English

A Conditional Upper Bound for the Moving Sofa Problem

Metric Geometry 2024-12-03 v2 Optimization and Control

Abstract

The moving sofa problem asks for the connected shape with the largest area μmax\mu_{\text{max}} that can move around the right-angled corner of a hallway LL with unit width. The best bounds currently known on μmax\mu_{\max} are summarized as 2.2195μmax2.372.2195\ldots \leq \mu_{\max} \leq 2.37. The lower bound 2.2195μmax2.2195\ldots \leq \mu_{\max} comes from Gerver's sofa SGS_G of area μG:=2.2195\mu_G := 2.2195\ldots. The upper bound μmax2.37\mu_{\max} \leq 2.37 was proved by Kallus and Romik using extensive computer assistance. It is conjectured that the equality μmax=μG\mu_{\max} = \mu_G holds at the lower bound. We develop a new approach to the moving sofa problem by approximating it as an infinite-dimensional convex quadratic optimization problem. The problem is then explicitly solved using a calculus of variation based on the Brunn-Minkowski theory. Consequently, we prove that any moving sofa satisfying a property named the injectivity condition has an area of at most 1+π2/8=2.23371 + \pi^2/8 = 2.2337\dots. The new conditional bound does not rely on any computer assistance, yet it is much closer to the lower bound 2.21952.2195\ldots of Gerver than the computer-assisted upper bound 2.372.37 of Kallus and Romik. Gerver's sofa SGS_G, the conjectured optimum, satisfies the injectivity condition in particular.

Cite

@article{arxiv.2406.10725,
  title  = {A Conditional Upper Bound for the Moving Sofa Problem},
  author = {Jineon Baek},
  journal= {arXiv preprint arXiv:2406.10725},
  year   = {2024}
}

Comments

This work has been superseded by arXiv:2411.19826 that resolves the moving sofa problem completely. Do not cite this work

R2 v1 2026-06-28T17:07:23.789Z