Courses Suggestions for Fall math elective courses?

AI Thread Summary
The discussion centers around course selection for a senior physics major with an eye on graduate studies. The student has completed several foundational math courses and is considering two electives from a list that includes Probability and Statistics, Linear Algebra, Point Set Topology, Numerical Analysis, and Discrete Mathematics. Key points raised include the essential nature of Linear Algebra for quantum mechanics, with strong recommendations for its inclusion in the curriculum. Probability and Statistics are noted as fundamental for scientific understanding, while Numerical Analysis is suggested for those leaning towards experimental or computational physics. Point Set Topology and Discrete Mathematics are acknowledged as less critical for most physicists, though they may be beneficial for specific theoretical pursuits. The student's interests in quantum mechanics and potential fields like experimental or computational physics further guide the recommendations, emphasizing the importance of aligning course choices with future academic goals.
deskswirl
Messages
129
Reaction score
50
I am a senior physics major and I have several electives (up to 2) to fill with math courses this Fall. I have previously taken:

Calculus 1-3 (Stewart)
Ordinary Differential Equations (Edwards and Penny)
Partial Differential Equations (Haberman)
Matrix Algebra
Parallel Processing

I am also required to take Mathematical Methods for Physicists and Engineers ( Matthews and Walker) in the Spring.

From the list below please tell me your likes or dislikes of the courses (if you have taken them) and how they contributed to your further studies (I am planning on graduate school in physics). Thanks for your time!

Possible Courses:


Probability and Statistics I - probability axioms and properties; conditional probability and independence; counting techniques; and discrete, continues, univariate, and multivariate random variables

Linear Algebra - theory of real vector spaces and linear transformations. Topics include vector spaces, inner product, norm, distance, subspaces, spanning sets, linear dependence and independence, bases, dimension, linear systems, coordinates, linear transformations, kernel, image, isomorphisms, inverse linear transformations, matrix representations of linear transformations, similarity, direct sums, and canonical forms.

Point Set Topology - open and closed sets, interior, closure, boundary, neighborhoods, continuous functions, separation and subspaces. Additional topics will be selected from compactness, connectedness and continua. (This has a prerequisite of Advanced Analysis but I spoke to the professor and he said not to worry about it. )

Numerical Analysis - Topics will be selected from error analysis, solving algebraic equations, interpolation, numerical differentiation and integration, methods for solving systems of equations, approximation theory, and initial value problems of ordinary differential equations.

Discrete Mathematics - Techniques and tools of reasoning, decision making and combinational problem solving. Topics include sets and logic, combinations, probability, relations and functions, Boolean properties and graph theory.


Note:
I will also be taking:
Intermediate Mechanics (Fowles & Cassidy)
Intermediate EM (Griffiths)
Medical Physics I
and possibly Statistical Thermodynamics (Callen ?)
 
Physics news on Phys.org
If you do not already know linear algebra, you should take the course. It is useful for a lot of physics, most notably quantum mechanics where it is absolutely indispensable.

Point-set topology is a good place to start if you plan on getting into certain types of theory like string theory, but most physicists don't need to think about topology. Same and to a greater extent with discrete math.

Numerical analysis sounds like a good course to take if you plan on getting into experimental or (especially) computational physics. But this isn't what I do, so I'll let someone else make a recommendation here.

Basic probability and statistics can't hurt since these ideas are somewhat fundamental to science.
 
You say you're wanting to go to grad school in physics. Can you be somewhat more specific?? What kind of physics are you considering. The answer will depend on that.
For example, if you're going into quantum mechanics, then you absolutely need to take linear algebra. If you're interested in general relativity, then topology might be helpful. Etc.
 
My recommendation would be 1) Linear algebra and 2) Either probability/statistics or numerical analysis. I think both in 2) are really valuable for physics, but as electroweak pointed out, you should really take linear algebra if you haven't done already.
 
My experience with linear algebra is that I think I know what an operator is and that it corresponds to taking a measurement or change of state (vaguely, I have take a intro Quantum mechanics course last fall) so not very deep at all. So I will take that course.

I am leaning toward something related to quantum mechanics, experimental or computational (molecular/atomic/nuclear or possibly medical physics).

Thanks for the replies!
 
After a year of thought, I decided to adjust my ratio for applying the US/EU(+UK) schools. I mostly focused on the US schools before, but things are getting complex and I found out that Europe is also a good place to study. I found some institutes that have professors with similar interests. But gaining the information is much harder than US schools (like you have to contact professors in advance etc). For your information, I have B.S. in engineering (low GPA: 3.2/4.0) in Asia - one SCI...
I graduated with a BSc in Physics in 2020. Since there were limited opportunities in my country (mostly teaching), I decided to improve my programming skills and began working in IT, first as a software engineer and later as a quality assurance engineer, where I’ve now spent about 3 years. While this career path has provided financial stability, I’ve realized that my excitement and passion aren’t really there, unlike what I felt when studying or doing research in physics. Working in IT...
Hello, I’m an undergraduate student pursuing degrees in both computer science and physics. I was wondering if anyone here has graduated with these degrees and applied to a physics graduate program. I’m curious about how graduate programs evaluated your applications. In addition, if I’m interested in doing research in quantum fields related to materials or computational physics, what kinds of undergraduate research experiences would be most valuable?
Back
Top