Approximate Capacities of Two-Dimensional Codes by Spatial Mixing

We apply several state-of-the-art techniques developed in recent advances of counting algorithms and statistical physics to study the spatial mixing property of the two-dimensional codes arising from local hard (independent set) constraints, including: hard-square, hard-hexagon, read/write isolated memory (RWIM), and non-attacking kings (NAK). For these constraints, the strong spatial mixing would imply the existence of polynomial-time approximation scheme (PTAS) for computing the capacity. It was previously known for the hard-square constraint the existence of strong spatial mixing and PTAS. We show the existence of strong spatial mixing for hard-hexagon and RWIM constraints by establishing the strong spatial mixing along self-avoiding walks, and consequently we give PTAS for computing the capacities of these codes. We also show that for the NAK constraint, the strong spatial mixing does not hold along self-avoiding walks

Upper bounds on the growth rates of hard squares and related models via corner transfer matrices

We study the growth rate of the hard squares lattice gas, equivalent to the number of independent sets on the square lattice, and two related models - non-attacking kings and read-write isolated memory. We use an assortment of techniques from combinatorics, statistical mechanics and linear algebra to prove upper bounds on these growth rates. We start from Calkin and Wilf's transfer matrix eigenvalue bound, then bound that with the Collatz-Wielandt formula from linear algebra. To obtain an approximate eigenvector, we use an ansatz from Baxter's corner transfer matrix formalism, optimised with Nishino and Okunishi's corner transfer matrix renormalisation group method. This results in an upper bound algorithm which no longer requires exponential memory and so is much faster to calculate than a direct evaluation of the Calkin-Wilf bound. Furthermore, it is extremely parallelisable and so allows us to make dramatic improvements to the previous best known upper bounds. In all cases we reduce the gap between upper and lower bounds by 4-6 orders of magnitude.Comment: Also submitted to FPSAC 2015 conferenc

Upper bounds on the growth rates of hard squares and related models via corner transfer matrices

International audienceWe study the growth rate of the hard squares lattice gas, equivalent to the number of independent sets on the square lattice, and two related models — non-attacking kings and read-write isolated memory. We use an assortment of techniques from combinatorics, statistical mechanics and linear algebra to prove upper bounds on these growth rates. We start from Calkin and Wilf’s transfer matrix eigenvalue bound, then bound that with the Collatz-Wielandt formula from linear algebra. To obtain an approximate eigenvector, we use an ansatz from Baxter’s corner transfer matrix formalism, optimised with Nishino and Okunishi’s corner transfer matrix renormalisation group method. This results in an upper bound algorithm which no longer requires exponential memory and so is much faster to calculate than a direct evaluation of the Calkin-Wilf bound. Furthermore, it is extremely parallelisable and so allows us to make dramatic improvements to the previous best known upper bounds. In all cases we reduce the gap between upper and lower bounds by 4-6 orders of magnitude.Nous étudions le taux de croissance du système de particules dur sur un réseau carré. Ce taux est équivalent au nombre d’ensembles indépendants sur le réseau carré. Nous étudions également deux modèles qui lui sont reliés : les rois non-attaquants et la mémoire isolée d’écriture-réécriture. Nous utilisons techniques diverses issues de la combinatoire, de la mécanique statistique et de l’algèbre linéaire pour prouver des bornes supérieures sur ces taux de croissances. Nous partons de la borne de Calkin et Wilf sur les valeurs propres des matrices de transfert, que nous bornons à l’aide de la formule de Collatz-Wielandt issue de l’algèbre linéaire. Pour obtenir une valeur approchée d’un vecteur propre, nous utilisons un ansatz du formalisme de Baxter sur les matrices de transfert de coin, que nous optimisons avec la méthode de Nishino et Okunishi qui exploite ces matrices. Il en résulte un algorithme pour calculer la borne supérieure qui n’est plus exponentiel en mémoire et est ainsi beaucoup plus rapide qu’une évaluation directe de la borne de Calkin-Wilf. De plus, cet algorithme est extrêmement parallélisable et permet ainsi une nette amélioration des meilleurs bornes supérieures existantes. Dans tous les cas l’écart entre les bornes supérieures et inférieures s’en trouve réduit de 4 à 6 ordres de grandeur

Lonesum (0,1)-matrices and poly-Bernoulli numbers of negative index

This thesis shows that the number of (0,1)-matrices with n rows and k columns uniquely reconstructible from their row and column sums are the poly-Bernoulli numbers of negative index, B[subscript n superscript ( -k)] . Two proofs of this main theorem are presented giving a combinatorial bijection between two poly-Bernoulli formula found in the literature. Next, some connections to Fermat are proved showing that for a positive integer n and prime number p B[subscript n superscript ( -p) congruent 2 superscript n (mod p),] and that for all positive integers (x, y, z, n) greater than two there exist no solutions to the equation: B[subscript x superscript ( -n)] + B[subscript y superscript ( -n)] = B[subscript z superscript ( -n)]. In addition directed graphs with sum reconstructible adjacency matrices are surveyed, and enumerations of similar (0,1)-matrix sets are given as an appendix

New upper and lower bounds on the channel capacity of read/write isolated memory

In this paper we refine upper and lower bounds for the channel capacity of a serial, binary rewritable medium in which no consecutive locations may store '1's and no consecutive locations may be altered during a single rewriting pass. This problem was originally examined by Cohn [4] who proved that C, the channel capacity of the memory, in bits per symbol per rewrite, satisfies 0.50913...≤ C ≤ 0.56029.... In this paper we show to model the problem as a constrained two-dimensional binary matrix problem and then modify recent techniques for dealing with such matrices to derive improved bounds of 0.53500...≤ C ≤ 0.55209...