Entropy: Difference between revisions
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From this you can directly calculate Entropy (S): | |||
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Where (The Boltzmann constant) Kb = 1.38 e -23 | |||
===A Computational Model=== | ===A Computational Model=== | ||
Revision as of 17:02, 27 November 2017
Short Description of Topic
The Main Idea
Entropy is an important idea as it is crucial to both the fields of physics and chemistry, but often times it is hard to understand. The traditional definition of entropy is "the degree of disorder or randomness in the system" (Merriam). This definition can however can get lost on some people. A good way to visualize how entropy works is to think of it as a probability distribution with energy. In a sample space which includes two models and 8 quanta, you can configure each quanta to any system you like. All 8 quanta could go to one system, or they can be evenly distributed. If there each systems have equal probabilities of quanta levels, then a whole distribution can be formed around it. In this model, the probability that the energy will reach equilibrium is the highest, while scenarios where all the quanta is located in exclusively one of the two models have the lowest probability. In this way the new definition of entropy becomes "the direct measure of each energy configuration's probability."
A Mathematical Model
Here is a formula to calculate how many ways there are to arrange q quanta among n one-dimensional oscillators:
From this you can directly calculate Entropy (S):
Where (The Boltzmann constant) Kb = 1.38 e -23
A Computational Model
How do we visualize or predict using this topic. Consider embedding some vpython code here Teach hands-on with GlowScript
Examples
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