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Linear Systems: No and Infinite Solutions

Jan 22, 2025

Lecture 21: Introductory Linear Algebra

Solving Linear Systems with No Solution or Infinitely Many Solutions

Introduction

  • Addressing how to solve linear systems with no solutions or infinitely many solutions.
  • Previous examples had unique solutions.

Solving a Linear System with No Solutions

  • Example Approach:
    • Start by throwing the system into an augmented matrix.
    • Perform row operations to reach row echelon form.
    • Zero out entries below leading entries using operations like row 2 minus double row 1, etc.
  • Key Signs of No Solution:
    • If row reduction results in a row where all coefficients are zero but the right-hand side is non-zero (e.g., 0x + 0y + 0z = -42/5), the system has no solution.
    • This inconsistency (0 = non-zero) indicates no solution.

Solving a Linear System with Infinitely Many Solutions

  • Challenges:
    • Not only solving but describing the solutions since they are infinite.
  • Example Approach:
    • Use reduced row echelon form to read off solutions.
    • Focus on leading entries and corresponding columns (variables).
    • Solve for leading variables in terms of free variables.

Terms and Definitions

  • Leading Variables: Variables in columns with leading entries.
  • Free Variables: Variables in columns without leading entries.
    • Free variables are unrestricted, leading to infinite solutions.

Describing Solutions

  • Example:
    • Given an augmented matrix already in reduced row echelon form, rearrange to express leading variables in terms of free variables.
    • Example: v = 3 + 2w - 2z, x = 7 + 3z, y = 4 - z.
    • All solutions can be described in terms of free variables w and z.
    • Every solution vector can be expressed with free variables deciding values.

Example with Calculation to Find Reduced Row Echelon Form

  • Process:
    • Convert system to augmented matrix and perform row operations to reduce.
    • Once in reduced row echelon form, identify and rearrange equations:
      • Leading variables (e.g., w, y) expressed in terms of free variables (e.g., x, z).
    • Describe the solution vector in terms of free variables.

Dimensionality of Solution Set

  • Number of free variables corresponds to solution set dimensionality.
  • Example: Two free variables imply a 2-dimensional solution set, forming a plane in 4-dimensional space.

Conclusion

  • Understanding how to solve and describe solutions for systems with no solutions or infinitely many solutions.
  • Completion of week 5, full understanding of solving linear systems.