On the Site Percolation Threshold of Circle Packings and Planar Graphs
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Three Puzzles on Mathematics, Computation, and Games
THREE PUZZLES ON MATHEMATICS, COMPUTATION, AND GAMES GIL KALAI HEBREW UNIVERSITY OF JERUSALEM AND YALE UNIVERSITY ABSTRACT. The second puzzle is about errors made when votes are counted during elections. 1. INTRODUCTION The theory of computing and computer science as a whole are precious resources for mathematicians. They bring new questions, new profound ideas, and new perspectives on classical mathematical ob- jects, and serve as new areas for applications of mathematics and of mathematical reasoning. In my lecture I will talk about three mathematical puzzles involving mathematics and computation (and, at times, other fields) that have preoccupied me over the years. The connection between mathematics and computing is especially strong in my field of combinatorics, and I believe that being able to per- sonally experience the scientific developments described here over the last three decades may give my description some added value. For all three puzzles I will try to describe with some detail both the large picture at hand, and zoom in on topics related to my own work. Puzzle 2: What are methods of election that are immune to errors in the counting of votes? The second puzzle can be seen in the context of understanding and planning of electoral methods. We all remember the sight of vote recount in Florida in the 2000 US presidential election. Is the American electoral system, based on electoral votes, inherently more susceptible to mistakes than the majority system? And what is the most stable method? Together with Itai Benjamini and Oded Schramm we investigated these and similar problems. We asked the following question: given that there are two Work supported in part by ERC advanced grant 320924, BSF grant 2006066, and NSF grant DMS-1300120. -
A Complete Bibliography of Combinatorics, Probability and Computing
A Complete Bibliography of Combinatorics, Probability and Computing Nelson H. F. Beebe University of Utah Department of Mathematics, 110 LCB 155 S 1400 E RM 233 Salt Lake City, UT 84112-0090 USA Tel: +1 801 581 5254 FAX: +1 801 581 4148 E-mail: [email protected], [email protected], [email protected] (Internet) WWW URL: http://www.math.utah.edu/~beebe/ 14 May 2021 Version 2.28 Title word cross-reference (1; 2) [HJ94]. (5; 5) [CH18]. (7; 4) [Sol15]. (∆ + 1) [BBP21]. (k + 1) [oCM12]. (k − 1) [LW07]. (n; d; λ) [Ofe07]. 0 [BKHL99, VZ06]. 0 <q<1 [Lar21]. 1 [BB12, BKHL99, RM92, VZ06]. 1324 [B´on14]. 2 [BLS+12b, DH00, FS12, FK06, F¨ur12, HZ17, IK09, M´at07, Nob06, Saa96, SS06b, Wu97, Yus07]. 2=3 [KLS+13]. $23.00 [Sco04]. 2k [NV05]. 2 × 2 [Had98, Had99]. 3 [AHL21, CP16, COMV09, EF95, FRV13, FRMZ21, GH17, GS11, HLP+09, HN18, Mar13, Mat03, PRS05, RW01, RRS06, Wag06a, Wu98]. 4 [BHL+15, FR01, KO04a, Mar13, Nag17, SW07a]. $49.95 [B´ar04, Lea04]. 5 [BDLP20]. $65.00 [Sco04]. 7 [Bri98]. 8 [Bri98]. 3;3 [KM12]. b [AF04]. B2[g] + [CV08]. Bh [DKL 16]. β [GA19]. C2k [GMT20]. C2k+1 [GL12b]. C4 [Pic11]. 3 C6 [GH17]. d [BCOK14a, BCOK15, BKW08, KN03, Siv14]. ∆ e − [FK09, KRT99]. ∆=2 [MR95]. [ABFK92]. F [PR17a, Wag00]. F7 [Mec01]. n F7 [Mec01]. Fp [Ngu11]. Fq[x] [Han93]. G [BFRT01, FR15, JT08b]. G(n; p) [Wol11]. Gn;p [CO07b]. GF (q) [Lef05]. H [AY93, AKS05, FJP13]. k 1 2 [Aig05, COGL07, COW18, CF95, CDD03, DHS16, Gao14, GGH12, GJ03, HZ05, Han15, JS20, KKY06, LMMW09, Nik01b, PV13, PS16, Ras19, Rio08, Sha11, Sub00, XY11, oCM12]. -
Around Two Theorems and a Lemma by Lucio Russo
NISSUNA UMANA INVESTIGAZIONE SI PUO DIMANDARE VERA SCIENZIA S’ESSA NON PASSA PER LE MATEMATICHE DIMOSTRAZIONI LEONARDO DA VINCI vol. 6 no. 2 2018 Mathematics and Mechanics of Complex Systems ITAI BENJAMINI AND GIL KALAI AROUND TWO THEOREMS AND A LEMMA BY LUCIO RUSSO msp MATHEMATICS AND MECHANICS OF COMPLEX SYSTEMS Vol. 6, No. 2, 2018 dx.doi.org/10.2140/memocs.2018.6.69 ∩ MM AROUND TWO THEOREMS AND A LEMMA BY LUCIO RUSSO ITAI BENJAMINI AND GIL KALAI We describe two directions of study following early work of Lucio Russo. The first direction follows the famous Russo–Seymour–Welsh (RSW) theorem. We describe an RSW-type conjecture by the first author which, if true, would imply a coarse version of conformal invariance for critical planar percolation. The second direction is the study of “Russo’s lemma” and “Russo’s 0–1 law” for threshold behavior of Boolean functions. We mention results by Friedgut, Bour- gain, and Hatami, and present a conjecture by Jeff Kahn and the second author, which may allow applications for finding critical probabilities. 1. Introduction We have not met Lucio Russo in person but his mathematical work has greatly influenced our own and his wide horizons and interests in physics, mathematics, philosophy, and history have greatly inspired us. We describe here two directions of study following early work of Russo. The first section follows the famous Russo–Seymour–Welsh theorem regarding critical planar percolation. The second section follows the basic “Russo’s lemma” and the deep “Russo’s 0–1 law”. In each direction we present one central conjecture. -
Three Puzzles on Mathematics, Computation, and Games
THREE PUZZLES ON MATHEMATICS, COMPUTATION, AND GAMES GIL KALAI HEBREW UNIVERSITY OF JERUSALEM AND YALE UNIVERSITY ABSTRACT. In this lecture I will talk about three mathematical puzzles involving mathematics and computation that have preoccupied me over the years. The first puzzle is to understand the amazing success of the simplex algorithm for linear programming. The second puzzle is about errors made when votes are counted during elections. The third puzzle is: are quantum computers possible? 1. INTRODUCTION The theory of computing and computer science as a whole are precious resources for mathematicians. They bring new questions, new profound ideas, and new perspectives on classical mathematical ob- jects, and serve as new areas for applications of mathematics and of mathematical reasoning. In my lecture I will talk about three mathematical puzzles involving mathematics and computation (and, at times, other fields) that have preoccupied me over the years. The connection between mathematics and computing is especially strong in my field of combinatorics, and I believe that being able to per- sonally experience the scientific developments described here over the last three decades may give my description some added value. For all three puzzles I will try to describe with some detail both the large picture at hand, and zoom in on topics related to my own work. Puzzle 1: What can explain the success of the simplex algorithm? Linear programming is the problem of maximizing a linear function φ subject to a system of linear inequalities. The set of solutions for the linear inequalities is a convex polytope P (which can be unbounded).