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Graphs with few cliques

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is a clique that is not properly contained in another clique. One can regard a clique as a cluster of vertices, since they are by definition all connected to each other by an edge. The concept of clusters is ubiquitous in
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Brimkov, V. E., Junosza-Szaniawski, K., Kafer, S., Kratochvíl, J., Pergel, M., Rzążewski, P., et al. (2018). Homothetic polygons and beyond: Maximal cliques in intersection graphs.
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Eppstein, D., Löffler, M., & Strash, D. (2010). Listing All Maximal Cliques in Sparse Graphs in Near-Optimal Time. In O. Cheong, K.-Y. Chwa, & K. Park (Eds.),
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Graph theory, combinatorics, and algorithms: proceedings of the Seventh Quadrennial International Conference on the Theory and Applications of Graphs
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computational problems are solvable in polynomial time on such classes of graphs, making graphs with few cliques of interest in computational
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Fox, J., Roughgarden, T., Seshadhri, C., Wei, F., & Wein, N. (2020). Finding Cliques in Social Networks: A New Distribution-Free Model.
432:, after Moon & Moser showed in 1965 that this graph has the largest number of maximal cliques among all graphs on 502:
vertices has as many maximal cliques as edges, since it contains no triangles by definition. Any tree has exactly
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Gavril, F. (1974). The intersection graphs of subtrees in trees are exactly the chordal graphs.
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edges, and therefore that number of maximal cliques. So the class of trees has few cliques.
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Rosgen, B., & Stewart, L. (2007). Complexity results on graphs with few cliques.
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Prisner, E. (1995). Graphs with Few Cliques. In Y. Alavi & A. Schwenk (Eds.),
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maximal cliques, so the class of graphs with bounded boxicity has few cliques.
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Spinrad, J. P. (2003). Intersection and containment representations. In
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Wood, D. R. (2007). On the Maximum Number of Cliques in a Graph.
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Mathematical foundations of computational engineering: a handbook
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than any polynomial function. This graph is sometimes called the
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maximal cliques, so the class of planar graphs has few cliques.
1283:(pp. 31–53). Providence, R.I: American Mathematical Society. 1202:
Moon, J. W., & Moser, L. (1965). On cliques in graphs.
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of maximal cliques. In particular, this graph has exactly
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Graham, R. L., Knuth, D. E., & Patashnik, O. (1994).
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Concrete mathematics: a foundation for computer science
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Discrete Mathematics & Theoretical Computer Science
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maximal cliques, so chordal graphs have few cliques.
