Damage spreading in the 'sandpile' model of SOC
ABSTRACT We have studied the damage spreading (defined in the text) in the 'sandpile'
model of self organised criticality. We have studied the variations of the
critical time (defined in the text) and the total number of sites damaged at
critical time as a function of system size. Both shows the power law variation.
- 4 r1000 10000 100000 1e+06 10100 L 1000 τ 3 3 333333 3 3 3 Fig. 1. Variation of critical time (τ) with system size L. 100 1000 10000 100000 10100 L 1000 3 3 333333 3 3 3 + + ++++++ + + + Fig. 2. Variations of Mτ(3) and Mtot(+) with system size L..
arXiv:1101.3047v1 [cond-mat.stat-mech] 16 Jan 2011
Damage spreading in the ’sandpile’
model of SOC
Saha Institute of Nuclear Physics
1/AF Bidhannagar, Calcutta-700064, India
Abstract: We have studied the damage spreading (defined in the text) in the ’sand-
pile’ model of self organised criticality. We have studied the variations of the critical
time (defined in the text) and the total number of sites damaged at critical time as
a function of system size. Both shows the power law variation.
Keywords: Sandpile model of SOC, Damage spreading
PACS Numbers: 05.50 +q
∗Present address:Department of Physics, Lady Brabourne College,
P-1/2 Suhrawardy Avenue, Calcutta-700017, India
The damage spreading [1-3] studies the dynamic behaviour of cooperative sys-
tems. The main idea of this problem is to study how a small perturbation, called a
damage, in a cooperative system changes with the evolution of time. This is studied
by observing the time evolution of the two copies of the system with slightly different
initial configuration under the same dynamics and measuring the damage by count-
ing the number of elements which are different in the two copies of the system. The
damage spreading has been studied exhaustively, in the Kauffman model  and the
spin systems [2,3].
In this paper, we have studied, by computer simulation, how damage spreads,
in the ’sandpile’ model, over the whole lattice during the course of time evolution.
’sandpile’ model  is a lattice automata model which describes the appearance of
long range spatio-temporal correlations observed in extended, dissipative dynamical
systems in nature. The essential feature of this model is the occurence of fractal
structure in space and ’1/f’ noise in time, which is so called self-organised criticality
(SOC) . Substantial developments have been made on the study of ’sandpile’
model. But all these studies have been made in the steady (SOC) state, reached by
II. The model and simulation
The lattice automata ’sandpile’ model  of SOC evolves to a stationary state in
a self-organised (having no tunable parameter) way. This state has no scale of length
and time, hence is called critical. Altogether the state is called self-organised critical
state. The description of the lattice automata model is as follows: At each site of this
lattice, a variable (automaton) z(i,j) is associated which can take positive integer
values. Starting from the initial condition (at every site z(i,j) = 0), the value of
z(i,j) is increased (so called addition of one ’sand’ particle) at a randomly chosen
site (i,j) of the lattice in steps of unity as,
z(i,j) = z(i,j) + 1.
When the value of z at any site reaches a maximum zm, its value decreases by four
units (i.e., it topples) and each of the four nearest neighbours gets one unit of z
(maintaining local conservation) as follows:
z(i,j) = z(i,j) − 4
z(i ± 1,j ± 1) = z(i ± 1,j ± 1) + 1 (1)
for z(i,j) ≥ zm. At the boundary sites z = 0 (dissipative; open boundary condition).
In this simulation, a square lattice of size L × L has been considered. The value
of zm = 4 here. It has been observed that, as the time goes on the average value
(¯ z) of z(i,j), over the space, increases and ultimately reaches a steady value (¯ zc)
characterising the SOC state.
We study here, by computer simulation, how a small perturbation spreads in time
in the ’sandplie’ model. We have considered a square lattice and allowed it to evolve
under the dynamics until the average value (¯ z) of z(i,j) reaches a steady value (¯ zc).
We also have considered a 2nd lattice, which is a replica of the 1st lattice. After
reaching the steady (SOC) state (characterised by the steady value of ¯ z) we have
perturbed suddenly one of the system (say the 1st lattice) by adding unity to the
automaton value at the central site of the lattice, i.e, z1(l/2,l/2) = z1(l/2,l/2) + 1 .
Then we allowed the two lattices to evolve in time by the specified dynamics in the
same way (i.e, by using the same sequence of random numbers). It will be observed
that both lattices (perturbed and unperturbed) give the same macroscopic behavior
(the same ¯ zcand same scale invariant (power law) distribution of the avalanches size).
But the microscopic details (the z(i,j) at any site i,j at any time) of the two lattices
are different. The differences in microscopic details of the two lattice are described
here in terms of the ”damaged sites”, i.e., the sites of the perturbed lattice which
are different from the unperturbed one. The damaged lattice is characterised by a
variable (say d(i,j)), which is zero if the two lattices have the same z (for any site i,j)
value and 1 otherwise. More precisely, d(i,j) = 0 if z1(i,j) = z2(i,j) and d(i,j) = 1
otherwise. The non-zero sites of the damaged lattice (i.e., d(i,j) = 1) indicates the
damage in this model.
It has been observed that, with the evolution of time, the damage (cloud formed
by the sites having d(i,j) = 1) spreads and touches any one of the boundary line of the
lattice at time τ (starting from the initial time when the central site of lattice 1 was
perturbed by adding unity). Here we study the spreading of damage by measuring
the following quantities:
(1) Minimum time (τ) taken by the damage to touch any one of the boundaries (upper
or lower) of the lattice.
(2) The number (Mτ) of damaged sites at τ-th instant.
(3) The total number (MTot) of sites damaged during the time τ, starting from the
initial time when the perturbation was added.
Fig.1 shows the variation of critical time (τ) with the sytem size L in the log scale
indicating the power law variation, following, τ ∼ Lawith a = 1.97. Fig.2 shows the
variations of Mτ, the number of sites damaged at critical time (τ) and Mtot, the total
number of sites damaged up to critical time with the syatem size L in the log scale,
indicating the power law variations, Mτ ∼ Lbwith b = 1.47. and Mtot∼ Lcwith
c = 1.66. Thus we see that τ, Mτ and Mtot, all these quantities follow a power law
variation with the system size. All these data have been obtained by sampling over
100 different seeds of random number generator for L = 30,40,···150 and over 10
samples for L = 200,300.
In the case of damage spreading in Ising model the spreading of damage is con-
trolled by tuning the temperature. But due to the absence of any tunable parameter
in the ’sandpile’ model it has been observed that in this case there is number spread-
ing transition contrast to the other cases of damage spreading (like Ising system etc).
There is a power law variation of critical time (τ) and Mτ, Mtotwith length as in the
other cases (though the exponents are different).
 A. Kauffman, J. Theor. Biol. 22, 437 (1969); See also B. Derrida and Y. Pomeau,
Europhys. Lett. 1, 45 (1986); B. Derrida and G. Weisbuch, J. Phys. (Paris) 47,
1297 (1986); B. Derrida and D. Stauffer, Europhys. Lett. 2, 739 (1986).
 N. Jan and L. de Arcangelis, in Annual Reviews of Computational Physics, Vol
1., Ed. D. Stauffer, World-Scientific, Singapore, (1994) 1.
 P. Grassberger, J. Stat. Phys. 79, 13 (1995).
 P. Bak, C. Tang and K. Wiesenfeld, Phys. Rev. Lett. 59 (1987) 381; Phys. Rev.
A. 38 (1988) 364.
Fig. 1. Variation of critical time (τ) with system size L.
Fig. 2. Variations of Mτ(3) and Mtot(+) with system size L.