9,386 research outputs found
Efficient algorithm to study interconnected networks
Interconnected networks have been shown to be much more vulnerable to random
and targeted failures than isolated ones, raising several interesting questions
regarding the identification and mitigation of their risk. The paradigm to
address these questions is the percolation model, where the resilience of the
system is quantified by the dependence of the size of the largest cluster on
the number of failures. Numerically, the major challenge is the identification
of this cluster and the calculation of its size. Here, we propose an efficient
algorithm to tackle this problem. We show that the algorithm scales as O(N log
N), where N is the number of nodes in the network, a significant improvement
compared to O(N^2) for a greedy algorithm, what permits studying much larger
networks. Our new strategy can be applied to any network topology and
distribution of interdependencies, as well as any sequence of failures.Comment: 5 pages, 6 figure
Effect of particle polydispersity on the irreversible adsorption of fine particles on patterned substrates
We performed extensive Monte Carlo simulations of the irreversible adsorption
of polydispersed disks inside the cells of a patterned substrate. The model
captures relevant features of the irreversible adsorption of spherical
colloidal particles on patterned substrates. The pattern consists of (equal)
square cells, where adsorption can take place, centered at the vertices of a
square lattice. Two independent, dimensionless parameters are required to
control the geometry of the pattern, namely, the cell size and cell-cell
distance, measured in terms of the average particle diameter. However, to
describe the phase diagram, two additional dimensionless parameters, the
minimum and maximum particle radii are also required. We find that the
transition between any two adjacent regions of the phase diagram solely depends
on the largest and smallest particle sizes, but not on the shape of the
distribution function of the radii. We consider size dispersions up-to 20% of
the average radius using a physically motivated truncated Gaussian-size
distribution, and focus on the regime where adsorbing particles do not interact
with those previously adsorbed on neighboring cells to characterize the jammed
state structure. The study generalizes previous exact relations on monodisperse
particles to account for size dispersion. Due to the presence of the pattern,
the coverage shows a non-monotonic dependence on the cell size. The pattern
also affects the radius of adsorbed particles, where one observes preferential
adsorption of smaller radii particularly at high polydispersity.Comment: 9 pages, 5 figure
Gaussian model of explosive percolation in three and higher dimensions
The Gaussian model of discontinuous percolation, recently introduced by
Ara\'ujo and Herrmann [Phys. Rev. Lett., 105, 035701 (2010)], is numerically
investigated in three dimensions, disclosing a discontinuous transition. For
the simple-cubic lattice, in the thermodynamic limit, we report a finite jump
of the order parameter, . The largest cluster at the
threshold is compact, but its external perimeter is fractal with fractal
dimension . The study is extended to hypercubic lattices up
to six dimensions and to the mean-field limit (infinite dimension). We find
that, in all considered dimensions, the percolation transition is
discontinuous. The value of the jump in the order parameter, the maximum of the
second moment, and the percolation threshold are analyzed, revealing
interesting features of the transition and corroborating its discontinuous
nature in all considered dimensions. We also show that the fractal dimension of
the external perimeter, for any dimension, is consistent with the one from
bridge percolation and establish a lower bound for the percolation threshold of
discontinuous models with finite number of clusters at the threshold
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