Disclaimer. I am a PhD level neurobiologist, and like most of my peers a crappy physicist. I went back to better complete my scientific understanding and just on my own am giving physics a crack as a curious adult, and in the process I have gotten hooked on the beauty of physics. I am working it at the level of the first calculus based course. I am especially blown away by the thermo and the quantum stuff. I feel like I can grasp each small piece of these topics, but I must confess the deep understanding, or clarity, is something I am still working towards. As an example, I can study the carnot cycle and understand entropy as it is introduced in the thermodynamic sense. But it is not obvious to me how this relates to the statistical derivation, aside from seeing that they give the same result. The mathematical equivalency doesn't help me figure out why they are related. The question I have deals with the statistical derivation and probabilities. In the maximization of microstates, once again the notion of probability comes into play as being a driver of physical processes. Is this just because the most likely events are the ones that happen, and there is nothing mysterious about it? Otherwise how does the universe "know" which state is the most likely? And also is this probability related to the probabilities in quantum mechanics. I know these are really big, and perhaps silly questions (see disclaimer), but I'd appreciate any feedback.(adsbygoogle = window.adsbygoogle || []).push({});

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# Why the randomness

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