Probability of electron in a box problem

AI Thread Summary
To calculate the probability of finding an electron in a box of length L = 10 nm using the wavefunction psi = (2/L)^1/2 sin(2*pi*x/L), one must integrate the squared wavefunction over the specified intervals. The normalization of the wavefunction can be assumed to be correct, as it can be verified through integration. The probability of finding the electron between two points is determined by the integral of the wavefunction squared over that range. The discussion also touches on constructing a new orthogonal and normalized function from two given eigenfunctions. The thread concludes with a request for assistance in solving these quantum mechanics problems.
TLeo198
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Homework Statement


Calculate the probability that an electron will be found (a) between x = 0.1 and 0.2 nm, (b) between 4.9 and 5.2 nm in a box of length L = 10 nm when its wavefunction is psi = (2/L)^1/2 sin(2*pi*x/L).

Homework Equations


As far as I know, only the normalization equation, which is A^2 * Integral(psi^2) = 1

The Attempt at a Solution


My problem is actually how to start it. Should I assume that the wavefunction is already normalized, or should I normalize the wavefunction by equating the integral of the squared wavefunction to 1, then solve for A? Sorry if wording of the question is bad. Any help is appreciated.
 
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It looks like the wavefunction is already normalized. Its easy to check.

The fundamental principle of the probabilistic interpretation of quantum mechanics is that the probability of finding a particle between points a and b, is equal to the integral of the wave-function squared over that interval:

<br /> P(a&lt;x&lt;b) = \int_a^b |\Psi(x) |^2 dx<br />
 
I was able to solve it, thanks!
 
Given two normalized but non-orthogonal eigen functions, psi=(1/sqrt(pi))exp(-r) and phi=(1/sqrt(3pi))rexp(-r). Construct a new function PSI which is orthogonal to the first function and is normalized.

Can anyone help me please?


Many many thanks for your kind help.

MSPNS
 
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