Linear algebra

Vectors, matrices, eigenvalues, inner products, the spectral theorem.

Linear algebra is the language of transformations: things that combine inputs additively and respect scaling. Once a phenomenon is linear — and an astonishing fraction of physics is linear, at least near equilibrium — its full structure can be captured in finite-dimensional terms by vectors and matrices, or in infinite-dimensional terms by operators on function spaces.

This chapter is the working refresher. It is here because the rest of the bookshelf invokes linear-algebra concepts repeatedly — eigenvalues of a Jacobian in the ODE phase plane, eigenfunctions of the wave operator in PDEs, modes of a cavity in Helmholtz, energy eigenstates in Schrödinger, the orthogonal basis underlying every Fourier expansion — and assumes the reader has the tools in hand. We collect those tools here.

The chapter is built as a gentle ramp:

If you have not done linear algebra in a while, this chapter is the audience it was written for. Each lesson reintroduces its idea from the picture down before any algebra is required.