A topic in the Open Knowledge Graph β€” a free, open map of 15,290 topics and the order to learn them in.

Representations of SLβ‚‚

Research Depth 88 in the knowledge graph I know this Set as goal
455prerequisites beneath it
See this on the map →
Lie Group Representations (Introduction)Reducibility and Irreducibility+1 more
sl2 highest-weight casimir-element weight-space raising-lowering

Core Idea

The representation theory of SLβ‚‚(β„‚) (or equivalently its Lie algebra 𝔰𝔩₂(β„‚)) is the fundamental example in Lie theory. The Lie algebra 𝔰𝔩₂ is spanned by three elements e, f, h with [h,e] = 2e, [h,f] = βˆ’2f, [e,f] = h. The finite-dimensional irreducible representations are classified by a single non-negative integer n: for each n β‰₯ 0, there is a unique (n+1)-dimensional irreducible representation V(n) with highest weight n. The representation V(n) has a basis of weight vectors v_n, v_{nβˆ’2}, …, v_{βˆ’n} on which e raises weight by 2, f lowers weight by 2, and h acts by the weight.

Explainer

The Lie algebra 𝔰𝔩₂(β„‚) consists of 2Γ—2 traceless complex matrices. It is 3-dimensional with standard basis: e = [[0,1],[0,0]] (strictly upper triangular), f = [[0,0],[1,0]] (strictly lower triangular), and h = [[1,0],[0,βˆ’1]] (diagonal). The commutation relations are [h,e] = 2e, [h,f] = βˆ’2f, [e,f] = h. These relations, not the specific matrices, determine the representation theory. The element h generates a Cartan subalgebra, e is a raising operator, and f is a lowering operator.

A representation V of 𝔰𝔩₂ decomposes into weight spaces V = βŠ•_Ξ» V_Ξ», where V_Ξ» = {v ∈ V : hΒ·v = Ξ»v}. The commutation relations force e to raise weights by 2 (if v ∈ V_Ξ», then eΒ·v ∈ V_{Ξ»+2}) and f to lower weights by 2. In a finite-dimensional representation, there must be a highest weight vector v_Ξ» with eΒ·v_Ξ» = 0 (since weights are bounded above). Starting from v_Ξ» and applying f repeatedly generates v_Ξ», fΒ·v_Ξ», fΒ²Β·v_Ξ», … until reaching the lowest weight. If the highest weight is n, this chain has length n+1, producing an (n+1)-dimensional space with weights n, nβˆ’2, …, βˆ’n.

The classification theorem states: for each integer n β‰₯ 0, there is a unique irreducible representation V(n) of dimension n+1, and every finite-dimensional representation is a direct sum of these. The proof uses the Casimir element C = hΒ² + 2h + 4fe ∈ U(𝔰𝔩₂), which lies in the center of the universal enveloping algebra and acts as the scalar n(n+2) on V(n). Since this scalar is distinct for each n, the Casimir separates irreducibles. Complete reducibility follows from the fact that SU(2) (the compact real form) is compact, so the analogue of Maschke's theorem applies.

The Clebsch-Gordan formula describes tensor products: V(m) βŠ— V(n) β‰… V(m+n) βŠ• V(m+nβˆ’2) βŠ• Β·Β·Β· βŠ• V(|mβˆ’n|), a multiplicity-free direct sum. This is the mathematical content of angular momentum addition in quantum mechanics (with V(n) corresponding to spin n/2). The formula can be proved by comparing characters or by explicitly constructing highest weight vectors in the tensor product. The entire structure β€” weight space decomposition, highest weight classification, Casimir element, Clebsch-Gordan decomposition β€” generalizes to all semisimple Lie algebras, with 𝔰𝔩₂ providing the blueprint for the general theory via the root system.

Practice Questions 5 questions

Prerequisite Chain

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

Longest path: 89 steps · 455 total prerequisite topics

Prerequisites (3)

Leads To (0)

No topics depend on this one yet.