Quasi-Distribution for Non-Physicists

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In summary, the conversation revolves around the topic of quasi-distribution and its relationship to statistics and physics. The individual is seeking an intuitive and non-physical explanation of this concept, and references the Wigner Transform and Quasi-likelihood as related topics. The conversation also touches on the distinction between quasi-likelihood and quasiprobability distribution.
  • #1
consuli
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Hello!

I am a statistician interested in physics.

In the glm procedure in the software R, one can choose, quasi-distribution. I have always wondered what that might be.

Could you introduce the statistical nature of quasi-distribution to me, ideally without mentioning any physics terms like Schrödinger-equation and so on.

Quasi-distribution has a proper statistical defintion, doesn't it? So for the first: The density of quasi-distribution references the probability of what?

Consuli
 
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  • #3
Well, I am looking for a more intuitive and especially less physical but more statistical introduction to this topic.

I am trying"The Wigner Transform", De Gosson, Maurice A, 2017 now. I guess, this isn't easier, but at least more detailed.

Consuli
 
  • #4
consuli said:
In the glm procedure in the software R, one can choose, quasi-distribution. I have always wondered what that might be.
The R documentation I see online uses the term "quasilikelihood", not "quasidistribution". https://www.rdocumentation.org/packages/stats/versions/3.4.3/topics/glm

A "Quasi-likelihood" may be an entirely different thing than a quasiprobability distribution. (The current Wikipedia treats them in different articles.)

Attempting to develop an intuition about either concept would be an interesting project.
 
  • #5
Stephen Tashi said:
The R documentation I see online uses the term "quasilikelihood", not "quasidistribution". https://www.rdocumentation.org/packages/stats/versions/3.4.3/topics/glm A "Quasi-likelihood" may be an entirely different thing than a quasiprobability distribution. (The current Wikipedia treats them in different articles.)

Meanwhile I have figured out, that
Wigner Probability Distribution
and
Quasi Probability Distribution
are the same, thus both related to Schrödinger equation (and the ones I asked for)

but
Quasi-likelihood
is another very different thing (I did NOT asked for).

Consuli
 

Related to Quasi-Distribution for Non-Physicists

1. What is a quasi-distribution?

A quasi-distribution is a mathematical tool used to describe the probability of finding a particle at a specific location in quantum mechanics. It is a function that maps the possible locations of a particle onto a real number line, providing information about the likelihood of finding the particle at each point.

2. How is a quasi-distribution different from a probability distribution?

A quasi-distribution takes into account the uncertainty principle in quantum mechanics, which states that the more precisely we know the position of a particle, the less we know about its momentum, and vice versa. This means that a quasi-distribution provides a more accurate and comprehensive representation of a particle's location than a traditional probability distribution.

3. Can non-physicists understand quasi-distributions?

While the concept of a quasi-distribution may seem complex and intimidating, it is possible for non-physicists to understand the basics. The key is to have a solid understanding of probability and basic calculus. With a little effort and patience, anyone can grasp the fundamentals of quasi-distributions.

4. How are quasi-distributions used in scientific research?

Quasi-distributions play a crucial role in quantum mechanics, particularly in understanding the behavior of particles at a subatomic level. They are used to make predictions and calculations in experiments and help scientists gain a deeper understanding of the fundamental laws of nature.

5. Are there any real-world applications of quasi-distributions?

Yes, while quasi-distributions were originally developed for use in theoretical physics, they have found practical applications in various fields, including quantum computing, cryptography, and signal processing. They are also used in the design and development of nanoscale technologies and devices.

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