Low-degree minimal spanning trees in normed spaces
Approximation k-hop minimum-spanning trees

离散数学双语课程教学大纲

离散数学》双语课程教学大纲一、课程编号:040510二、课程类型:必修课程学时:理论教学 72学时 / 4.5学分。
适用专业:信息与计算科学专业。
先修课程:线性代数、概率论、高等数学等。
后续课程:编译原理、操作系统、数据结构、数据库等。
三、课程性质与任务《离散数学》是信息与计算科学中基础理论的核心课程。
该课程采用双语教学形式,教材是国外原版英语教材。
通过本课程的学习,主要培养学生的抽象思维能力、严密的逻辑推理能力、阅读外文科技文献能力和专业英语写作能力。
并为学生今后处理离散信息、离散建模、软件开发、计算机硬件系统设计、程序设计的时间和空间复杂度分析等提供理论指导基础,是学生从事信息科学的实际工作必备数学工具。
四、教学主要内容及学时分配授课内容教学要求课时1.Fundamentals1.1.Sets and subsets1.2.Operations on sets1.5.Boolean matrix掌握 62 Logic2.1.Propositions and logical operations 2.2.Conditional Statements2.3.Methods of proof 掌握103.Counting3.1.Permutationsbinations3.3.Pigeonhole principle掌握 64.Relations and Digraphs4.1.Product sets4.1.Product sets and Partitions4.2.Relations and Digraphs4.3.Paths in Relations and Digraphs掌握204.4.Properties of relations4.5.Equivalence relations4.7.Operations on relations4.8.Transitive closure and Warshall’s Algorithm5.Functions5.1.Functions5.2.Functions for computer science5.3.Growth of functions5.4.Permutation Functions掌握 6 6.Order relations and structures6.1.Partially ordered sets6.2.Extremal elements of partially ordered sets 掌握67.Trees7.1.Treesbeled Trees7.3.Tree searching7.4.Undirected Trees7.5.Minimal spanning trees掌握 68.Topics in Graph theory8.1.Graphs8.2.Euler paths and circuits8.3.Hamiltonian paths and circuits8.5.matching problems8.6.coloring graphs掌握8五、教学基本要求了解离散数学所涵盖的内容及背景思想;理解离散数学组的数学思想和基本概念。
离散数学英中名词对照表

离散数学英中名词对照表英文Abel categoryAbel group (commutative group) Abel semigroup Abelian groupabsorption property accessibility relation acyclicaddition principleadequate set of connectives adjacentadjacent matrixadjugateadjunctionaffine planealgebraic closed field algebraic element algebraic extensionalphabetalternating groupannihilatorantecedentanti symmetryanti-isomorphismarc setargumentarityarrangement problem associateassociativeassociative algebraassociatorasymmetricatomatomic formulaaugmenting pigeon hole principle augmenting path automorphism automorphism group of graph auxiliary symbol A 离散数学英文—中文名词axiom of choiceaxiom of equalityaxiom of extensionalityaxiom of infinityaxiom of pairsaxiom of regularityaxiom of replacement for the formulaaxiom of the empty setaxiom of unionB balanced imcomplete block designbarber paradoxbase (base 2 exponential function)base (logarithm function to the base 2)Bell numberBernoulli numberBerry paradoxbiconditionalbijection (one-to-one correspondence)bi-mdulebinary relationbinary operationbinary symmetric channel (BSC)binary treebinomial coefficientbinomial theorembinomial transform bipartite graphblockblockblock codeblock designBondy theoremBoolean algebra Boolean expression Boolean functionBoole homomorophism Boole latticeBoolean matrixBoolean productbound occurrencebound variablebounded latticeBruijn theorem Burnside lemmaC cagecancellation property canonical epimorphism Cantor conjecture Cantor diagonal method Cantor paradoxcapacitycardinal number cardinalityCartesion product of graph Catalan numbercatenationCayley graphCayley theoremceiling functioncell (block)centercertain eventchain (walk) characteristic function characteristic of ring characteristic polynomial check digitsChinese postman problem chromatic number chromatic polynomial circuitcirculant graph circumferenceclassclassical completeness classical consistent cliqueclique numberclose with respect to closed termclosureclosure of graphcode elementcode lengthcode wordcoefficientcoimageco-kernalcoloringcoloring problemcombinationcombination numbercombination with repetationcommon divisorcommon factorcommutativecommutative diagramcommutative ringcommutative seimgroupcomparablecompatible withcomplementcomplement elementcomplement of B with respect to A complementary relation complemented latticecomplete bipartite graphcomplete graphcomplete k-partite graphcomplete latticecomplete matchcomplete n-treecompositecomposite operationcomposition (molecular proposition) composition of graph (lexicographic product) compound statementconcatenation (juxtaposition) concatenation graphconditional statement (implication) congruence relationcongruent toconjectureconjunctive normal form connected component connective connectivityconnectivity relation consecutively consequence (conclusion) conservation of flow consistent (non-contradiction) constructive proofcontain (in)contingencycontinuumcontraction of graph contradiction contravariant functor contrapositiveconversecoproductcorankcorresponding universal map countable (uncountable) countably infinite set counter examplecountingcovariant functorcoveringcovering numbercrossing number of graph cosetcotreecutcut edgecut vertexcyclecycle basiscycle matrixcycle rankcycle spacecycle vectorcyclic groupcyclic indexcyclic permutation cyclic semigroupD De Morgan's law decision procedure decoding table deduction theorem degreedegree sequence derivation algebra Descartes product descendant