State Space and Probability Theory

In summary, mathematical probability theory defines a "probability space" and does not define a "state space". Classical probability is an application of mathematical probability theory to "state space" as defined in physics - presumably as defined in "classical" physics. The difference is the pure states are not definite - there is no way to tell what a quantum pure state is by observation.
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Hi All

This is in relation to the folllowing paper:
https://arxiv.org/pdf/1402.6562.pdf

See section 3 on examples where standard probability theory is discussed. Is it valid? To me its rather obvious but I had had a retired professor of probability say probability theory doesn't have a state space. This has me totality flummoxed. Is he right and if so what am I missing?

Thanks
Bill
 
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Mathematical probability theory defines a "probability space" and does not define a "state space".

What the article calls "Classical probability" is not an exposition of mathematical probability theory. Instead it is an application of mathematical probability theory to "state space" as defined in physics - presumably as defined in "classical" physics.
 
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Stephen Tashi said:
Instead it is an application of mathematical probability theory to "state space" as defined in physics - presumably as defined in "classical" physics.

Yes - agreed. But its a perfectly legit space

Its easy to define. If your outcomes are definite you simply define each as a vector with 1 in the outcome. They are by definition the pure states. Then you create all the convex sums of them. That forms a space. The sums are by definition called mixed states and of course the 'weight' in that sum can easily be interpreted as the probability of that pure state. Or have I made a mistake?

Its purpose is to bring out the difference to QM. There states are positive operators of trace 1. Pure states are defined to be of the form |u><u|. You can also form mixed states from them with the same interpretation. The difference is the pure states are not definite - there is no way to tell what a quantum pure state is by observation.

This is all part of a class of theories based on probability but generalize it in all sorts of ways

Thanks
Bill
 
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1. What is state space in probability theory?

The state space in probability theory refers to the set of all possible outcomes or states that a system or experiment can have. It is denoted by the symbol Ω and is used to analyze the probability of different events occurring within the system or experiment.

2. What is the difference between discrete and continuous state space?

In discrete state space, the possible outcomes or states are countable and can be listed or enumerated. On the other hand, in continuous state space, the possible outcomes or states are uncountable and can only be described using intervals or ranges.

3. How is probability represented in state space?

In state space, probability is represented by assigning a probability value to each possible outcome or state. This can be done using different methods such as assigning equal probabilities, using frequency or historical data, or using mathematical models.

4. What is the relationship between state space and events in probability theory?

In probability theory, events are subsets of the state space. They represent specific outcomes or combinations of outcomes within the system or experiment. The probability of an event can be calculated by summing the probabilities of the individual outcomes or states within that event.

5. How is state space used in Bayesian probability?

In Bayesian probability, the state space is used to represent the possible values of a parameter or variable of interest. By assigning prior probabilities to different values in the state space, and updating them based on new evidence, the posterior probability of the parameter or variable can be calculated.

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