Estimate the partition function by analyzing a graphic

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SUMMARY

The discussion centers on estimating the partition function Z by analyzing graphical representations of Boltzmann factors. Participants clarify that the partition function is derived from the sum of Boltzmann factors, emphasizing the importance of accurately interpreting graphical data. One contributor highlights a method involving direct measurement of y-values from the graph, which provides ratios rather than absolute values, suitable for normalization. The conversation reveals confusion regarding missing terms in the summation and the significance of x-coordinate measurements.

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  • Understanding of partition functions in statistical mechanics
  • Familiarity with Boltzmann factors and their significance
  • Basic knowledge of graphical data interpretation
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  • Study the implications of direct measurement of y-values in statistical analysis
  • Learn about normalization techniques in the context of statistical mechanics
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LCSphysicist
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Homework Statement
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1596796127472.png

I am not sure, but since the partition function Z is just the sum of all Boltzmann Factor
1596796184138.png

We can just add:
1596797180297.png

(some terms don't appear in the image, by the way, the estimative is nice, the result is above ANS)

But i didn't understand what the author did:
1596797273294.png


While i didn't even care about the image of the functions (P(s), what he call by height), his resolution is based on it, not only, he talk nothing about the estimative of the exponents (the values on the abscissa), while my resolution is based on it.

What method he used?? Do you understand?
 

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I was confused at first because the first two terms of your sum are missing. What I see starts at ##+e^{-0.7}##.
The author is doing the same as you, but instead of measuring the x coordinates off the graph and computing each y coordinate, he is measuring the y values directly. This gives him cm rather than the actual Boltzmann factor, but he is only interested in ratios of values since it is going to be normalized to a total of 1 anyway.
 
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