Which is More Mathematical: The Princeton Companion or Mathematics for Physics?

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SUMMARY

The discussion compares "The Princeton Companion to Applied Mathematics" and "Mathematics for Physics" by Michael Stone and Paul Goldbart, determining that "Mathematics for Physics" is more mathematically rigorous and streamlined for learning essential concepts in physics. While "The Princeton Companion" serves as a comprehensive reference covering specialized topics such as asymptotics and mathematical modeling, it lacks the focused pedagogical approach found in "Mathematics for Physics." Ultimately, the latter is deemed superior for students seeking a solid mathematical foundation relevant to physics.

PREREQUISITES
  • Understanding of applied mathematics concepts
  • Familiarity with mathematical modeling techniques
  • Knowledge of asymptotic analysis
  • Basic principles of physics relevant to mathematics
NEXT STEPS
  • Explore advanced topics in "Mathematics for Physics" by Michael Stone and Paul Goldbart
  • Study asymptotic analysis techniques in applied mathematics
  • Research mathematical modeling applications in physics
  • Review supplementary mathematics courses for physics undergraduates
USEFUL FOR

Students and educators in applied mathematics, physicists seeking a deeper understanding of mathematical principles, and anyone interested in comparing mathematical rigor in educational texts.

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Which is more mathematical among The Princeton Companion to Applied Mathematics and Mathematics for Physics by Michael Stone and Paul Goldbart?
Both of them are applied mathematics books. What are the main differences between them? Which is more mathematical i.e. mathematically advanced, mathematically rigorous?
 
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Mathematics for Physics is more streamlined in its presentation, and covers the most important mathematics for physics that might not be covered in the mathematics classes required for a typical undergraduate degree. The Princeton Companion is a nice reference, but it... sprawls a bit. It does cover quite a few interesting specialized topics like asymptotics, mathematical modeling, etc. , but I don't feel that the Princeton Guide is as good for learning from.
 
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