Macbeath region

Brief description on Macbeath Regions
The Macbeath region around a point x in a convex body K and the scaled Macbeath region around a point x in a convex body K

In mathematics, a Macbeath region is an explicitly defined region in convex analysis on a bounded convex subset of d-dimensional Euclidean space R d {\displaystyle \mathbb {R} ^{d}} . The idea was introduced by Alexander Macbeath (1952)[1] and dubbed by G. Ewald, D. G. Larman and C. A. Rogers in 1970.[2] Macbeath regions have been used to solve certain complex problems in the study of the boundaries of convex bodies.[3] Recently they have been used in the study of convex approximations and other aspects of computational geometry.[4][5]

Definition

Let K be a bounded convex set in a Euclidean space. Given a point x and a scaler λ the λ-scaled the Macbeath region around a point x is:

M K ( x ) = K ( 2 x K ) = x + ( ( K x ) ( x K ) ) = { k K | k K  and  k x = x k } {\displaystyle {M_{K}}(x)=K\cap (2x-K)=x+((K-x)\cap (x-K))=\{k'\in K|\exists k\in K{\text{ and }}k'-x=x-k\}}

The scaled Macbeath region at x is defined as:

M K λ ( x ) = x + λ ( ( K x ) ( x K ) ) = { ( 1 λ ) x + λ k | k K , k K  and  k x = x k } {\displaystyle M_{K}^{\lambda }(x)=x+\lambda ((K-x)\cap (x-K))=\{(1-\lambda )x+\lambda k'|k'\in K,\exists k\in K{\text{ and }}k'-x=x-k\}}

This can be seen to be the intersection of K with the reflection of K around x scaled by λ.

Example uses

  • Macbeath regions can be used to create ϵ {\displaystyle \epsilon } approximations, with respect to the Hausdorff distance, of convex shapes within a factor of O ( log d + 1 2 ( 1 ϵ ) ) {\displaystyle O(\log ^{\frac {d+1}{2}}({\frac {1}{\epsilon }}))} combinatorial complexity of the lower bound.[5]
  • Macbeath regions can be used to approximate balls in the Hilbert metric, e.g. given any convex K, containing an x and a 0 λ < 1 {\displaystyle 0\leq \lambda <1} then:[4][6]
B H ( x , 1 2 ln ( 1 + λ ) ) M λ ( x ) B H ( x , 1 2 ln 1 + λ 1 λ ) {\displaystyle B_{H}\left(x,{\frac {1}{2}}\ln(1+\lambda )\right)\subset M^{\lambda }(x)\subset B_{H}\left(x,{\frac {1}{2}}\ln {\frac {1+\lambda }{1-\lambda }}\right)}
  • Dikin’s Method

