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Tensor Product of Representations

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Reducibility and IrreducibilityTensor Products as Universal Constructions→→Representation Ring
tensor-product clebsch-gordan kronecker-product

Core Idea

Given representations ρ: G → GL(V) and σ: G → GL(W), their tensor product ρ ⊗ σ: G → GL(V ⊗ W) is defined by (ρ ⊗ σ)(g)(v ⊗ w) = ρ(g)v ⊗ σ(g)w. The character of the tensor product is the pointwise product of characters: χ_{ρ⊗σ}(g) = χ_ρ(g)·χ_σ(g). Decomposing tensor products of irreducibles into irreducible summands (the Clebsch-Gordan problem) is fundamental in both mathematics and physics.

Explainer

The tensor product gives a way to combine two representations into a new, larger one. If G acts on V via ρ and on W via σ, the tensor product representation acts on V ⊗ W by the diagonal action: g sends v ⊗ w to ρ(g)v ⊗ σ(g)w, extended linearly to all of V ⊗ W. This is not the same as acting on V and W independently (which would be the direct sum ρ ⊕ σ) — in the tensor product, the same group element g acts simultaneously on both factors.

The dimension of V ⊗ W is dim(V) · dim(W), and in a chosen basis the representing matrix is the Kronecker product of the two individual matrices. The character has a beautiful form: χ_{ρ⊗σ}(g) = χ_ρ(g) · χ_σ(g), a pointwise product. This follows from the fact that the eigenvalues of A ⊗ B are all pairwise products of eigenvalues of A and B, so tr(A ⊗ B) = tr(A) · tr(B). This multiplicativity converts the tensor product decomposition problem into arithmetic with characters.

The Clebsch-Gordan problem asks: given irreducible representations V_i and V_j, decompose V_i ⊗ V_j into irreducibles. The answer is V_i ⊗ V_j ≅ ⊕_k N_{ij}^k V_k, where the multiplicities N_{ij}^k (called Clebsch-Gordan coefficients or Kronecker coefficients for symmetric groups) are computed by N_{ij}^k = ⟨χ_i · χ_j, χ_k⟩. For finite groups over ℂ, this is always a finite computation. For SU(2) in physics, the Clebsch-Gordan decomposition governs angular momentum addition: coupling spin-j₁ and spin-j₂ gives all spins from |j₁−j₂| to j₁+j₂.

Tensor products interact with direct sums distributively: (V₁ ⊕ V₂) ⊗ W ≅ (V₁ ⊗ W) ⊕ (V₂ ⊗ W). This, combined with the tensor product of irreducibles, means the entire tensor product structure is determined by the Clebsch-Gordan coefficients for irreducible pairs. These coefficients encode deep information about the group and are the subject of ongoing research, particularly for symmetric groups (where computing Kronecker coefficients is a major open problem in algebraic combinatorics).

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 → Equivalence of Representations → Reducibility and Irreducibility → Tensor Product of Representations

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