designated truth value deterministic diagonal functor diagonal matrix diameterdigraphdilemmadirect consequence direct limitdirect sumdirected by inclutiondisconnecteddiscrete Fourier transform discrete graph (null graph) disjoint setdisjunctiondisjunctive normal form disjunctive syllogism distancedistance transitive graph distinguished element distributivedistributive lattice divisibilitydivision subringdivison ringdivisor (factor) dodecahedrondomaindual categorydual formdual graphdual principledual statementdummy variableE eccentricityedge chromatic number edge coloringedge connectivityedge coveringedge covering numberedge cutedge setedge-independence number eigenvalue of graph element (entry) elementary divisor ideal elementary product elementary sumempty graphempty relationempty set endomorphismendpointentry (element) enumeration function epimorphismequipotentequivalenceequivalent category equivalent class equivalent matrix equivalent object equivalent relationerror functionerror patternEuclid algorithmEuclid domainEuler characteristicEuler circuitEuler functionEuler graphEuler numberEuler pathEuler polyhedron formula Euler tourEuler traileven permutationeventeverywhere defined excess capacity existence proof existential generalization existential quantification existential quantifier existential specification explicitextended Fibonacci number extended Lucas number extensionextension field extension graphexterior algebraF facefactorfactorablefactotialfactorizationfaithful (full) functor Ferrers graphFibonacci numberfieldfilterfinite dimensional associative division algebra finite extensionfinite field (Galois field )finite groupfinite setfinitely generated modulefirst order theory with equalityfive-color theoremfive-time-repetitionfixed pointfloor functionflowforestforgetful functorfour-color theorem (conjecture)F-reduced productfree elementfree monoidfree occurrencefree R-modulefree variablefree-Ω-algebrafull n-treefunction schemeG Galileo paradoxGauss coefficientGBN (G?del-Bernays-von Neumann system) GCD (Greatest Common Divisor) generalized Petersen graphgenerating functiongenerating proceduregeneratorgenerator matrixgeneric elementgenusgirthG?del completeness theoremgolden section numbergraceful graphgraceful tree conjecturegraphgraph of first class for edge coloring graph of second class for edge coloring graph rankgraph sequencegreatest common factorgreatest elementgreedy algorithmGrelling paradoxGr?tzsch graphgroupgroup codegroup of graphgrowth of functionHajós conjectureHamilton cycleHamilton graphHamilton pathHarary graphhash functionHasse diagramHeawood graphheightHerschel graphhom functorhomemorphism homomorphism homomorphism image homomorphism of graph hyperoctahedronhypothelical syllogism hypothesis (premise)idealidempotentidentityidentity functionidentity natural transformation imageimbeddingimmediate predcessor immediate successorimpossible eventincidentincident axiomincident matrixinclusion and exclusion principle inclusion relationindegreeindependentindependent number independent setindependent transcendental element indexindirected method H Iindividual variableinduced subgraphinfinite extensioninfinite groupinfinite setinitial endpointinitial objectinjectioninjection functorinjective (one to one mapping) inner faceinner neighbour setinorder searchintegral domainintegral subdomaininternal direct sum intersectionintersection of graph intersection operation intervalinvariant factorinvariant factor idealinverseinverse limitinverse morphisminverse natural transformation inverse operationinverse relationinversioninvertableinvolution property irreflexiveisolated vertexisomorphic categoryisomorphismisomorphism of graphjoinjoin of graphJ Jordan algebraJordan product (anti-commutator)Jordan sieve formulaj-skewjuxtapositionk-chromatic graphk-connected graphk-critical graphk-edge chromatic graphk-edge-connected graphk-edge-critical graph Kanaugh mapkernelKirkman schoolgirl problem Klein 4 groupKonisberge Brudge problem Kruskal's algorithm Kuratowski theoremlabeled graphLah numberLatin rectangleLatin squarelatticelattice homomorphismlawLCM (Least Common Multiple) leader cosetleast elementleafleast upper boundleft (right) identityleft (right) invertible element left (right) moduleleft (right) zeroleft (right) zero divisorleft adjoint functorleft cancellableleft cosetlengthlexicographic orderlLie algebraline- grouplinear array (list)linear graphlinear order (total order)K Llinear order set (chain)logical connective logical followlogically equivanlent logically implies logically valid loopLucas numbermagicmany valued proposition logic map coloring problem matchingmathematical structure matrix representation maximal element maximal idealmaximal outerplanar graph maximal planar graph maximum flow maximum matching maxtermmaxterm normal form (conjunctive normal form)McGee graph meetMenger theorem Meredith graph message word mini term