A one-dimensional "universe" consists of the linear space between x = 0 and x = 1 . There is a single particle in this universe, and its behavior at a particular energy level is governed by a variant of the time-independent Schrodinger equation, expressed in terms of a wave function Ψ N ( x ) .
− d x 2 d 2 Ψ N ( x ) − x Ψ N ( x ) = Ψ N ( x )
The values of Ψ N ( x ) and its first spatial derivative at x = 0 are:
Ψ N ( 0 ) = 1 ( d x d Ψ N ) ( 0 ) = 0
The probability of detecting the particle within the region a ≤ x ≤ b is:
P ( a ≤ x ≤ b ) = ∫ 0 1 ∣ Ψ N ( x ) ∣ 2 d x ∫ a b ∣ Ψ N ( x ) ∣ 2 d x
What is the probability of detecting the particle in the region ( 0 ≤ x ≤ 2 1 ) ?
Note: This problem lends itself well to numerical solution
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The problem can easily be solved numerically with these two lines in Mathematica:
s ( t$_$ ) := NDSolveValue [ { ψ ′ ′ ( x ) + ( x + 1 ) ψ ( x ) = 0 , ψ ( 0 ) = 1 , ψ ′ ( 0 ) = 0 } , { ψ ( t ) } , { x , 0 , 1 } ]
P = NIntegrate [ s ( t ) 2 , { t , 0 , 1 } ] NIntegrate [ s ( t ) 2 , { t , 0 , 2 1 } ]
which gives us P = 0 . 6 9 7 9 0 1 .
Is there a way to do it by hand?
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Good question... I wasn't able to solve that differential eqn by hand but I hope there is a way and I'd like to see an old way solution. Maybe Steven Chase could provide one...
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We can convert the differential equation − ψ ′ ′ ( x ) − x ψ ( x ) = ψ ( x ) ψ ( 0 ) = 1 , ψ ′ ( 0 ) = 0 to the Volterra-type integral equation ψ ( x ) = 1 − ∫ 0 x ( x − u ) ( u + 1 ) ψ ( u ) d u Consider the linear operator X : C [ 0 , 1 ] → C [ 0 , 1 ] defined by ( X f ) ( x ) = − ∫ 0 x ( x − u ) ( u + 1 ) f ( u ) d u We can show that if ∣ f ( x ) ∣ ≤ K x a for all x , then ∣ ( X f ) ( x ) ∣ ≤ ( a + 1 ) ( a + 2 ) 2 K x a + 2 , which implies that ∥ X n f ∥ ∞ ≤ ( 2 n ) ! 2 n ∥ f ∥ ∞ f ∈ C [ 0 , 1 ] , n ∈ N Thus we have a linear operator Y : C [ 0 , 1 ] → C [ 0 , 1 ] defined by Y f = n = 0 ∑ ∞ X n f with ∥ Y f ∥ ∞ ≤ cosh ( 2 ) ∥ f ∥ 2 . This operator has the property that Y f = f + X Y f f ∈ C [ 0 , 1 ] Moreover, if Y N ( f ) = n = 0 ∑ N X n f then ∥ Y N f − Y f ∥ ∞ ≤ ( cosh ( 2 ) − n = 0 ∑ N ( 2 n ) ! 2 n ) ∥ f ∥ ∞ We want the function ψ = Y 1 . Then ∥ ψ − Y 3 1 ∥ ∞ ≤ 4 × 1 0 − 4 , which means that Y 3 1 is a good approximation for ψ . Now ( Y 3 1 ) ( x ) = 1 − 2 1 x 2 − 1 5 4 x 2 5 + 2 4 1 x 4 + 9 4 5 4 6 x 2 9 + 7 5 1 x 5 − 7 2 0 1 x 6 − 2 7 0 2 7 0 6 8 3 x 2 1 3 − 1 9 8 4 5 0 2 9 3 x 7 − 1 4 6 2 5 4 x 2 1 5 and we can use this in place of ψ to approximate the probability as 0 . 6 9 7 9 1 7 , which is accurate to 4 decimal places. Using Y 4 1 would give an even better approximation.