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If for every 32:if every member of the class has a 13: 1212:https://doi.org/10.1007/BF02760024 1177:https://doi.org/10.1137/18M1210459 1157:https://doi.org/10.46298/dmtcs.387 14: 1351: 1121: 288:class of graphs with few cliques. 1302: 1286: 1280:Efficient graph representations 837:{\displaystyle d\equiv 0\mod 3} 825: 417:{\displaystyle n\equiv 0\mod 3} 405: 1271: 1251: 1231: 1228:. Berlin ; New York: Springer. 1216: 1196: 1181: 1161: 1141: 778: 766: 700: 687: 337: 311: 253: 250: 244: 238: 195: 189: 1: 1204:Israel Journal of Mathematics 1155:(Graph and Algorithms), 387. 1115: 84:, such as on the analysis of 62: 1310:Discrete Applied Mathematics 179:, there exists a polynomial 7: 292: 10: 1356: 1294:Algorithms and Computation 1169:SIAM Journal on Computing 1051:, which is polynomial in 869:{\displaystyle n\geq d+3} 809:maximal cliques whenever 802:{\textstyle (n-d)3^{d/3}} 71:of a graph is a complete 1259:Graphs and Combinatorics 706:{\displaystyle O(n^{b})} 52:, and other branches of 382:{\displaystyle 3^{n/3}} 259:{\displaystyle O(f(n))} 92:on graphs or networks. 1105: 1085: 1065: 1045: 991: 968: 940: 917: 893: 870: 838: 803: 753: 730: 707: 671: 648: 625: 596: 569: 549: 522: 496: 476: 446: 426:asymptotically greater 418: 383: 344: 280: 266:maximal cliques, then 260: 222: 202: 173: 153: 129: 109: 1106: 1086: 1066: 1046: 992: 969: 941: 918: 894: 871: 839: 804: 754: 731: 708: 672: 649: 626: 624:{\displaystyle 8n-16} 602:vertices has at most 597: 570: 555:vertices has at most 550: 523: 497: 477: 447: 419: 389:maximal cliques when 384: 345: 281: 261: 223: 203: 174: 154: 130: 110: 1340:Discrete mathematics 1095: 1075: 1055: 1001: 981: 958: 930: 907: 883: 848: 813: 763: 743: 720: 681: 661: 638: 606: 586: 559: 539: 506: 486: 466: 436: 393: 358: 305: 270: 232: 212: 201:{\displaystyle f(n)} 183: 163: 143: 119: 99: 736:-vertex graph with 654:-vertex graph with 521:{\displaystyle n-1} 54:applied mathematics 1101: 1081: 1061: 1041: 987: 964: 936: 913: 901:intersection graph 889: 866: 834: 799: 749: 726: 703: 667: 644: 621: 592: 565: 545: 518: 492: 472: 442: 414: 379: 352:exponential number 340: 276: 256: 218: 198: 169: 149: 125: 105: 40:Certain generally 1104:{\displaystyle k} 1084:{\displaystyle d} 1064:{\displaystyle n} 990:{\displaystyle G} 967:{\displaystyle k} 939:{\displaystyle d} 916:{\displaystyle n} 892:{\displaystyle G} 752:{\displaystyle d} 729:{\displaystyle n} 670:{\displaystyle b} 647:{\displaystyle n} 595:{\displaystyle n} 568:{\displaystyle n} 548:{\displaystyle n} 495:{\displaystyle n} 475:{\displaystyle T} 456:have few cliques. 445:{\displaystyle n} 279:{\displaystyle X} 221:{\displaystyle G} 172:{\displaystyle X} 152:{\displaystyle G} 128:{\displaystyle n} 108:{\displaystyle X} 34:polynomial number 1347: 1320: 1306: 1300: 1290: 1284: 1275: 1269: 1255: 1249: 1235: 1229: 1220: 1214: 1200: 1194: 1185: 1179: 1165: 1159: 1145: 1139: 1130: 1110: 1108: 1107: 1102: 1090: 1088: 1087: 1082: 1070: 1068: 1067: 1062: 1050: 1048: 1047: 1042: 1040: 1036: 1035: 1034: 1033: 996: 994: 993: 988: 973: 971: 970: 965: 954:are parallel to 945: 943: 942: 937: 924:convex polytopes 922: 920: 919: 914: 898: 896: 895: 890: 875: 873: 872: 867: 843: 841: 840: 835: 808: 806: 805: 800: 798: 797: 793: 758: 756: 755: 750: 735: 733: 732: 727: 712: 710: 709: 704: 699: 698: 676: 674: 673: 668: 653: 651: 650: 645: 630: 628: 627: 622: 601: 599: 598: 593: 574: 572: 571: 566: 554: 552: 551: 546: 527: 525: 524: 519: 501: 499: 498: 493: 481: 479: 478: 473: 451: 449: 448: 443: 430:Moon-Moser graph 423: 421: 420: 415: 388: 386: 385: 380: 378: 377: 373: 349: 347: 346: 341: 330: 286:is said to be a 285: 283: 282: 277: 265: 263: 262: 257: 227: 225: 224: 219: 207: 205: 204: 199: 178: 176: 175: 170: 158: 156: 155: 150: 134: 132: 131: 126: 114: 112: 111: 106: 50:network analysis 38:maximal cliques. 28:is said to have 1355: 1354: 1350: 1349: 1348: 1346: 1345: 1344: 1325: 1324: 1323: 1307: 1303: 1291: 1287: 1276: 1272: 1256: 1252: 1236: 1232: 1221: 1217: 1201: 1197: 1186: 1182: 1166: 1162: 1146: 1142: 1131: 1122: 1118: 1096: 1093: 1092: 1076: 1073: 1072: 1056: 1053: 1052: 1023: 1019: 1015: 1011: 1007: 1002: 999: 998: 982: 979: 978: 959: 956: 955: 948:Euclidean space 931: 928: 927: 908: 905: 904: 884: 881: 880: 849: 846: 845: 814: 811: 810: 789: 785: 781: 764: 761: 760: 744: 741: 740: 721: 718: 717: 694: 690: 682: 679: 678: 662: 659: 658: 639: 636: 635: 607: 604: 603: 587: 584: 583: 560: 557: 556: 540: 537: 536: 507: 504: 503: 487: 484: 483: 467: 464: 463: 437: 434: 433: 394: 391: 390: 369: 365: 361: 359: 356: 355: 326: 306: 303: 302: 295: 271: 268: 267: 233: 230: 229: 213: 210: 209: 184: 181: 180: 164: 161: 160: 144: 141: 140: 120: 117: 116: 100: 97: 96: 86:social networks 65: 12: 11: 5: 1353: 1343: 1342: 1337: 1322: 1321: 1301: 1285: 1270: 1265:(3), 337–352. 