Bose-Einstein physics question

In summary: But in this case the transition probability is p(i,i+1) = Prob{X(n+1) = i+1 given X(n) = i}. This scheme is reversible as it is easy to see that p(i,i+1)*p(i+1,i) = p(i,i+1)*p(i+1,i) = 1/4.In summary, the given conversation discusses the concept of limiting probabilities in a time-reversible Markov process, where M molecules are distributed among two urns and one molecule is randomly chosen and moved between the urns at each time point. The limiting probabilities represent the probability that a specific number of particles will be in one of the urns in the long run, and can
  • #1
tronter
185
1
Suppose that [tex] M [/tex] molecules are distributed among two urns; and at each time point one of the molecules it chosen at random, removed from its urn, and placed in the other one. So this is a time-reversible Markov process right?

So [tex] P_{i,i+1} = \frac{M-i}{M} [/tex]. What do the limiting probabilities mean in words?

Like [tex] \pi_0 = \left[ 1 + \sum_{j=1}^{M} \frac{(M-j+1) \cdots (M-1)M}{j(j-1) \cdots 1} \right ]^{-1} [/tex]

[tex] = \left [\sum_{j=0}^{M} \binom{M}{j} \right]^{-1} = \left(\frac{1}{2} \right)^{M} [/tex]


and [tex] \pi_i = \binom{M}{i} \left(\frac{1}{2} \right)^{M}, \ i = 0,1, \ldots, M [/tex].

What do these really signify?

Source: Introduction to Probability Models by Sheldon Ross

Thanks
 
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  • #2
Limiting probability of a state-transition probability is a probability value that the state-transition probability converges to, as the number of steps approaches infinity.

See http://en.wikipedia.org/wiki/Markov_chain
 
  • #3
I am not sure though, but the significance appears as-
The stated scheme in the long run is equivalent to distribute M distinguishable particles
in two urns where each particle has probability 1/2 to go into an urn. Pai(i) is the probability that one specified urn will contain i particles. That is, in the stated scheme, whatever be the initial distribution of particles in the urns, in a long run they will be distributed as in case of a Binomial distribution.
 
  • #4
Usually a transition probability is expressed as p(i,j) where i and j are the two states. p(i,j) = Prob{X(n+1) = i given X(n) = j}.
 

1. What is Bose-Einstein physics?

Bose-Einstein physics is a branch of quantum mechanics that describes the behavior of particles at extremely low temperatures. It was developed by Satyendra Nath Bose and Albert Einstein in the 1920s.

2. What is the Bose-Einstein condensate?

The Bose-Einstein condensate (BEC) is a state of matter that occurs at temperatures close to absolute zero. In this state, a large number of particles behave as a single quantum entity, exhibiting macroscopic quantum phenomena.

3. How is Bose-Einstein physics different from classical physics?

Bose-Einstein physics is based on the principles of quantum mechanics, which describe the behavior of particles on a very small scale. In contrast, classical physics is based on the laws of classical mechanics, which describe the behavior of macroscopic objects.

4. What are some applications of Bose-Einstein physics?

Bose-Einstein physics has many practical applications, including superconductivity, superfluidity, and atom lasers. It also plays a crucial role in modern technologies such as transistors, lasers, and magnetic resonance imaging (MRI).

5. What is the Bose-Einstein distribution?

The Bose-Einstein distribution is a statistical distribution that describes the probability of finding a particle in a given energy state at a specific temperature. It is used to calculate the number of particles in a Bose-Einstein condensate and other systems of interacting particles.

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