minimal -connected graph minimal polynomial minimal spanning tree Minimanoff paradox minimum distance Minkowski summinterm (fundamental conjunctive form)minterm normal form (disjunctive normal form)M?bius function M?bius ladder M?bius transform (inversion)modal logic modelmodule homomorphismMkmoduler latticemodulusmodus ponensmodus tollensmodule isomorphismmonic morphismmonoidmonomorphismmorphism (arrow)M?bius functionM?bius ladderM?bius transform (inversion)multigraphmultinomial coefficientmultinomial expansion theoremmultiple-error-correcting codemultiplication principlemutually exclusivemultiplication tablemutually orthogonal Latin squareN n-ary operationn-ary productn-ary tree (n-tree)n-tuplenatural deduction systemnatural homomorphismnatural isomorphismnatural transformationnearest neighbernegationneighbour setnext state transition functionnon-associative algebranon-standard logicNorlund formulanormal formnormal modelnormal subgroup (invariant subgroup)n-relationnull graph (discrete graph)null objectnullary operationobjectodd permutationoffspringone to oneone-to-one correspondence (bijection) onto optimal solutionorbitorderorder (lower order,same order) order ideal order relationordered pairOre conditionorientationorthogonal Latin square orthogonal layoutoutarcoutdegreeouter faceouter neighbourouterneighbour setouterplanar graphpancycle graphparallelismparallelism classparentparity-check codeparity-check equationparity-check machineparity-check matrixpartial functionpartial ordering (partial relation) partial order relation partial order set (poset)partitionpartition number of integerpartition number of setPascal formulapathperfect code O Pperfect t-error-correcting code perfect graph permutationpermutation grouppermutation with repetation Petersen graphp-graphPierce arrowpigeonhole principleplanar graphplane graphPolish formPólya theorempolynomailpolynomial codepolynomial representation polynomial ring positional treepossible worldpostorder searchpower functorpower of graphpower setpredicateprenex normal formpreorder searchpre-ordered setprimary cycle modulePRIM's algorithmprimeprime fieldprime to each otherprimitive connectiveprimitive elementprimitive polynomialprincipal idealprincipal ideal domainprinciple of dualityprinciple of mathematical induction principle of redundancy probabilisticprobability (theory)productproduct categoryproduct partial orderproduct-sum formproof (deduction)proof by contraditionproper coloringproper factorproper filterproper subgroupproperly inclusive relationproposition (statement)propositional constantpropositional formula (well-formed formula,wff) propositional functionpropositional variablepseudocodepullbackpushoutquantification theoryquantifierquasi order relationquaternionquotient (difference) algebraquotient algebraquotient field (field of fraction)quotient groupquotient modulequotient ring (difference ring , residue ring) quotient set Ramsey graph Ramsey number Ramsey theorem rangerankreachability reconstruction conjecture recursive redundant digits reflexiveregular expression regular graph R Qregular representationrelation matrixrelative setremainderreplacement theoremrepresentationrepresentation functorrestricted proposition formrestrictionretractionreverse Polish formRichard paradoxright adjoint functorright cancellableright factorright zero divisonringring of endomorphismring with unity elementR-linear independencerooted treeroot fieldrule of inferenceRussell paradoxS sample spacesatisfiablesaturatedscopesearchingsectionself-complement graphsemantical completenesssemantical consistentsemigroupseparable elementseparable extensionsequencesequentsequentialSheffer strokesiblingssimple algebraic extensionsimple cyclesimple extensionsimple graphsimple pathsimple proposition (atomic proposition) simple transcental extension simplicationsinkslopesmall categorysmallest element Socrates argument soundness (validity) theorem sourcespanning subgraph spanning treespectra of graphspetral radiussplitting fieldsquare matrixstandard modelstandard monomil statement (proposition) Steiner tripleStirling numberStirling transformstrong induction subalgebrasubcategorysubdirect product subdivison of graph subfieldsubformulasubdivision of graph subgraphsubgroupsub-modulesubmonoidsublatticesubrelationsubringsub-semigroup subscript。
图论总结(超强大)解读

