u\left( x,0\right) = u_0 \delta\left( x\right) . }[/math] Note that this function can be thought of as the limit as of the potential
In this case we need to solve
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
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. }[/math] This final condition is obtained by integrating `across' zero as follows
This gives the condition that [math]\displaystyle{ a=b }[/math] and [math]\displaystyle{ k=u_{0}/2. }[/math] We need to normalise the eigenfunctions so that
Therefore
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]
The continuous eigenfunctions correspond to [math]\displaystyle{ \lambda=k^{2}\gt 0 }[/math] are of the form
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
which has solution
Example 2: Hat Function Potential
The properties of the eigenfunction is perhaps seem most easily through the following example
where [math]\displaystyle{ b\gt 0. }[/math]
Case when [math]\displaystyle{ \lambda\lt 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
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\varsigma }[/math] to solve for [math]\displaystyle{ a }[/math] and [math]\displaystyle{ b }[/math]. This leads to two system of equations, 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
If we impose the condition that the function and its derivative are continuous at [math]\displaystyle{ x=\pm\varsigma }[/math] we obtain the following equation
This has non trivial solutions when
which gives us the equation
or
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
and again imposing the condition that the solution and its derivative is continuous at [math]\displaystyle{ x=\pm\varsigma }[/math] gives
This can non trivial solutions when
which gives us the equation
or
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
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