Schools "Catching Up" before graduate school

AI Thread Summary
The discussion centers on seeking study resources for graduate school preparation, particularly for a transition from an unknown state school to Cornell. The individual has a background in electromagnetism (E&M), quantum mechanics, and classical mechanics but lacks a solid foundation in thermodynamics. They express concern about being underprepared compared to peers. Recommendations for textbooks include Kittel for statistical mechanics, Jackson for E&M, and Sakurai for quantum mechanics, with suggestions to also consider Pathria and Huang for statistical mechanics. Participants emphasize the importance of reviewing class notes, exploring various textbooks, and practicing problems from undergraduate courses to build a strong foundation before starting graduate studies. The consensus is that investing time in preparation can significantly ease the transition to the increased difficulty of graduate-level coursework.
Sam I Am
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Can anyone recommend good study resources before entering graduate school? I'm going from an "unknown" state school to Cornell, and I'm worried about being underprepared for courses. I have taken two semesters of E&M and Quantum (Griffiths), one semester of mechanics (Fowles & Cassiday) plus self-studying Lagrangians and Hamiltonians for the pGRE, and had no textbook for thermo so I'll be starting from scratch there.

I am unable to find the textbooks used for the courses specific to Cornell, so if anyone has any ideas there that would be fantastic, otherwise just generic study resources (preferably cheap, since I'll be buying books for the fall also). I'll also be studying Hassani's "math methods" book for the fall since I can get it for free.

Also, if anyone has generic tips for success in my endeavors, please pass them on!

Cheers,
Sam
 
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Do want to get a jump start on your Fall courses? If so, what classes will you be taking?

Or are you more concerned about passing your qualifying exams? What exams will you be taking?
 
DrSteve said:
Do want to get a jump start on your Fall courses? If so, what classes will you be taking?

Or are you more concerned about passing your qualifying exams? What exams will you be taking?

I won't be taking the qualifying exams until my second year (I think), though I guess incoming students get a free crack at it in the fall of their first year. I'm more worried about fall courses, though not so much a "jump start" as "catching up to everyone else".

I don't know specifically what courses I'll be taking, but I'm sure thermodynamics/stat mech, E&M (which I'm not so worried about), and quantum will be in there.
 
Sam I Am said:
I won't be taking the qualifying exams until my second year (I think), though I guess incoming students get a free crack at it in the fall of their first year. I'm more worried about fall courses, though not so much a "jump start" as "catching up to everyone else".

I don't know specifically what courses I'll be taking, but I'm sure thermodynamics/stat mech, E&M (which I'm not so worried about), and quantum will be in there.

Then

Stat Mech - Kittel
E&M - Jackson
QM - Cohen and Tannoujdi or Suzuki
 
I would recommend Pathria, Kardar, and Huang for stat mech. If I remember correctly, Kittel is actually an undergrad book.

I would highly recommend Sakurai for QM. That is one of my favorite physics books. It does assume a pretty high level background,but is a great book. The second chapter is especially elegant.

I think there is a pretty high probability Cornell might use Sakurai and Pathria, they are pretty standard.
 
Excellent, I will see if I can find a cheap used copy of those.

Thanks!
 
You're being really smart, Sam I Am. The summer before graduate school I spent my evenings (I had a summer job) going over class notes, reading different textbooks, and re-doing tests and homework assignments from key undergraduate courses. It was IMMENSELY helpful when I started graduate school which, for me, was a step-change in difficulty compared to undergrad.

In particular, I read all the textbooks my undergrad library had in my particular specialty. I found that taking the time to learn the slightly different pedagogical approaches and the different perspectives they gave in each of the books was incredibly helpful in building up my own intuition. It was a serious time investment (and I kept my partying to a minimum) but it paid off handsomely.
 
Cornell follows Sakurai/Gottfried and Yan for QM and Stat Mech tends to be all over the place so I'd say go with Pathria to be safe.
 
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