The Asymptotic Capacity of Multi-Dimensional Runlength-Limited Constraints and Independent Sets in Hypergraphs Erik Ordentlich, Ron M. Roth1 Information Theory Research Group HP Laboratories Palo Alto HPL-2002-348 December 17th , 2002* E-mail: eord@hpl.hp.com, ronny@cs.technion.ac.il regular graphs, Hamming graphs, linear hypergraphs, multi-dimensional constraints, runlength- limited constraints Let C(n,d) be the Shannon capacity of the n-dimensional (d,Τ)runlength- limited (RLL) constraint. Denote by I(n,q) the number of independent sets in the Hamming graph with vertices consisting of all n-tuples over an alphabet of size q and edges connecting pairs of vertices with Hamming distance 1. We show that limn ∆ Τ C(n,d) = limn ∆ Τ (d+1) -n log2 I (n,d+1)=1/(d +1). Our method also leads to an improvement of a previous bound by Alon on the number of independent sets in regular graphs and to a generalization of this bound to a family of hypergraphs, of which the Hamming graphs can be thought of as a special case. * Internal Accession Date Only 1 Computer Science Department, Technion, Haifa, 32000, Israel Copyright Hewlett-Packard Company 2002 Approved for External Publication ! " # " $%"" & ' ( # ) '' ! " ¾ " ! " # $ % & & & ' & ! " ! " # £ !"# !$ % & $ !% ! % & ' !! ! ( )! % & * !! ( + ,-.$ ,/.% & ! *0 % $ % /1.% ,$ (% ( $ ( ,/.% 2% 13435/4 ( 13435/5 ,2.$ ,5.$ ,2.% -% 1((1 2 1(/5 ,5.% 1% # ,-.$ ,/.% & ! 6 # # # # % & !$ ! !! ($ ! # % 7 ! ! !% 7 ! !! ! )! $ # # ! 6$ ! # $ ! % ! ! % ! $ ! $ ! ! $ $ 0 ( (% $ Æ $ %%$ Æ ! % 8 ! Æ % 8 ! 9 6 96 ! % 8 ! % & % : ! ! !! ; ! % & * ; % < ! 6 # ! # % & % &$ # ) # % ! $ $ % = ! ; ! ( > % & ) ! $ ! ! ( ( ! * ; !% & ( ? '>* ,4. ,.$ ( ( ( % < ( ( ($ % & ! $ 8 ,.$ ? ,1.% $ ,. ! ( # 2 ( ( $ !! % & ,1. ! ! ( 0 # # # ( 0 # # # (% & 2 ! % * (% =! ! ( 2 - ! ,(.% ! ( % '!! $ % # 2 ' # ! # $ ! % # 7 2 % ( # - @ $ - !A! ! ! A ! ,.$ ,1.% &$ % B & (% (%2 & (%- $ ! ! ,(.% $ $ ! $ ! $ 0 (% ! A! $ $ 0 Æ % ' $ $ % 8 ! ! !$ ! ! ! % < ! ! % # - & & (%- '! 2% ; $ $ ! !% ;!$ & (% & (%- $ $ % & (%2 (% & ! ! ! ! $ $ '! 2% < '! - > & (%- ! % C $ ! %%$ !! ! $ $ 0 ( ! !$ $ 0 D 1 = ($ $ $ ( / 96 % ! 1% % E E Æ # 4 $ ) ! ! % & 1 Æ & ! ! % & & (%- ! 4 ( ! ! 4 % & * $ ! $ ! * E 4 % & ! ! ! % '! > $ $ $ !! E$ ! % Æ 3 % ! A! ! " % 0 % & + $ ! ! B ! ! !% $ % ! ! ! ! ! % '! ! '! ! ,3. $ A! ! ! ! % 8$ ! $ > % &$ $ %&¾ Æ ' ( ) * $# + %%, % $ - ) # . $ $ % %/ ) ) %/ $ $ )%/ $% * / # / 7 $ E Æ $ ! E E% : 3% % # 2 ) % & ! ! $ % B $ $ $ % $ 2 % ( # # ! $ ! % & ! $ ¼ ¼ ! % & # # # 5 5 ! $ ! ! F 2%2$ % 4 E ) 3% $ * E ! + ! $ % D ! E % &$ # ( $ ! $ % '! ! #$ % &$ 2%$ )! F 2%-% ;!$ # # 2 # 2 /% <! # ( 2 # # # # # # (# # # (# # - 1 / 4 - ! ! $ 1 ! ( 2 F 2%2$ / ! % & A 4% & ! % 3 < !$ > & (%- ! % C $ ! Æ Æ Æ % ( ! Æ & $ ! ! % 2%( % Æ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