Systems of EquationsTopic #13 of 30

Systems of Linear Equations

Representing systems as matrices, Ax = b form, and geometric interpretation.

Overview

A system of linear equations is a collection of linear equations involving the same set of variables. Linear algebra provides powerful methods for understanding and solving these systems.

Standard Form

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}$$ ## Matrix Form The system can be written as: $$A\mathbf{x} = \mathbf{b}$$ where: $$A = \begin{bmatrix} 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{bmatrix}, \quad \mathbf{x} = \begin{bmatrix} x_1 \\ x_2 \\ \vdots \\ x_n \end{bmatrix}, \quad \mathbf{b} = \begin{bmatrix} b_1 \\ b_2 \\ \vdots \\ b_m \end{bmatrix}$$ ## Augmented Matrix $$[A \mid \mathbf{b}] = \left[\begin{array}{cccc|c} a_{11} & a_{12} & \cdots & a_{1n} & b_1 \\ a_{21} & a_{22} & \cdots & a_{2n} & b_2 \\ \vdots & \vdots & \ddots & \vdots & \vdots \\ a_{m1} & a_{m2} & \cdots & a_{mn} & b_m \end{array}\right]$$ ## Geometric Interpretation ### In 2D (Two Variables) Each equation represents a line. Solutions are intersection points. ### In 3D (Three Variables) Each equation represents a plane. Solutions are intersection points. ## Example $$2x + y = 5$$ $$x - y = 1$$ Matrix form: $$\begin{bmatrix} 2 & 1 \\ 1 & -1 \end{bmatrix}\begin{bmatrix} x \\ y \end{bmatrix} = \begin{bmatrix} 5 \\ 1 \end{bmatrix}$$ Augmented matrix: $$\left[\begin{array}{cc|c} 2 & 1 & 5 \\ 1 & -1 & 1 \end{array}\right]$$ ## Homogeneous Systems A system $A\mathbf{x} = \mathbf{0}$ (where $\mathbf{b} = \mathbf{0}$) is homogeneous. ### Properties - Always has the trivial solution $\mathbf{x} = \mathbf{0}$ - May have infinitely many solutions - Solution set is a subspace (the null space of $A$) ### When Non-Trivial Solutions Exist A homogeneous system $A\mathbf{x} = \mathbf{0}$ has non-trivial solutions if: - Number of variables > number of equations - $\det(A) = 0$ (for square systems) - $A$ is not full column rank ## Consistent vs Inconsistent | Type | Meaning | Condition | |------|---------|-----------| | Consistent | At least one solution exists | $\text{rank}(A) = \text{rank}([A \mid \mathbf{b}])$ | | Inconsistent | No solution exists | $\text{rank}(A) < \text{rank}([A \mid \mathbf{b}])$ | ## Examples ### Example 1: Consistent System $$x + y = 3$$ $$x - y = 1$$ Solution: $x = 2$, $y = 1$ (intersection point) ### Example 2: Inconsistent System $$x + y = 3$$ $$x + y = 5$$ No solution (parallel lines) ### Example 3: Infinitely Many Solutions $$x + y = 3$$ $$2x + 2y = 6$$ Solution: $x = t$, $y = 3 - t$ for any $t$ (same line) ## Solution Representation For consistent systems, the general solution is: $$\mathbf{x} = \mathbf{x}_p + \mathbf{x}_h$$ where: - $\mathbf{x}_p$ is a particular solution (any solution to $A\mathbf{x} = \mathbf{b}$) - $\mathbf{x}_h$ is the general solution to $A\mathbf{x} = \mathbf{0}$ (homogeneous part)