Properties

  • The M K λ ( x ) {\displaystyle M_{K}^{\lambda }(x)} is centrally symmetric around x.
  • Macbeath regions are convex sets.
  • If x , y K {\displaystyle x,y\in K} and M 1 2 ( x ) M 1 2 ( y ) {\displaystyle M^{\frac {1}{2}}(x)\cap M^{\frac {1}{2}}(y)\neq \emptyset } then M 1 ( y ) M 5 ( x ) {\displaystyle M^{1}(y)\subset M^{5}(x)} .[3][4] Essentially if two Macbeath regions intersect, you can scale one of them up to contain the other.
  • If some convex K in R d {\displaystyle R^{d}} containing both a ball of radius r and a half-space H, with the half-space disjoint from the ball, and the cap K H {\displaystyle K\cap H} of our convex set has a width less than or equal to r 2 {\displaystyle {\frac {r}{2}}} , we get K H M 3 d ( x ) {\displaystyle K\cap H\subset M^{3d(x)}} for x, the center of gravity of K in the bounding hyper-plane of H.[3]
  • Given a convex body K R d {\displaystyle K\subset R^{d}} in canonical form, then any cap of K with width at most 1 6 d {\displaystyle {\frac {1}{6d}}} then C M 3 d ( x ) {\displaystyle C\subset M^{3d}(x)} , where x is the centroid of the base of the cap.[5]
  • Given a convex K and some constant λ > 0 {\displaystyle \lambda >0} , then for any point x in a cap C of K we know M λ ( x ) K C 1 + λ {\displaystyle M^{\lambda }(x)\cap K\subset C^{1+\lambda }} . In particular when λ 1 {\displaystyle \lambda \leq 1} , we get M λ ( x ) C 1 + λ {\displaystyle M^{\lambda }(x)\subset C^{1+\lambda }} .[5]
  • Given a convex body K, and a cap C of K, if x is in K and C M ( x ) {\displaystyle C\cap M'(x)\neq \emptyset } we get M ( x ) C 2 {\displaystyle M'(x)\subset C^{2}} .[5]
  • Given a small ϵ > 0 {\displaystyle \epsilon >0} and a convex K R d {\displaystyle K\subset R^{d}} in canonical form, there exists some collection of O ( 1 ϵ d 1 2 ) {\displaystyle O\left({\frac {1}{\epsilon ^{\frac {d-1}{2}}}}\right)} centrally symmetric disjoint convex bodies R 1 , . . . . , R k {\displaystyle R_{1},....,R_{k}} and caps C 1 , . . . . , C k {\displaystyle C_{1},....,C_{k}} such that for some constant β {\displaystyle \beta } and λ {\displaystyle \lambda } depending on d we have:[5]
    • Each C i {\displaystyle C_{i}} has width β ϵ {\displaystyle \beta \epsilon } , and R i C i R i λ {\displaystyle R_{i}\subset C_{i}\subset R_{i}^{\lambda }}
    • If C is any cap of width ϵ {\displaystyle \epsilon } there must exist an i so that R i C {\displaystyle R_{i}\subset C} and C i 1 β 2 C C i {\displaystyle C_{i}^{\frac {1}{\beta ^{2}}}\subset C\subset C_{i}}

References

  1. ^ Macbeath, A. M. (September 1952). "A Theorem on Non-Homogeneous Lattices". The Annals of Mathematics. 56 (2): 269–293. doi:10.2307/1969800. JSTOR 1969800.
  2. ^ Ewald, G.; Larman, D. G.; Rogers, C. A. (June 1970). "The directions of the line segments and of the r-dimensional balls on the boundary of a convex body in Euclidean space". Mathematika. 17 (1): 1–20. doi:10.1112/S0025579300002655.
  3. ^ a b c Bárány, Imre (June 8, 2001). "The techhnique of M-regions and cap-coverings: a survey". Rendiconti di Palermo. 65: 21–38.
  4. ^ a b c Abdelkader, Ahmed; Mount, David M. (2018). "Economical Delone Sets for Approximating Convex Bodies". 16th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2018). 101: 4:1–4:12. doi:10.4230/LIPIcs.SWAT.2018.4.
  5. ^ a b c d e f Arya, Sunil; da Fonseca, Guilherme D.; Mount, David M. (December 2017). "On the Combinatorial Complexity of Approximating Polytopes". Discrete & Computational Geometry. 58 (4): 849–870. arXiv:1604.01175. doi:10.1007/s00454-016-9856-5. S2CID 1841737.
  6. ^ Vernicos, Constantin; Walsh, Cormac (2021). "Flag-approximability of convex bodies and volume growth of Hilbert geometries". Annales Scientifiques de l'École Normale Supérieure. 54 (5): 1297–1314. arXiv:1809.09471. doi:10.24033/asens.2482. S2CID 53689683.

Further reading

  • Dutta, Kunal; Ghosh, Arijit; Jartoux, Bruno; Mustafa, Nabil (2019). "Shallow Packings, Semialgebraic Set Systems, Macbeath Regions, and Polynomial Partitioning". Discrete & Computational Geometry. 61 (4): 756–777. doi:10.1007/s00454-019-00075-0. S2CID 127559205.