{"title":"Exercise Solutions","authors":"René Orth","doi":"10.1061/9780784409213.apb","DOIUrl":null,"url":null,"abstract":"Linear Algebra Methods in Combinatorics This file contains solutions to some of the exercises, and it will be periodically updated. 1 Exercise Set 2 Exercise 4 (One-Distance Sets). A regular simplex is a set of n + 1 points in R n such that any two points are at distance 1. Prove that no set with this property can have more points. n are such that d(s i , s j) = 1 for all i = j (1) where d() is the Euclidean distance, then m ≤ n + 1. If you cannot prove this bound, try to prove the simpler bound m ≤ n + 2. Warm up (\" n + 2 \"). We can assume wlog that d() is the square of the Euclidean distance (this will not change the problem), that is d(x, y) = k","PeriodicalId":292995,"journal":{"name":"An Invitation to Applied Category Theory","volume":"108 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"An Invitation to Applied Category Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1061/9780784409213.apb","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Linear Algebra Methods in Combinatorics This file contains solutions to some of the exercises, and it will be periodically updated. 1 Exercise Set 2 Exercise 4 (One-Distance Sets). A regular simplex is a set of n + 1 points in R n such that any two points are at distance 1. Prove that no set with this property can have more points. n are such that d(s i , s j) = 1 for all i = j (1) where d() is the Euclidean distance, then m ≤ n + 1. If you cannot prove this bound, try to prove the simpler bound m ≤ n + 2. Warm up (" n + 2 "). We can assume wlog that d() is the square of the Euclidean distance (this will not change the problem), that is d(x, y) = k