1.图论Graph Theory1.1.定义与术语Definition and Glossary1.1.1.图与网络Graph and Network1.1.2.图的术语Glossary of Graph1.1.3.路径与回路Path and Cycle1.1.4.连通性Connectivity1.1.5.图论中特殊的集合Sets in graph1.1.6.匹配Matching1.1.7.树Tree1.1.8.组合优化Combinatorial optimization1.2.图的表示Expressions of graph1.2.1.邻接矩阵Adjacency matrix1.2.2.关联矩阵Incidence matrix1.2.3.邻接表Adjacency list1.2.4.弧表Arc list1.2.5.星形表示Star1.3.图的遍历Traveling in graph1.3.1.深度优先搜索Depth first search (DFS)1.3.1.1.概念1.3.1.2.求无向连通图中的桥Finding bridges in undirected graph1.3.2.广度优先搜索Breadth first search (BFS)1.4.拓扑排序Topological sort1.5.路径与回路Paths and circuits1.5.1.欧拉路径或回路Eulerian path1.5.1.1.无向图1.5.1.2.有向图1.5.1.3.混合图1.5.1.4.无权图Unweighted1.5.1.5.有权图Weighed —中国邮路问题The Chinese post problem1.5.2.Hamiltonian Cycle 哈氏路径与回路1.5.2.1.无权图Unweighted1.5.2.2.有权图Weighed —旅行商问题The travelling salesman problem1.6.网络优化Network optimization1.6.1.最小生成树Minimum spanning trees1.6.1.1.基本算法Basic algorithms1.6.1.1.1.Prim1.6.1.1.2.Kruskal1.6.1.1.3.Sollin(Boruvka)1.6.1.2.扩展模型Extended models1.6.1.2.1.度限制生成树Minimum degree-bounded spanning trees1.6.1.2.2.k小生成树The k minimum spanning tree problem(k-MST)1.6.2.最短路Shortest paths1.6.2.1.单源最短路Single-source shortest paths1.6.2.1.1.基本算法Basic algorithms1.6.2.1.1.1. ..................................................................................................... D ijkstra1.6.2.1.1.2. .......................................................................................... B ellman-Ford1.6.2.1.1.2.1.....................................Shortest path faster algorithm(SPFA)1.6.2.1.2.应用Applications1.6.2.1.2.1. ........................... 差分约束系统System of difference constraints1.6.2.1.2.2. .......................... 有向无环图上的最短路Shortest paths in DAG1.6.2.2.所有顶点对间最短路All-pairs shortest paths1.6.2.2.1.基本算法Basic algorithms1.6.2.2.1.1. ....................................................................................... F loyd-Warshall1.6.2.2.1.2. .................................................................................................... Johnson 1.6.3.网络流Flow network1.6.3.1.最大流Maximum flow1.6.3.1.1.基本算法Basic algorithms1.6.3.1.1.1. ........................................................................ Ford-Fulkerson method1.6.3.1.1.1.1.......................................................... E dmonds-Karp algorithm1.6.3.1.1.1.1.1. ................................................... M inimum length path1.6.3.1.1.1.1.2. ........................................... Maximum capability path1.6.3.1.1.2. ............................................... 预流推进算法Preflow push method1.6.3.1.1.2.1.................................................................................. P ush-relabel1.6.3.1.1.2.2........................................................................... Relabel-to-front1.6.3.1.1.3. .......................................................................................... Dinic method1.6.3.1.2.扩展模型Extended models1.6.3.1.2.1. ............................................................................... 有上下界的流问题1.6.3.2.最小费用流Minimum cost flow1.6.3.2.1.找最小费用路Finding minimum cost path1.6.3.2.2.找负权圈Finding negative circle1.6.3.2.3.网络单纯形Network simplex algorithm1.6.4.匹配Matching1.6.4.1.二分图Bipartite Graph1.6.4.1.1.无权图-匈牙利算法Unweighted - Hopcroft and Karp algorithm1.6.4.1.2.带权图-KM算法Weighted –Kuhn-Munkres(KM) algorithm1.6.4.2.一般图General Graph1.6.4.2.1.无权图-带花树算法Unweighted - Blossom (Edmonds)1.图论Graph Theory1.1. 定义与术语Definition and Glossary1.1.1.图与网络Graph and Network二元组(),V E称为图(graph)。
A Randomized Linear-Time Algorithm to Find Minimum Spanning

Cut Property
For any proper nonempty subset X of the vertices, the lightest edge with exactly one endpoint in X belongs to the minimum spanning tree.
Cut Property
X
VX
Boruvka Algorithm
For each vertex, select the minimum-weight edge incident to the vertex. Contract all the selected edges, replacing by a single vertex each connected component defined by the selected edges and deleting all resulting isolated vertices, loops (edges both of whose endpoints are the same), and all but the lowest-weight edge among each set of multiple edges. O(m log n)
Algorithm
G
G*
Return F
Back to analysis
G*
H F
E(G**) E(F(H)heaEv(yF))
E(G*) (F heavy) Algorithm
E(G*) E(H ) E(F)
图论总结(超强大)

图论总结(超强⼤)1.图论Graph Theory1.1.定义与术语Definition and Glossary1.1.1.图与⽹络Graph and Network1.1.2.图的术语Glossary of Graph1.1.3.路径与回路Path and Cycle1.1.4.连通性Connectivity1.1.5.图论中特殊的集合Sets in graph1.1.6.匹配Matching1.1.7.树Tree1.1.8.组合优化Combinatorial optimization1.2.图的表⽰Expressions of graph1.2.1.邻接矩阵Adjacency matrix1.2.2.关联矩阵Incidence matrix1.2.3.邻接表Adjacency list1.2.4.弧表Arc list1.2.5.星形表⽰Star1.3.图的遍历Traveling in graph1.3.1.深度优先搜索Depth first search (DFS)1.3.1.1.概念1.3.1.2.求⽆向连通图中的桥Finding bridges in undirected graph1.3.2.⼴度优先搜索Breadth first search (BFS)1.4.拓扑排序Topological sort1.5.路径与回路Paths and circuits1.5.1.欧拉路径或回路Eulerian path1.5.1.1.⽆向图1.5.1.2.有向图1.5.1.3.混合图1.5.1.4.⽆权图Unweighted2.Hamiltonian Cycle 哈⽒路径与回路1.5.2.1.⽆权图Unweighted1.5.2.2.有权图Weighed —旅⾏商问题The travelling salesman problem1.6.⽹络优化Network optimization1.6.1.最⼩⽣成树Minimum spanning trees1.6.1.1.基本算法Basic algorithms1.6.1.1.1.Prim1.6.1.1.2.Kruskal1.6.1.1.3.Sollin(Boruvka)1.6.1.2.扩展模型Extended models1.6.1.2.1.度限制⽣成树Minimum degree-bounded spanning trees1.6.1.2.2.k⼩⽣成树The k minimum spanning tree problem(k-MST)1.6.2.最短路Shortest paths1.6.2.1.单源最短路Single-source shortest paths1.6.2.1.1.