What will i use in Quantum maths from linear algebra?

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SUMMARY

The discussion emphasizes the critical role of linear algebra in quantum mathematics, highlighting essential concepts such as matrices, basis sets, matrix transposition, and coordinate systems. Key topics include vector spaces, eigenvalues, complex vector spaces, linear independence, inner products, orthonormal bases, and self-adjoint linear operators. Recommended resources for foundational knowledge are the books by Axler and Friedberg, Insel & Spence, which effectively cover the relationship between linear operators and matrices. A solid understanding of these concepts is necessary for proficiency in quantum mechanics.

PREREQUISITES
  • Linear algebra fundamentals, including matrices and matrix operations
  • Understanding of vector spaces and their properties
  • Knowledge of eigenvalues and eigenvectors
  • Familiarity with inner product spaces and orthonormal bases
NEXT STEPS
  • Study the spectral theorem in linear algebra
  • Learn about self-adjoint linear operators and their properties
  • Explore complex inner product spaces in detail
  • Read Axler's "Linear Algebra Done Right" for a focused approach on linear operators
USEFUL FOR

Students and professionals in mathematics, physics, and engineering, particularly those focusing on quantum mechanics and linear algebra applications.

Ayham
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What is the linear algebra background for Quantum maths? Matrices? Basis's? Matrix trans.? Coordinate Systems?
Please help me, and I am sorry if i posted this in the wrong place...
 
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Ayham said:
Matrices? Basis's? Matrix trans.? Coordinate Systems?
All of them are relevant.
Plus some general properties of vector spaces, different bases, eigenvalues of various operators and so on.
 
Complex vector spaces, linear independence, bases, inner products, inner product spaces, orthonormal bases, linear operators, matrices, matrix multiplication, a theorem about which matrices are invertible, the relationship between linear operators and matrices, the adjoint operation, self-adjoint linear operators, eigenvectors and eigenvalues, and the spectral theorem.

Since the relationship between linear operators and matrices is very important, I recommend that you use a book that presents those things early in the book, like Axler or Friedberg, Insel & Spence. (I have only read the former, but I've heard good things about the latter).

You may not need all of those things for an introductory course. It may be enough to understand complex inner product spaces, orthonormal bases and self-adjoint linear operators. But you will need the rest if you want to get good at QM.
 

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