Do Quantum Mechanics PDFs Converge?

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In summary, the conversation discusses the convergence of probability density functions (PDFs) in quantum mechanics (QM) random processes. The double-slit experiment using low-intensity monochromatic photons shows that the interference pattern observed over time converges to the PDF associated with the wave function. The conversation also mentions different types of convergence in probability theory, such as convergence in distribution and convergence in probability. The question is posed about whether there is literature on the types of convergence in QM random processes. However, it is noted that the question is more mathematical and empirical rather than physical, and that there is extensive literature on the mathematical aspects of QM.
  • #1
LarryS
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Consider the double-slit experiment using a low-intensity source of monochromatic photons: If the intensity is low enough, one can observe the photons, one at a time, slowly developing an interference pattern on a photographic plate.

The interference pattern, over time, resembles more and more the continuous probability density function associated with the wave function, i.e. it “converges” to the PDF.

I have just started reading about the different types of convergence in probability theory:

Convergence in Distribution
Convergence in Probability
Almost Sure Convergence
Etc.

Has anybody found QM literature researching the types of convergence that occur in QM random processes?

Thanks in advance.
 
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  • #2
Forget the QM part, it isn't actually important. Your question is more a standard one from sampling theory - if I draw n samples from a distribution, how do the properties of the sample converge on the distribution as n gets very big. The convergence phrases you refer to in your post are more mathematical, different from this empirical effect where a histogram of a large number of samples from a distribution converges on that distribution.
 
  • #3
peteratcam said:
Forget the QM part, it isn't actually important. Your question is more a standard one from sampling theory - if I draw n samples from a distribution, how do the properties of the sample converge on the distribution as n gets very big. The convergence phrases you refer to in your post are more mathematical, different from this empirical effect where a histogram of a large number of samples from a distribution converges on that distribution.

I realize my question is more mathematical than physical/empirical. But much has been written about the purely mathematical aspects of QM (Von Neumann, etc.).

So, has anyone written about the very specific type of PDFs that are produced by quantum processes?
 

1. What is QM PDF?

QM PDF stands for Quantum Mechanical Probability Density Function. It is a mathematical function used in quantum mechanics to describe the probability of finding a particle at a particular position in space.

2. How do QM PDFs converge?

QM PDFs converge through the use of wave functions, which are solutions to the Schrödinger equation in quantum mechanics. These wave functions are then squared to obtain the probability density function.

3. What is the significance of QM PDFs converging?

The convergence of QM PDFs is significant because it allows us to accurately predict the behavior and properties of quantum systems. This is essential in fields such as materials science, chemistry, and quantum computing.

4. What factors affect the convergence of QM PDFs?

There are several factors that can affect the convergence of QM PDFs, including the complexity of the system, the accuracy of the wave function, and the computational resources used. Inaccuracies in any of these factors can lead to a slower or even failed convergence.

5. How can we improve the convergence of QM PDFs?

To improve the convergence of QM PDFs, we can use more advanced wave function models, increase the accuracy of the computational methods, and use more powerful computing resources. Additionally, careful analysis and optimization of the system being studied can also help improve the convergence.

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