Linear System of Equations

Work in progress. This note is still being written and incomplete.

A linear system of mm equations in nn unknowns x1,x2,…,xnx_1, x_2, \ldots, x_n is a set of equations of the form

a11x1+a12x2+⋯+a1nxn=b1a21x1+a22x2+⋯+a2nxn=b2⋮am1x1+am2x2+⋯+amnxn=bm\begin{aligned} a_{11}x_1 + a_{12}x_2 + \cdots + a_{1n}x_n &= b_1 \\ a_{21}x_1 + a_{22}x_2 + \cdots + a_{2n}x_n &= b_2 \\ \vdots \\ a_{m1}x_1 + a_{m2}x_2 + \cdots + a_{mn}x_n &= b_m \end{aligned}

where aij,bi∈Ra_{ij}, b_i \in \mathbb{R} for 1≤i≤m1 \le i \le m and 1≤j≤n1 \le j \le n.

In matrix form, Ax⃗=b⃗A\vec{x} = \vec{b}, where

A=(a11a12⋯a1na21a22⋯a2n⋮⋮⋱⋮am1am2⋯amn),x⃗=(x1x2⋮xn),b⃗=(b1b2⋮bm)A = \begin{pmatrix} a_{11} & a_{12} & \cdots & a_{1n} \\ a_{21} & a_{22} & \cdots & a_{2n} \\ \vdots & \vdots & \ddots & \vdots \\ a_{m1} & a_{m2} & \cdots & a_{mn} \end{pmatrix}, \quad \vec{x} = \begin{pmatrix} x_1 \\ x_2 \\ \vdots \\ x_n \end{pmatrix}, \quad \vec{b} = \begin{pmatrix} b_1 \\ b_2 \\ \vdots \\ b_m \end{pmatrix}

Here:

  • AA: coefficient matrix
  • [A∣b⃗][A \mid \vec{b}]: augmented matrix

Ax⃗=b⃗A\vec{x} = \vec{b} has exactly one of 3 outcomes:

  • A unique solution.
  • Infinitely many solutions.
  • No solution.

Homogeneity

The system is homogeneous iff b⃗=0⃗\vec{b} = \vec{0}. Otherwise it’s non-homogeneous.

For a system Ax⃗=b⃗A\vec{x} = \vec{b}, the system Ax⃗=0⃗A\vec{x} = \vec{0} is its associated homogeneous system.

Methods

Numerical methods for solving linear systems split into 2 classes:

Direct

Yield the exact solution in a finite number of steps, in the absence of round-off error.

Iterative

Useful for special, very large matrices.

Written by September 28, 2026 1 min read
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