基本算法Basic algorithms1.6.2.1.1.1. ..................................................................................................... D ijkstra1.6.2.1.1.2. .......................................................................................... B ellman-Ford1.6.2.1.1.2.1.....................................Shortest path faster algorithm(SPFA)1.6.2.1.2.应⽤Applications1.6.2.1.2.1. ........................... 差分约束系统System of difference constraints2.1.2.2. .......................... 有向⽆环图上的最短路Shortest paths in DAG1.6.2.2.所有顶点对间最短路All-pairs shortest paths1.6.2.2.1.基本算法Basic algorithms1.6.2.2.1.1. ....................................................................................... F loyd-Warshall1.6.2.2.1.2. .................................................................................................... Johnson 1.6.3.⽹络流Flow network1.6.3.1.最⼤流Maximum flow1.6.3.1.1.基本算法Basic algorithms1.6.3.1.1.1. ........................................................................ Ford-Fulkerson method 1.6.3.1.1.1.1.......................................................... E dmonds-Karp algorithm1.6.3.1.1.1.1.1. ................................................... M inimum length path1.6.3.1.1.1.1.2. ........................................... Maximum capability path1.6.3.1.1.2. ............................................... 预流推进算法Preflow push method1.6.3.1.1.2.1.................................................................................. P ush-relabel1.6.3.1.1.2.2........................................................................... Relabel-to-front1.6.3.1.1.3. .......................................................................................... Dinic method1.6.3.1.2.扩展模型Extended models1.6.3.1.2.1. ............................................................................... 有上下界的流问题1.6.3.2.最⼩费⽤流Minimum cost flow1.6.3.2.1.找最⼩费⽤路Finding minimum cost path1.6.3.2.2.找负权圈Finding negative circle2.3.⽹络单纯形Network simplex algorithm1.6.4.匹配Matching1.6.4.1.⼆分图Bipartite Graph1.6.4.1.1.⽆权图-匈⽛利算法Unweighted - Hopcroft and Karp algorithm1.6.4.1.2.带权图-KM算法Weighted –Kuhn-Munkres(KM) algorithm1.6.4.2.⼀般图General Graph1.6.4.2.1.⽆权图-带花树算法Unweighted - Blossom (Edmonds)1.图论Graph Theory1.1. 定义与术语Definition and Glossary1.1.1.图与⽹络Graph and Network⼆元组(),V E称为图(graph)。
(c) 1996 SIAM J. Computing LOW DEGREE SPANNING TREES OF SMALL WEIGHT

SAMIR KHULLER , BALAJI RAGHAVACHARI
y
AND NEAL YOUNG
z
Abstract. Given n points in the plane, the degree-K spanning tree problem asks for a spanning tree of minimum weight in which the degree of each vertex is at most K . This paper addresses the problem of computing low-weight degree-K spanning trees for K > 2. It is shown that for an arbitrary collection of n points in the plane, there exists a spanning tree of degree three whoss the weight of a minimum spanning tree. It is shown that there exists a spanning tree of degree four whose weight is at most 1.25 times the weight of a minimum spanning tree. These results solve open problems posed by Papadimitriou and Vazirani. Moreover, if a minimum spanning tree is given as part of the input, the trees can be computed in O(n) time. The results are generalized to points in higher dimensions. It is shown that for any d 3, an arbitrary collection of points in <d contains a spanning tree of degree three, whose weight is at most 5/3 times the weight of a minimum spanning tree. This is the rst paper that achieves factors better than two for these problems.
离散数学双语专业词汇表

《离散数学》双语专业词汇表set:集合subset:子集element, member:成员,元素well-defined:良定,完全确定brace:花括号representation:表示sensible:有意义的rational number:有理数empty set:空集Venn diagram:文氏图contain(in):包含(于)universal set:全集finite (infinite) set:有限(无限)集cardinality:基数,势power set:幂集operation on sets:集合运算disjoint sets:不相交集intersection:交union:并complement of B with respect to A:A与B的差集symmetric difference:对称差commutative:可交换的associative:可结合的distributive:可分配的idempotent:等幂的de Morgan’s laws:德摩根律inclusion-exclusion principle:容斥原理sequence:序列subscript:下标recursive:递归explicit:显式的string:串,字符串set corresponding to a sequence:对应于序列的集合linear array(list):线性表characteristic function:特征函数countable(uncountable):可数(不可数)alphabet:字母表word:词empty sequence(string):空串catenation:合并,拼接regular expression:正则表达式division:除法multiple:倍数prime:素(数)algorithm:算法common divisor:公因子GCD(greatest common divisor):最大公因子LCM(least common multiple):最小公倍数Euclidian algorithm:欧几里得算法,辗转相除法pseudocode:伪码(拟码)matrix:矩阵square matrix:方阵row:行column:列entry(element):元素diagonal matrix:对角阵Boolean matrix:布尔矩阵join:并meet:交Boolean product:布尔乘积mathematical structure(system):数学结构(系统)closed with respect to:对…是封闭的binary operation:二元运算unary operation:一元运算identity:么元,单位元inverse:逆元statement, proposition:命题logical connective:命题联结词compound statement:复合命题propositional variable:命题变元negation:否定(式)truth table:真值表conjunction:合取disjunction:析取quantifier:量词universal quantification:全称量词化propositional function:命题公式predicate:谓词existential quantification:存在量词化converse:逆命题conditional statement, implication:条件式,蕴涵式consequent, conclusion:结论,后件contrapositive:逆否命题hypothesis:假设,前提,前件biconditional, equivalence:双条件式,等价logically