Courses Thermodynamics/Statistical Mechanics and Discrete questions

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The discussion centers on a student transitioning from chemistry to physics and expressing concerns about upcoming courses, specifically statistical mechanics, discrete math, mechanics, and laboratory physics. They seek preparatory resources and clarity on course content, particularly the mathematical requirements for statistical mechanics and the nature of discrete math. The student is unsure about the focus of the mechanics course, whether it will cover Newtonian or Hamiltonian mechanics, and is looking for guidance on laboratory physics expectations. Additionally, they request tips for success in the physics field beyond standard classroom advice. Overall, the conversation highlights the need for resources and understanding of the new curriculum in physics.
rmiller70015
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I just switched my major from chemistry to physics because I wasn't happy with the amount of math I was encountering as a physical chemist. So now I am going into a new major program and I am afraid of some of the courses I am about to take. Next semester I will be taking a math methods course, which I'm not too concerned about. But I will also be taking a mechanics course, statistical mechanics/thermodynamics, discrete math, and lab physics. I have no idea what these entail and I have some questions and requests about these courses. I have taken organic chemistry, instrumental and chemical analysis, and perhaps most importantly for my new path differential equations.

1) Statistical Mechanics and Thermodynamics:
  • Are there any good preparatory resources for this class that anyone knows of, bonus points if they're free or super cheap?
  • Having taken all the calculuses...calculii?? ...and diff eq should I be ready for this course as far as the math is concerned? Also, I haven't taken probability theory yet, but I am assuming the modeling class will cover this type of thing; and analytical chemistry does cover some probability theory such as standard deviation, median, mean, and error treatment methods as well as several of the various statistical tests.
  • What should I expect from this course, what are some typical real world applications of this type of physics? Would it be something like all the molecules or atoms in a system should behave in some way and we can assume that overall the system should behave in some other way based on what we've sampled plus some statistical analysis?
2) Discrete Math:
  • I have no idea what this is exactly. I hear it's about discontinuities and involves proofs, but other than that I'm not sure what discrete math is used for.
  • Again, any preparatory resources would be awesome.
  • What kinds of applications are there to discrete math?
3) Mechanics:
  • The course catalog doesn't really say much about this course and I am wondering is this Newtonian mechanics or will it be Hamiltonian, or both?
  • Same as the other two, are there any good books that I can get for this subject before I actually take it.
4)Laboratory Physics:
  • In chemistry it's pretty clear what the labs are for and why, but again the course catalog isn't too forthcoming in what I should expect for this class. There is a lecture portion and a lab portion, but I'm guessing this is sort of like analytical chemistry where you learn to use the tools of the trade.
Also, any tips on how to be a successful student in the physics field outside of go to class, pay attention, and the like would be greatly appreciated.
 
rmiller70015 said:
2) Discrete Math:
  • I have no idea what this is exactly. I hear it's about discontinuities and involves proofs, but other than that I'm not sure what discrete math is used for.
  • Again, any preparatory resources would be awesome.
  • What kinds of applications are there to discrete math?
Discrete math courses vary wildly from university to university. They seem to be survey courses. For instance, I've taken two discrete math courses. The first one was many years ago when I was in school. That class covered set theory, logic, and proofs. The other one, taken many years later, covered combinatorics, number theory, and graph theory. In the course you take, your professor may cover several subfields, or dive more deeply into just one or two.

As for applications, nearly all of computer science has its roots in discrete math.
 
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