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Matrix Representations

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Group RepresentationsEigenvalues and Eigenvectors→→Character TheoryEquivalence of Representations+1 more
matrix-representation change-of-basis coordinate-representation

Core Idea

Once a basis for V is chosen, a representation ρ: G → GL(V) becomes a map G → GL_n(F), assigning an n×n invertible matrix to each group element. Different basis choices yield different matrix representations of the same abstract representation. The passage from abstract linear maps to concrete matrices makes computation possible but introduces basis-dependence that must be carefully managed.

Explainer

An abstract representation ρ: G → GL(V) becomes a matrix representation once you choose an ordered basis {v₁, …, vₙ} for V. Each linear map ρ(g): V → V is then encoded as an n×n matrix whose columns are the coordinates of ρ(g)(v₁), …, ρ(g)(vₙ) in that basis. The homomorphism condition ρ(gh) = ρ(g)ρ(h) translates directly: the matrix product of the matrices for g and h equals the matrix for gh.

The immediate advantage is computability. To check whether a proposed assignment of matrices to group elements is a representation, you verify a finite number of matrix equations. For a group with generators g₁, …, gₖ and relations r₁, …, rₘ, you only need the matrices for the generators and must check that the relations hold at the matrix level. This reduces an infinite verification (all pairs g, h) to a finite one.

The cost is basis-dependence. The same abstract representation can look very different in two bases. For instance, a rotation of ℝ² by angle θ is diagonal in the basis of eigenvectors (with eigenvalues eiθ and e−iθ over ℂ) but has the familiar rotation matrix [[cos θ, −sin θ], [sin θ, cos θ]] in the standard basis. The representation is the same; only the coordinates changed. Two matrix representations related by ρ'(g) = Pρ(g)P⁻¹ for a fixed invertible P and all g ∈ G are called equivalent — they are different coordinate descriptions of the same abstract representation.

This means that properties worth studying are those invariant under conjugation. The determinant det(ρ(g)), the trace tr(ρ(g)), and the eigenvalues of ρ(g) are all basis-independent. The trace, in particular, will become the central object of study when you reach character theory: it distills each representation into a function on the group that captures essentially all the structural information, without any reference to a basis.

Practice Questions 4 questions

Prerequisite Chain

Understanding Zero → The Number Zero → Counting to Five → Counting to 10 → Counting to 20 → Counting a Set of Objects Up to 20 → Cardinality: The Last Number Counted → Matching Numerals to Quantities → Subitizing Small Quantities → Addition Within 10 → Number Bonds to 10 → Addition Within 20 → Doubles and Near Doubles → Doubles Facts Within 10 → Near Doubles Facts Within 20 → Mental Math Strategies for Addition → Mental Math: Adding and Subtracting Tens → Addition Within 100 → Repeated Addition as Multiplication → Multiplication as Equal Groups → Multiplication: Arrays → Basic Multiplication Facts (0s, 1s, 2s, 5s, 10s) → Multiplication Facts Within 100 → Division as Equal Sharing → Division as Grouping (Measurement Division) → Division: Grouping (Repeated Subtraction) Model → Division: Fair Sharing Model → Division as Equal Sharing → Division as Grouping → Basic Division Facts → Division Facts Within 100 → Multiplication and Division Fact Families → Relationship Between Multiplication and Division → Division Facts as Inverse of Multiplication → Remainders and Quotients in Division → Division Word Problems → Multi-Step Word Problems → Solving Multi-Step Word Problems → Multiplication Word Problems → Division Word Problems → Introduction to Long Division → Factors and Multiples → Prime and Composite Numbers → Equivalent Fractions → Relating Fractions and Decimals → Decimal Place Value → Integers and the Number Line → Comparing and Ordering Integers → Absolute Value → Adding Integers → Subtracting Integers → Multiplying Integers → Dividing Integers → Unit Rates → Proportions → Percent Concept → Converting Between Fractions, Decimals, and Percents → Operations with Rational Numbers → Two-Step Equations → Solving Multi-Step Equations → Equations with Variables on Both Sides → Angle Pairs: Complementary, Supplementary, and Vertical → Parallel Lines and Transversals → Corresponding Angles → Alternate Interior Angles → Triangle Angle Sum Theorem → Exterior Angle Theorem → Triangle Inequality Theorem → Similar Triangles: AA Similarity → Similar Triangles: SSS and SAS Similarity → Proportions in Similar Triangles → Right Triangle Trigonometry Introduction → Sine, Cosine, and Tangent Ratios → Trigonometric Ratios Review → Vectors in Two Dimensions → Vector Operations: Addition, Subtraction, and Scalar Multiplication → Dot Product (Inner Product in R^n) → Matrix Multiplication → Determinants of 2×2 and 3×3 Matrices → Invertible Matrices and Matrix Inverses → Systems of Linear Equations and Matrix Form → Gaussian Elimination and Row Reduction → Row Echelon Form and Back Substitution → The Standard Matrix of a Linear Transformation → Eigenvalues and Eigenvectors → Matrix Representations

Longest path: 86 steps · 451 total prerequisite topics

Prerequisites (2)

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