equivalent:(逻辑)等价的contingency:可满足式tautology:永真(重言)式contradiction, absurdity:永假(矛盾)式logically follow:是…的逻辑结论rules of reference:推理规则modus ponens:肯定律m odus tollens:否定律indirect method:间接证明法proof by contradiction:反证法counterexample;反例basic step:基础步principle of mathematical induction:(第一)数学归纳法induction step:归纳步strong induction:第二数学归纳法relation:关系digraph:有向图ordered pair:有序对,序偶product set, Caretesian set:叉积,笛partition, quotient set:划分,商集block, cell:划分块,单元domain:定义域range:值域R-relative set:R相关集vertex(vertices):结点,顶点edge:边in-degree:入度out-degree:出度path:通路,路径cycle:回路connectivity relation:连通性关系reachability relation:可达性关系composition:复合reflexive:自反的irreflexive:反自反的empty relation:空关系symmetric:对称的asymmetric:非对称的antisymmetric:反对称的graph:无向图undirected edge:无向边adjacent vertices:邻接结点connected:连通的transitive:传递的equivalent relation:等价关系congruent to:与…同余modulus:模equivalence class:等价类linked list:链表storage cell:存储单元pointer:指针complementary relation:补关系inverse:逆关系closure:闭包symmetric closure:对称闭包reflexive closure:自反闭包composition:关系的复合transitive closure:传递闭包Warshal’s algorithm:Warshall算法function, mapping, transformation:函数,映射,变换argument:自变量value, image:值,像,应变量labeled digraph:标记有向图identity function on A:A上的恒等函数everywhere defined:处处有定义的onto:到上函数,满射one to one:单射,一对一函数bijection, one-to-one correspondence:双射,一一对应invertible function:可逆函数floor function:下取整函数ceiling function:上取整函数Boolean function:布尔函数base 2 exponential function:以2为底的指数函数logarithm function to the base n:以n为底的对数hashing function:杂凑函数key:键growth of function:函数增长same order:同阶lower order:低阶running time:运行时间permutation:置换,排列cyclic permutation:循环置换,轮换transposition:对换odd(even) permutation:奇(偶)置换order relation:序关系partial order:偏序关系partially ordered set, poset:偏序集dual:对偶comparable:可比较的linear order(total order):线序,全序linearly ordered set, chain:线(全)序集,链product partial order:积偏序lexicographic order:字典序Hasse diagram:哈斯图topological sorting:拓扑排序isomorphism:同构maximal(minimal) element:极大(小)元extremal element:极值元素greatest(least) element:最大(小)元unit element:么(单位)元zero element:零元upper(lower) bound:上(下)界least upper(greatest lower) bound:上(下)确界lattice:格join:,保联,并meet:保交,交sublattice:子格absorption property:吸收律bounded lattice:有界格distributive lattice:分配格complement:补元modular lattice:模格Boolean algebra:布尔代数involution property:对合律Boolean polynomial, Boolean expression:布尔多项式(表达式)or(and, not) gate:或(与,非)门inverter:反向器circuit design:线路设计minterm:极小项Karnaugh map:卡诺图tree:树root:根,根结点rooted tree:(有)根树level:层,parent:父结点offspring:子女结点siblings:兄弟结点height:树高leaf(leave):叶结点ordered tree:有序树n-tree:n-元树complete n-tree:完全n-元树(complete) binary tree:(完全)二元(叉)树descendant:后代subtree:子树positional tree:位置树positional binary tree:位置二元(叉)树doubly linked list:双向链表tree searching:树的搜索(遍历)traverse:遍历,周游preorder search:前序遍历Polish form:(表达式的)波兰表示inorder search:中序遍历postorder search:后序遍历reverse Polish form:(表达式的)逆波兰表示linked-list representation:链表表示undirected tree:无向树undirected edge:无向边adjacent vertices:邻接结点simple path:简单路径(通路)simple cycle:简单回路acyclic:无(简单)回路的spanning tree:生成树,支撑树Prim’s algorithm:Prim算法minimal spanning tree:最小生成树weighted graph:(赋)权图weight:树distance:距离nearest neighbor:最邻近结点greedy algorithm:贪婪算法optimal solution:最佳方法Kruskal’s algorithm:Kruskal算法graph:(无向)图vertex(vertices):结点edge:边end point:端点relationship:关系connection:连接degree of a vertex:结点的度loop:自回路path:路径isolated vertex:孤立结点adjacent vertices:邻接结点circuit:回路simple path(circuit):基本路径(回路) connected:连通的disconnected:不连通的component:分图discrete graph(null graph):零图complete graph:完全图regular graph:正规图,正则图linear graph:线性图subgraph:子图Euler path(circuit):欧拉路径(回路) Konisberg Bridge problem:哥尼斯堡七桥问题ordinance:法规recycle:回收,再循环bridge:桥,割边Hamiltonian path(circuit):哈密尔顿路径(回路)dodecahedron:正十二面体weight:权TSP(traveling salesperson problem):货郎担问题transport network:运输网络capacity:容量maximum flow:最大流source:源sink:汇conversation of flow:流的守恒value of a flow:流的值excess capacity:增值容量cut:割the capacity of a cut:割的容量matching problems:匹配问题matching function:匹配函数compatible with:与…相容maximal match:最大匹配complete match:完全匹配coloring graphs:图的着色proper coloring:正规着色chromatic number of G:G的色数map-coloring problem:地图着色问题conjecture:猜想planar graph:(可)平面图bland meats:未加调料的肉chromatic polynomial:着色多项式binary operation on a set A:集合A上的二元运算closed under the operation:运算对…是封闭的commutative:可交换的associative:可结合的idempotent:幂等的distributive:可分配的semigroup:半群product:积free semigroup generated by A:由A生成的自由半群identity(element):么(单位)元monoid:含么半群,独异点subsemigroup:子半群submonoid:子含么半群isomorphism:同构homomorphism:同态homomorphic image:同态像Kernel:同态核congruence relation:同余关系natural homomorphism:自然同态group:群inverse:逆元quotient group:商群Abelian group:交换(阿贝尔)群cancellation property:消去律multiplication table:运算表finite group:有限(阶)群order of a group:群的阶symmetric group:对称群subgroup:子群alternating group:交替群Klein 4 group:Klein四元群coset:陪集(left) right coset:(左)右陪集normal subgroup:正规(不变)子群prerequisite:预备知识virtually:几乎informal brand:不严格的那种notation:标记sensible:有意义的logician:逻辑学家extensively:广泛地,全面地commuter:经常往来于两地的人by