Computing Multiplicities of Lie Group Representations
summary
Algorithm computes branching multiplicities when group/homomorphism and number of diagram rows are fixed, running in poly-time for fixed rank (polynomial in log n). Method reduces highest-weight decomposition to weight multiplicities via Kostka-type partition functions, evaluates them with Barvinok lattice-point counting, then recovers highest-weight multiplicities by finite-difference inversion (derivative principle). Implementation (leadspeak.org) handles d=3 and extremely large box counts (reports up to 10^8), and recent refinements by Panova and Pak speed up zero/nonzero tests.
AI-written summary · about
chapters (15)
- 0:00Introduction
- 1:07Talk structure
- 3:13Branching problem setup
- 5:26Kostka numbers example
- 10:32Littlewood-Richardson example
- 13:55Kronecker coefficients example
- 16:00Plethysm coefficients example
- 19:54Known results overview
- 27:57Main theorem
- 33:25Proof strategy
- 36:35Weight multiplicities step
- 43:06Branching decomposition step
- 46:38Recovering multiplicities step
- 50:08Kronecker simpler case
- 54:09Software results
related talks
43mApplied Hodge Theory
01h 00mAverage-case Complexity for Polynomials, and All That
01h 01mTrue Complexity of Multilinear Systems
01h 11mPedagogical Talk: Failure of Low-Degree Polynomials
01h 00mOn Approximating the Covering Radius and Finding Dense Lattice Subspaces
01h 07mA Few Simple Average-Case Reduction Techniques And Their Surprising Effectiveness
11mUnderstanding Statistical-to-Computational Gaps via Low-Degree Polynomials
54mNegative Dependence and Lorentzian Polynomials