1250: 1230: 1215: 1195: 1180: 1175:(2), 448–464. 1160: 1140: 1119: 1117: 1114: 1113: 1112: 1100: 1080: 1060: 1039: 1032: 1029: 1026: 1022: 1018: 1014: 1010: 1006: 986: 963: 935: 912: 888: 877: 865: 862: 859: 856: 853: 833: 828: 824: 821: 818: 796: 792: 788: 784: 780: 777: 774: 771: 768: 748: 725: 714: 702: 697: 693: 689: 686: 666: 643: 632: 620: 617: 614: 611: 591: 576: 564: 544: 529: 517: 514: 511: 491: 471: 457: 441: 413: 408: 404: 401: 398: 376: 372: 368: 364: 339: 336: 333: 329: 325: 322: 319: 316: 313: 310: 294: 291: 275: 255: 252: 249: 246: 243: 240: 237: 217: 197: 194: 191: 188: 168: 148: 124: 104: 95:Formally, let 77:maximal clique 64: 61: 9: 6: 4: 3: 2: 1352: 1341: 1338: 1336: 1333: 1332: 1330: 1319: 1315: 1311: 1305: 1299: 1295: 1289: 1282: 1281: 1274: 1268: 1264: 1260: 1254: 1248: 1244: 1240: 1234: 1227: 1226: 1219: 1213: 1209: 1205: 1199: 1192: 1191: 1184: 1178: 1174: 1170: 1164: 1158: 1154: 1150: 1144: 1137: 1136: 1129: 1127: 1125: 1120: 1098: 1078: 1058: 1037: 1030: 1027: 1024: 1020: 1016: 1012: 1008: 1004: 984: 976: 961: 953: 949: 946:-dimensional 933: 925: 910: 902: 886: 878: 863: 860: 857: 854: 851: 831: 826: 822: 819: 816: 794: 790: 786: 782: 775: 772: 769: 746: 739: 723: 715: 695: 691: 684: 664: 657: 641: 633: 618: 615: 612: 609: 589: 581: 577: 562: 542: 534: 533:chordal graph 530: 515: 512: 509: 489: 469: 462: 458: 455: 439: 431: 427: 411: 406: 402: 399: 396: 374: 370: 366: 362: 353: 331: 327: 323: 317: 314: 308: 301: 297: 296: 290: 289: 273: 247: 241: 235: 215: 192: 186: 166: 146: 138: 122: 102: 93: 91: 87: 83: 82:data analysis 78: 74: 70: 60: 59: 55: 51: 47: 43: 39: 35: 31: 27: 23: 19: 1335:Graph theory 1313: 1309: 1304: 1293: 1288: 1278: 1273: 1262: 1258: 1253: 1245:(1), 47–56. 1242: 1238: 1233: 1223: 1218: 1210:(1), 23–28. 1207: 1203: 1198: 1188: 1183: 1172: 1168: 1163: 1153:Vol. 9 no. 1 1152: 1148: 1143: 1133: 759:has at most 580:planar graph 453: 429: 287: 94: 76: 68: 66: 46:graph theory 29: 18:graph theory 15: 1316:, 263–277. 975:hyperplanes 424:, which is 300:Turán graph 30:few cliques 1329:Categories 1116:References 1071:for fixed 738:degeneracy 208:such that 90:algorithms 75:, while a 63:Definition 855:≥ 820:≡ 773:− 616:− 513:− 400:≡ 335:⌉ 321:⌈ 58:clusters. 656:boxicity 293:Examples 73:subgraph 350:has an 42:NP-hard 952:facets 950:whose 899:be an 139:graph 137:vertex 69:clique 26:graphs 22:class 1091:and 879:Let 844:and 716:Any 677:has 634:Any 578:Any 461:tree 298:The 228:has 20:, a 1314:247 997:is 926:in 903:of 827:mod 582:on 535:on 482:on 454:not 407:mod 159:in 36:of 24:of 16:In 1331:: 1312:, 1263:23 1261:, 1243:16 1241:, 1206:, 1173:49 1171:, 1151:, 1123:^ 619:16 531:A 459:A 67:A 48:, 1208:3 1099:k 1079:d 1059:n 1038:) 1031:1 1028:+ 1025:d 1021:k 1017:d 1013:n 1009:( 1005:O 985:G 962:k 934:d 911:n 887:G 864:3 861:+ 858:d 852:n 832:3 823:0 817:d 795:3 791:/ 787:d 783:3 779:) 776:d 770:n 767:( 747:d 724:n 701:) 696:b 692:n 688:( 685:O 665:b 642:n 613:n 610:8 590:n 563:n 543:n 516:1 510:n 490:n 470:T 440:n 412:3 403:0 397:n 375:3 371:/ 367:n 363:3 338:) 332:3 328:/ 324:n 318:, 315:n 312:( 309:T 274:X 254:) 251:) 248:n 245:( 242:f 239:( 236:O 216:G 196:) 193:n 190:( 187:f 167:X 147:G 135:- 123:n 103:X

Index

graph theory
class
graphs
polynomial number
maximal cliques.
NP-hard
graph theory
network analysis
applied mathematics
clusters.
subgraph
data analysis
social networks
algorithms
vertex
Turán graph
exponential number
asymptotically greater
tree
chordal graph
planar graph
boxicity
degeneracy
intersection graph
convex polytopes
Euclidean space
facets
hyperplanes

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