convention:按常规,按惯例dimension:维(数) compatible:相容的discipline:学科reasoning:推理declarative sentence:陈述句n-tuple:n-元组component sentence:分句tacitly:默认generic element:任一元素algorithm verification:算法证明counting:计数factorial:阶乘combination:组合pigeonhole principle:鸽巢原理existence proof:存在性证明constructive proof:构造性证明category:类别,分类factor:因子consecutively:相继地probability(theory):概率(论) die:骰子probabilistic:概率性的sample space:样本空间event:事件certain event:必然事件impossible event:不可能事件mutually exclusive:互斥的,不相交的likelihood:可能性frequency of occurrence:出现次数(频率) summarize:总结,概括plausible:似乎可能的equally likely:等可能的,等概率的random selection(choose an object at random):随机选择terminology:术语expected value:期望值backtracking:回溯characteristic equation:特征方程linear homogeneous relation of degree k:k阶线性齐次关系binary relation:二元关系prescribe:命令,规定coordinate:坐标criteria:标准,准则gender:性别graduate school:研究生院generalize:推广notion:概念intuitively:直觉地verbally:用言语approach:方法,方式conversely:相反地pictorially:以图形方式restriction:限制direct flight:直飞航班tedious:冗长乏味的main diagonal:主对角线remainder:余数random access:随机访问sequential access:顺序访问custom:惯例polynomial:多项式substitution:替换multi-valued function:多值函数collision:冲突analysis of algorithm:算法分析sophisticated:复杂的set inclusion(containment):集合包含distinguish:区分analogous:类似的ordered triple:有序三元组recreational area:游乐场所multigraph:多重图pumping station:抽水站depot:货站,仓库relay station:转送站。
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a rX iv:mat h /63394v1[mat h.MG ]16Mar26Low-degree minimal spanning trees in normed spaces ∗Horst Martini Fakult¨a t f¨u r Mathematik,Technische Universit¨a t Chemnitz,D-09107Chemnitz,Germany E-mail:martini@mathematik.tu-chemnitz.de Konrad J.Swanepoel Department of Mathematical Sciences University of South Africa PO Box 392,Pretoria 0003South Africa E-mail:swanekj@unisa.ac.za Abstract We give a complete proof that in any finite-dimensional normed linear space a finite set of points has a minimal spanning tree in which the maximum degree is bounded above by the strict Hadwiger number of the unit ball,i.e.,the largest number of unit vectors such that the distance between any two is larger than 1.1Introduction Let X d denote a d -dimensional Minkowski space,i.e.,R d equipped with a norm · .Let B ={x : x ≤1}be the unit ball of X d ,and let B (a,r )={x : x −a ≤r }be the closed ball with centre a and radius r .For any finite setS of points in X d ,let M (S )denote the set of minimal spanning trees (MSTs)on S .As usual,a minimal spanning tree of a set S is a tree with S as vertex set such that the sum of the lengths of the edges is a minimum over all trees on S .Let ∆(T )denote the maximum degree of a tree T .Define ∆+(S )=max {∆(T ):T ∈M (S )}and ∆−(S )=min {∆(T ):T ∈M (S )}.Thus ∆+(S )is the smallest number k such that all MSTs of S have maximum degree at mostk,and∆−(S)is the smallest number k such that there exists an MST of S of maximum degree at most k.Now define∆+(X d)=max{∆+(S):S⊂X d} and∆−(X d)=max{∆−(S):S⊂X d}.Again,∆+(X d)is the smallest number k such that all MSTs offinite subsets of X d have maximum degree at most k, and∆−(X d)is the smallest number k such that anyfinite subset of X d has an MST with maximum degree at most k.For the Euclidean plane E2,for example,∆+(E2)=6and∆−(E2)=5[PV84],while for the taxicab plane with norm (x,y)1=|x|+|y|we have∆+(R2, ·1)=8[HVW90]and∆−(R2, ·1)=4[RS95].The two quantities defined above are related to two quantities from convex geometry.Let C be an arbitrary convex body in R d.The Hadwiger number H(C)of C is the largest number k of translates{C+v1,...,C+v k}of C such that each C+v i touches C and such that no two C+v i intersect in interior points[Had57].Cieslik[Cie90,Cie91]first proved that∆+(X d)=H(B),where B is the unit ball of X d(see also[RS95]).Note that for a unit ball B the value H(B)equals the maximum number of unit vectors in X d such that the distance between any two is at most1.The value∆−(X d)also equals a similar quantity,called the MST number in[RS95],and called the weak Hadwiger number in[Swa99].Here we propose the following more descriptive name.The strict Hadwiger number H s(C)of C is the largest number k of translates{C+v1,...,C+v k}of C such that each C+v i touches C and such that any two C+v i are disjoint.Again note that for a unit ball B the value H s(B)equals the maximum number of unit vectors in X d such that the distance between any two is greater than1.For theℓp norm(x1,...,x d)p =(di=1|x i|p)1/p with unit ball B p it was shown by Robins andSalowe[RS95]that∆−(R d, ·p )=H s(B p).However,their proof uses a certainperturbation of points.It is not immediately clear how such a perturbation is to be done.It is the purpose of this note to clear up this point(using the Baire category theorem from point-set topology)and,simultaneously,to extend the result to arbitrary Minkowski spaces(using planar Minkowski geometry). Theorem.For any Minkowski space X d with unit ball B,∆−(X d)=H s(B).We note that there are many