Statistical Mechanics Analysis of the Continuous Number Partitioning Problem

The number partitioning problem consists of partitioning a sequence of positive numbers ${a_1,a_2,..., a_N}$ into two disjoint sets, ${\cal A}$ and ${\cal B}$, such that the absolute value of the difference of the sums of $a_j$ over the two sets is minimized. We use statistical mechanics tools to study analytically the Linear Programming relaxation of this NP-complete integer programming. In particular, we calculate the probability distribution of the difference between the cardinalities of ${\cal A}$ and ${\cal B}$ and show that this difference is not self-averaging.Comment: 9 pages, 1 figur

On the structure pf genealogical trees in the presence of selection

We investigate through numerical simulations the effect of selection on two summary statistics for nucleotide variation in a sample of two genes from a population of N asexually reproducing haploid individuals. One is the mean time since two individuals had their most recent common ancestor ($\bar{T_s}$), and the other is the mean number of nucleotide differences between two genes in the sample ($\bar{d_s}$). In the case of diminishing epistasis, in which the deleterious effect of a new mutation is attenuated, we find that the scale of $\bar{d_s}$ with the population size depends on the mutation rate, leading then to the onset of a sharp threshold phenomenon as N becomes large.Comment: 6 page

Phase transition between synchronous and asynchronous updating algorithms

We update a one-dimensional chain of Ising spins of length $L$ with algorithms which are parameterized by the probability $p$ for a certain site to get updated in one time step. The result of the update event itself is determined by the energy change due to the local change in the configuration. In this way we interpolate between the Metropolis algorithm at zero temperature for $p$ of the order of 1/L and for large $L$, and a synchronous deterministic updating procedure for $p=1$. As function of $p$ we observe a phase transition between the stationary states to which the algorithm drives the system. These are non-absorbing stationary states with antiferromagnetic domains for $p>p_c$, and absorbing states with ferromagnetic domains for $p\leq p_c$. This means that above this transition the stationary states have lost any remnants to the ferromagnetic Ising interaction. A measurement of the critical exponents shows that this transition belongs to the universality class of parity conservation.Comment: 5 pages, 3 figure

Escaping from cycles through a glass transition

A random walk is performed over a disordered media composed of $N$ sites random and uniformly distributed inside a $d$-dimensional hypercube. The walker cannot remain in the same site and hops to one of its $n$ neighboring sites with a transition probability that depends on the distance $D$ between sites according to a cost function $E(D)$. The stochasticity level is parametrized by a formal temperature $T$. In the case $T = 0$, the walk is deterministic and ergodicity is broken: the phase space is divided in a ${\cal O}(N)$ number of attractor basins of two-cycles that trap the walker. For $d = 1$, analytic results indicate the existence of a glass transition at $T_1 = 1/2$ as $N \to \infty$. Below $T_1$, the average trapping time in two-cycles diverges and out-of-equilibrium behavior appears. Similar glass transitions occur in higher dimensions choosing a proper cost function. We also present some results for the statistics of distances for Poisson spatial point processes.Comment: 11 pages, 4 figure

Generalization in a Hopfield network

The performance of a Hopfield network in learning an extensive number of concepts having access only to a finite supply of typical data which exemplify the concepts is studied. The minimal number of examples which must be taught to the network in order it starts to create representations for the concepts is calculated analitically. It is shown that the mixture states play a crucial role in the creation of these representations

Landscape statistics of the binary perceptron

The landscape of the binary perceptron is studied by Simulated Annealing, exhaustive search and performing random walks on the landscape. We find that the number of local minima increases exponentially with the number of bonds, becoming deeper in the vicinity of a global minimum, but more and more shallow as we move away from it. The random walker detects a simple dependence on the size of the mapping, the architecture introducing a nontrivial dependence on the number of steps

Information processing in synchronous neural networks

The phase diagram of Little's model is determined when the number of stored patterns p grows as ρ = αN, where N is the number of neurons. We duplicate phase space in order to accomodate cycles of length two within the framework of equilibrium statistical mechanics. Using the replica symmetry scheme we determine the phase diagram including a parameter J0 able to control the occurrence of cycles. The second order transition between the paramagnetic and ferromagnetic phase becomes first order at a tricritical point. The retrieval region is some what larger than in Hopfield's model. We also find a low temperature paramagnetic phase with unphysical properties.Nous obtenons le diagramme de phase du modèle de Little quand le nombre p d'échantillons mémorisés croit comme ρ = αN, où N est le nombre de neurones. Nous dédoublons l'espace de phase de façon à accommoder des cycles de longueur deux dans le cadre de la mécanique statistique. Utilisant la méthode des répliques, nous déterminons le diagramme de phase incluant un paramètre J0 pour contrôler l'apparition des cycles. La transition de phase entre les phases para- et ferromagnétiques passe du second ordre au premier ordre au point tricritique. La région de recouvrement de l'information est un peu plus grande que dans le modèle de Hopfield. Nous trouvons également une phase paramagnétique à basse température qui a des propriétés physiquement inacceptables