Notation

\[ \newcommand{\R}{\mathbb{R}} \newcommand{\C}{\mathbb{C}} \newcommand{\N}{\mathbb{N}} \newcommand{\E}{\mathbb{E}} \newcommand{\eps}{\varepsilon} \newcommand{\abs}[1]{\left\lvert #1 \right\rvert} \newcommand{\norm}[1]{\left\lVert #1 \right\rVert} \newcommand{\ninf}[1]{\left\lVert #1 \right\rVert_{\infty}} \newcommand{\ntwo}[1]{\left\lVert #1 \right\rVert_{2}} \newcommand{\none}[1]{\left\lVert #1 \right\rVert_{1}} \newcommand{\inner}[2]{\left\langle #1,\, #2 \right\rangle} \newcommand{\bigO}{\mathcal{O}} \newcommand{\dd}{\mathrm{d}} \newcommand{\diff}[2]{\frac{\mathrm{d} #1}{\mathrm{d} #2}} \newcommand{\pdiff}[2]{\frac{\partial #1}{\partial #2}} \newcommand{\spec}{\rho} \newcommand{\cond}{\kappa} \newcommand{\Span}{\operatorname{span}} \newcommand{\rank}{\operatorname{rank}} \newcommand{\tr}{\operatorname{tr}} \newcommand{\diag}{\operatorname{diag}} \newcommand{\argmax}{\operatorname*{arg\,max}} \newcommand{\argmin}{\operatorname*{arg\,min}} \newcommand{\defeq}{:=} \]

This chapter is the master notation table for the whole book. Because Part I (128A) and Part II (128B) come from different sources with different habits, the conventions here are chosen once and applied across both parts; the canonical word for each concept lives in CONTEXT.md. The traps worth watching are flagged with callouts.

General symbols

Symbol Meaning
\(\R,\ \R^n,\ \C\) reals, \(n\)-space, complex numbers
\(\abs{x}\) absolute value / modulus
\(\norm{x},\ \none{x},\ \ntwo{x},\ \ninf{x}\) vector norm; \(1\)-, \(2\)-, \(\infty\)-norm
\(\inner{x}{y}=x^\top y\) inner product
\(\bigO(h^p)\) asymptotic error order as \(h\to 0\)
\(\defeq\) “is defined as”
\(e_k,\ e(h)\) error at step \(k\) / at mesh size \(h\)

Part I: Interpolation & approximation of functions (Ch. 1–2)

Symbol Meaning
\(x_0,\dots,x_n\) interpolation / quadrature nodes (\(n+1\) nodes, degree \(n\))
\(P_n(x),\ p_n(x)\) interpolating polynomial of degree \(\le n\)
\(L_{n,k}(x)\) Lagrange basis polynomial
\(f[x_i,\dots,x_j]\) divided difference
\(S(x),\ S_j(x)\) spline / its \(j\)-th piece
\(h,\ h_j\) step size / subinterval width
\(\phi_k,\ P_k,\ T_k\) orthogonal polynomials; Legendre; Chebyshev
\(w(x)\) quadrature / inner-product weight function

“Order” is overloaded. Order of accuracy \(p\) means error \(\bigO(h^p)\) (quadrature, ODE methods, Ch. 2–3). Order of convergence \(q\) means \(\norm{e_{k+1}}\le C\norm{e_k}^q\) (iterations, Ch. 8). The notes always name which one. See def-8-order-convergence.

Part I: ODE initial-value problems (Ch. 3)

Symbol Meaning
\(y'=f(t,y),\ y(a)=\alpha\) initial-value problem
\(w_j \approx y(t_j)\) numerical approximation at mesh point \(t_j\)
\(h=(b-a)/N,\ t_j=a+jh\) step size, mesh
\(\tau_j(h)\) local truncation error (LTE), see def-3-lte
\(L\) Lipschitz constant of \(f\) in \(y\)

Part I/II: Linear systems and matrices (Ch. 4–5)

Symbol Meaning
\(A\in\R^{n\times n},\ b\in\R^n\) system matrix, right-hand side of \(Ax=b\)
\(A=LU,\ PA=LU\) LU factorization; with partial-pivot permutation \(P\)
\(A=LL^\top,\ A=LDL^\top\) Cholesky / \(LDL^\top\) of an SPD matrix
\(\spec(A)=\rho(A)\) spectral radius \(\max_i\abs{\lambda_i}\) (kept distinct from any norm)
\(\cond(A)=\norm{A}\norm{A^{-1}}\) condition number, see def-4-cond
\(T=M^{-1}N,\ x^{(k+1)}=Tx^{(k)}+c\) iteration matrix and splitting (Jacobi/GS/SOR)
\(r^{(k)}=b-Ax^{(k)}\) residual

\(\rho(A)\) is the spectral radius, never a norm, though \(\rho(A)\le\norm{A}\) for any induced norm, and \(\rho(A)<1\) is the convergence test for stationary iterations (thm-5-jacobi-gs-conv).

Part II: Eigenvalues, SVD, nonlinear (Ch. 7–8)

Symbol Meaning
\(\lambda_i,\ v_i\) eigenvalue, eigenvector
\(A=U\Sigma V^\top\) singular value decomposition; \(\sigma_i\) singular values
\(Q,\ R\) orthonormal factor, upper-triangular factor (Rayleigh–Ritz, subspace iteration)
\(g(x)=x\) fixed-point form; \(g\) a contraction with constant \(k<1\) (thm-8-banach)
\(q\) order of convergence of an iteration (def-8-order-convergence)

The full glossary of words (Reconstruction, source-of-truth per part, etc.) is in CONTEXT.md.