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A Productization Property/Trick For H-Stable(And Hopefully Strongly Log-Concave) Polynomials

Talkat Optimization Under Symmetry 2021 · 2021-11-29..12-03
links:none on file
slides:none on file

Claims a productization trick that locally expresses many H-stable (real-stable) polynomials as a product of simpler “product polynomials” built from matrices whose row and column sums meet prescribed vectors, uses matrix eigen/Schur decompositions and semi‑algebraic reductions, and converts known matrix capacity/permanent bounds into polynomial coefficient lower bounds. Provides a polynomial-time zero test for the infimum over that polytope, shows L1 condition (not L2) is the natural necessary/sufficient closeness measure, and drives improved van der Waerden–style bounds used in recent traveling‑salesman work.

AI-written summary · about

  1. 0:00Introduction
  2. 7:55Hyperbolic polynomials
  3. 14:05Doubly stochastic polynomials
  4. 21:27Minimizing capacity
  5. 27:46Productization trick explained
  6. 34:16Proof approaches
  7. 41:00When trick fails
  8. 45:05H-stable polynomials
  9. 48:51Non-homogeneous polynomials
  10. 54:42Traveling salesman problem
  11. 58:52Q&A
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