Representation Qit
Exercise PLAN-113
primary source nl only. Current content-bound mathematical second pass accepted. No new Lean verification is claimed for this NL view.
Assumptions and conventions
Question
Let (phi, V) be a finite-dimensional complex representation of a finite group G. For the trivial representation, define P := (1/|G|) sum_{g in G} phi(g). Prove that (a) P is idempotent (P^2 = P), (b) im P = V^G := {|v> : phi(g)|v> = |v> for all g}, and (c) P commutes with every phi(h). Then explain, by taking the trace, why tr P equals the multiplicity of the trivial representation in V (the number of independent G-invariant vectors), connecting to the general character-projection formula P_W = (dim W / |G|) sum_g conj(chi_W(g)) phi(g).
Hint: mathematical route
Averaging the representation over G gives the orthogonal projection onto the invariant vectors V^G, whose trace counts the trivial-representation multiplicity, the trivial case of the character projection formula.
- Reindexing g -> hg gives phi(h) P = P (and P phi(h) = P), so P commutes with the representation.
- P^2 = (1/|G|) sum_g phi(g) P = P, so P is idempotent.
- im P subset V^G (image vectors fixed) and V^G subset im P (invariant vectors satisfy P|v>=|v>), so im P = V^G.
- As an orthogonal projection tr P = dim V^G = multiplicity of the trivial irrep, the chi_triv case of the character projector.
Reference solution
(a) and (c) together: for any h in G, phi(h) P = (1/|G|) sum_g phi(h)phi(g) = (1/|G|) sum_g phi(hg) = (1/|G|) sum_{g'} phi(g') = P, reindexing g' = hg (a bijection of G); likewise P phi(h) = P by reindexing on the right. So phi(h) P = P = P phi(h) for all h, which gives both that P commutes with every phi(h) and that P is left/right absorbing for the group action. Idempotency follows: P^2 = (1/|G|) sum_g phi(g) P = (1/|G|) sum_g P = P, using phi(g) P = P from the previous line. (b) If |v> in im P, write |v> = P|w>; then phi(h)|v> = phi(h) P|w> = P|w> = |v> for all h, so |v> in V^G, giving im P subset V^G. Conversely if |v> in V^G then phi(g)|v> = |v> for all g, so P|v> = (1/|G|) sum_g phi(g)|v> = (1/|G|) sum_g |v> = |v>, hence |v> in im P; thus V^G subset im P. Therefore im P = V^G. (b continued, trace) Since P is idempotent and (being an average of the unitaries phi(g) in a suitable invariant inner product) an orthogonal projection, its trace equals the dimension of its image: tr P = dim im P = dim V^G, which is precisely the number of independent G-invariant vectors, i.e. the multiplicity of the trivial representation in V. This is the chi_W = chi_triv = 1 case of the general formula P_W = (dim W/|G|) sum_g conj(chi_W(g)) phi(g): the trivial representation has dimension 1 and character identically 1, so P_triv = (1/|G|) sum_g phi(g) = P, and its trace recovers the multiplicity, consistent with the character inner-product formula for multiplicities.
Assessment rubric
- Proves phi(h) P = P = P phi(h) via reindexing, giving both commutation with phi(h) and absorption (1 weight)
- Deduces idempotency P^2 = P from phi(g) P = P (1 weight)
- Proves im P = V^G by double inclusion (image vectors are invariant; invariant vectors are fixed by P) (1 weight)
- Explains tr P = dim V^G = multiplicity of the trivial representation, as the chi_triv case of P_W = (dim W/|G|) sum_g conj(chi_W(g)) phi(g) (1 weight)
Graph-grounded prerequisites
These are support/source anchors, not an automatically extracted theorem-dependency proof.
- Harmonic analysis (frozen curriculum anchor; see graph registry)
- Operator and semigroup theory (frozen curriculum anchor; see graph registry)
- Matrix analysis (frozen curriculum anchor; see graph registry)
Lean view and evidence boundary
No aligned Lean view has been admitted for this native core in this textbook checkpoint. This is not a claim that the underlying mathematics lacks a formal proof. Contributions must preserve this exact target contract and split.
Sources and provenance
- website/research/sources.json
leditzky-2025-repth-qit
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Graph snapshot: qcb-snapshot-ffa644f0da3031a1ce754b9a
Authored support steps: 4. This is not measured graph distance or model difficulty.