results about the Hadwiger number;see for example[B¨o r04,§2.9,§9.6,§9.7].We mention the following facts.For planar convex bodies,the Hadwiger number is8for parallelograms and6for all other bodies[Gr¨u61],for the three-dimensional octahedron O(the unit ball of the L1 norm in R3)it is H(O)=18[RS95],and for the d-cube C d(the unit ball of the L∞norm in R d)it is easily seen that H(C d)=3d−1.Much less is known about the strict Hadwiger number.For planar convex bodies,the strict Hadwiger number is4for parallelograms[RS95]and5for all other bodies[DLR92].For the three-dimensional Euclidean ball it is easily seen that the value equals the Hadwiger number,namely12.For the three-dimensional octahedron it is known that13≤H s(O)≤14[RS95],and for the d-cube H s(C d)=2d[RS95].22ProofThere exists a set S of H s (B )points on the boundary of the unit ball B such that the distance between any two is greater than 1.Then the set S ∪{o }has only one MST,with the origin o of degree H s (B ).It follows that ∆−(X d )≥H s (B ).We now show that for any finite set S in X d there exists an MST T with ∆(T )≤H s (B ).In order to do this,we consider angles.Anythree distinctpoints a,b,c ∈S define an angle ∢abc at b ,bounded by the rays −→ba and −→bc .(Ifb is between a andc on the same line,we may take either half plane to be the angle.)We define the size of ∢abc by|∢abc |:= 1c −b (c −b ) .This is the distance between the two points where the rays of the angle intersect the unit ball with centre b .In Euclidean space we have that |∢abc |=1if and only if the ordinary angular measure of ∢abc is 60◦.It is well-known that angles between incident edges in MSTs in Euclidean space are always at least 60◦.The Minkowski analogue,observed by Cieslik [Cie90],is as follows.Lemma 1.If ba and bc are two edges in an MST in a Minkowski space,then |∢abc |≥1.Proof.Without loss of generality we may assume that a −b ≥ c −b (oth-erwise interchange a ↔c ).Letd =b + c −bLemma2.Let∢abc be any angle in a Minkowski plane X2such that|∢abc|=1. Then for anyε>0there exists an angle∢a′b′c′with a−a′ ≤ε, b−b′ ≤ε, c−c′ ≤εand|∢a′b′c′|=1.Proof.Without loss of generality we may assume that b=o.Let x=1c c.If for all a′∈B(a,ε)and c′∈B(c,ε)we still have|∢a′bc′|=1,then all chords of the unit ball parallel to xy and sufficiently close to the chord xy have length1.Since the unit ball is convex,this is only possible if x and y are both contained in two parallel segments on the boundary of the unit ball. However,such parallel segments are either on the same line or on two different lines at distance2from each other.Both cases give a contradiction.The proof of the above lemma also gives that{S′∈P:|∢a′b′c′|=λ}is nowhere dense in P for any0<λ<2.Forλ=2this set is not necessarily nowhere dense if the norm is not strictly convex.Up to now we have shown that for any sufficiently smallε>0there exists an ε-perturbation Sεof S such that no angle in Sεhas size1.Consider now an MST of Sε.Let o be a point in Sεwhich has largest degree,and let its neighbours be p1,...,p k.By Lemma1,|∢p i op j|≥1,and by choice of Sε,|∢p i op j|=1 for any i=j.It follows that if we let x i= p i −1p i,then x1,...,x k are unit vectors with x i−x j >1for all distinct i,j.Therefore,k≤H s(B).If we now letε=1/n for sufficiently large n,we obtain a sequence of MSTs,each with maximum degree bounded above by H s(B).Since there are onlyfinitely many trees on afinite set of points,there is a subsequence with the same tree structure.This subsequence converges to a tree on S which,by continuity of the norm,is an MST of S.We have found an MST T of S with∆(T)≤H s(B). This shows that∆−(X d)≤H s(B),andfinishes the proof of the theorem. References[B¨o r04]K.B¨o r¨o czky,Jr.,Finite Packing and Covering,Cambridge University Press,Cambridge,2004.[Cie90] D.Cieslik,Knotengrade k¨u rzester B¨a ume in endlich-dimensionalen Banachr¨a umen,Rostock Math.Kolloq.39(1990),89–93.[Cie91] D.Cieslik,The1-Steiner-minimal-tree problem in Minkowski-spaces, Optimization22(1991),291–296.[DLR92]P.G.Doyle,garias,and D.Randall,Self-packing of centrally symmetric convex bodies in R2,Discrete Comput.Geom.8(1992),171–189.[Gr¨u61] B.Gr¨u nbaum,On a conjecture of H.Hadwiger,Pacific J.Math.11 (1961),215–219.[Had57]H.Hadwiger,¨Uber Treffanzahlen bei translationsgleichen Eik¨o rpern, Arch.Math.8(1957),212–213.4[HVW90]J.-M.Ho,G.Vijayan,and C.K.Wong,New algorithms for the recti-linear Steiner tree problem,IEEE puter-Aided Design9(1990),185–193.[PV84] C.H.Papadimitriou and U.V.Varizani,On two geometric problems relating to the traveling salesman problem,J.Algorithms5(1984),231–246.[RS95]G.Robins and J.S.Salowe,Low-degree minimum spanning trees, Discrete Comput.Geom.14(1995),151–165.[Sim63]G. F.Simmons,Introduction to Topology and Modern Analysis, McGraw-Hill,New York,1963.[Swa99]K.J.Swanepoel,New lower bounds for the Hadwiger numbers ofℓp balls for p<2,Applied Mathematics Letters12(1999)57–60.5。