Expectation Value vs Probability Density

In summary, the difference between expectation value and probability density is that expectation value is the average value of all probabilities, while probability density is the probability of the particle being in a particular spot. To calculate the probability density for an observable other than position, the general rule is the Born rule. This means that for energy, you can expand the state in terms of energy eigenfunctions and the probability will be the square of the coefficient for the corresponding eigenfunction. In quantum mechanics, only expectation values can be predicted, but distributions can be reconstructed from these values.
  • #1
jaydnul
558
15
I know the difference between the expectation value and probability density, but how do you calculate the probability density of an observable other than position? For position, the probability of the particle being in a particular spot is given by [itex]|\Psi|^2[/itex], which is the probability density, and the average of all those probabilities is given by [itex]\int \Psi^*x\Psi[/itex] correct?

Now for all the other observables (momentum, energy, etc...) the expectation values are straight foward, but how do I calculate the probability densities?

Thanks
 
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  • #3
So if i were given [itex]\Psi(x)[/itex], to find the momentum probability density I would convert to momentum space using a Fourier transform? What about the energy probability density?
 
  • #4
Let's restrict to projective measurements for simplicity. The potential outcome is represented by a certain state. The probability of the outcome is the square of the projection of the state being measured onto the state representing the potential outcome. This rule is called the Born rule.

For energy, you can expand the state in terms of energy eigenfunctions. Then the probability of a given energy will be the square of the coefficient for the corresponding eigenfunction.

You will often hear the only expectation values can be predicted in quantum mechanics. Then you will ask why only averages, and not the distributions themselves? For most distributions, one can reconstruct them from the expectation values of their moments or cumulants. This ability to reconstruct distributions from expectation values is why it is often said that only expectation values can be predicted in quantum mechanics.
 
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  • #5
And a probability is an expectation value of 0 and 1 (this is the way you measure them)
 

FAQ: Expectation Value vs Probability Density

What is the difference between expectation value and probability density?

Expectation value is a measure of the average value of a quantity in a given system, while probability density is a measure of the likelihood of finding a particular value of that quantity in the system.

How are expectation value and probability density related?

Expectation value is calculated by multiplying the probability density of each possible value by that value, and then summing all of these products. In other words, the expectation value is a weighted average of the probability density function.

Can expectation value and probability density be used for continuous variables?

Yes, both expectation value and probability density can be used for continuous variables. In this case, the probability density is represented by a probability density function (PDF) and the expectation value is calculated by integrating the product of the PDF and the variable over the entire range of values.

How do expectation value and probability density relate to quantum mechanics?

In quantum mechanics, expectation value represents the average value of a physical quantity that can be measured, while probability density describes the likelihood of finding a particle in a certain location or state. These concepts are fundamental to understanding the behavior of particles at the quantum level.

Can expectation value and probability density be used to make predictions?

Yes, both expectation value and probability density can be used to make predictions about the behavior of a system. For example, knowing the expectation value of an electron's position in an atom can help predict its behavior and interactions with other particles. However, these predictions are probabilistic in nature, as they are based on the likelihood of a particular outcome.

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