The Complexity of Random Ordered Structures
Author(s) -
Joel Spencer,
Katherine St. John
Publication year - 2005
Publication title -
electronic notes in theoretical computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.242
H-Index - 60
ISSN - 1571-0661
DOI - 10.1016/j.entcs.2005.05.030
Subject(s) - random graph , combinatorics , mathematics , quantifier (linguistics) , discrete mathematics , order (exchange) , graph , computer science , finance , artificial intelligence , economics
We show that for random bit strings, Up(n), with probability, p=12, the first-order quantifier depth D(Up(n)) needed to distinguish non-isomorphic structures is Θ(lglgn), with high probability. Further, we show that, with high probability, for random ordered graphs, G≤,p(n) with edge probabiltiy p=12, D(G≤,p(n))=Θ(log∗n), contrasting with the results of random (non-ordered) graphs, Gp(n), by Kim et al. [J.H. Kim, O. Pikhurko, J. Spencer, O. Verbitsky, How complex are random graphs in first order logic? (2005), to appear in Random Structures and Algorithms] of D(Gp(n))=log1/pn+O(lglgn)
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom