Fix two typos

docs/src/matrix_free.md

@@ -166,7 +166,7 @@ For a function $u(x)$ discretized on a periodic grid with $n$ points, the FFT of
 \hat{u}_k = \sum_{j=0}^{n-1} u_j e^{-i k x_j},
 ```
 
-where $\hat{u}_k$ represents the Fourier coefficients for the frequency $k$, and $u_j$ is the value of $u$ at the grid point $x_j$ defined as $x_j = \frac{2 \pi j}{L} with period $L$.
+where $\hat{u}_k$ represents the Fourier coefficients for the frequency $k$, and $u_j$ is the value of $u$ at the grid point $x_j$ defined as $x_j = \frac{2 \pi j}{L}$ with period $L$.
 The inverse FFT (IFFT) reconstructs $u$ from its Fourier coefficients:
 
 ```math
@@ -192,7 +192,7 @@ This example consists of solving the 1D Poisson equation on a periodic domain $[
 ```
 
 where $u(x)$ is the unknown solution, and $f(x)$ is the given source term.
-We solve this equation using [FFTW.jl](https://github.com/JuliaMath/FFTW.jl) to compute the matrix-free action of the Laplacian within CG.
+We solve this equation using [FFTW.jl](https://github.com/JuliaMath/FFTW.jl) to compute the matrix-free action of the Laplacian within the conjugate gradient solver.
 
 ```@example fft_poisson
 using FFTW, Krylov, LinearAlgebra