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I was reading the proof of Metropolis algorithm.

The transition probability of going from a state $i$ to a state $j$ is $\pi_{ij}$. If I understand correctly, this is the product $\pi_{i j}=\alpha_{ij}p_{ij}$ where $\alpha_{ij}$ is the probability of selecting the spin that is flipped when going from $i$ to $j$ and $p_{ij}$ is the acceptance probability ($1$ if the new state lowers total energy and $e^{-\beta \Delta E}$ if it doesn't).

What I don't understand is detailed balance. It is said that $p_i \pi_{ij}=p_j \pi_{ji}$. I don't know what $p_{i}$ is. What is the difference with $\pi_{ij}$?

And when I calculate average observables numerically , such as energy, should I take the value of one should I take the mean?

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You can think of the whole thing as a "fluid of systems" and each one of them can be in any of the states $i$ available.

  • $\pi_{ij}$ tells you what is the speed at which a system in state $i$ will go to state $j$

  • $p_i$ tells you how likely it is for a system (in this fluid or ensemble of systems) to be in state $i$ and is proportional to the number of systems in this state. If your system is in contact with a thermostat $p_i \propto \exp(-\beta E_i)$

Now, the total flux that goes from $i$ to $j$ is the velocity to go from $i$ to $j$ for a single system times the number of systems in state $i$; hence $p_i \pi_{ij}$. Conversely, the total flux to go from $j$ to $i$ is $p_j \pi_{ji}$.

  • The detailed balance criterion (which is a sufficient criterion for equilibrium) tells you that the flux from $i$ to $j$ has to be balanced by the flux from $j$ to $i$ so that state $i$ (stationary) population cannot suffer any loss/gain by moving to to state $j$ as it is exactly balanced by systems from $j$ moving to $i$ and vice versa.
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  • $\begingroup$ I think I understand it now. So in a Metropolis simulation the set of generated states should represent the distribution $\exp(-\beta E)$ and to calculate average magnetization I would calculate the mean of the magnetization of every system? $\endgroup$ – jinawee Apr 16 '15 at 5:19
  • $\begingroup$ Yes. So when your Metropolis algorithm has reached equilibrium, each MC step will lead from one "equilibrium" state to another if you want. You can then calculate the average by measuring the "time average" of the magnetization in your MC simulation. Of course the bigger your system the more self averaging the magnetization per spin will be. $\endgroup$ – gatsu Apr 16 '15 at 8:23

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