Critical dimensions for random walks on random-walk chains
Savely Rabinovich, H. Eduardo Roman, Shlomo Havlin, and Armin Bunde
Minerva Center and Department of Physics, Bar-Ilan University, 52900 Ramat Gan, Israel
arXiv:cond-mat/9604167v1 29 Apr 1996
and
Institut für Theoretische Physik, Universität Gießen, Heinrich-Buff-Ring 16, D-35392 Gießen,
Germany
(received August 23, 2019)
Abstract
The probability distribution of random walks on linear structures generated
by random walks in d-dimensional space, Pd (r, t), is analytically studied for
the case ξ ≡ r/t1/4 ≪ 1. It is shown to obey the scaling form Pd (r, t) =
ρ(r)t−1/2 ξ −2 fd (ξ), where ρ(r) ∼ r 2−d is the density of the chain. Expanding
fd (ξ) in powers of ξ, we find that there exists an infinite hierarchy of critical
dimensions, dc = 2, 6, 10, . . ., each one characterized by a logarithmic correction in fd (ξ). Namely, for d = 2, f2 (ξ) ≃ a2 ξ 2 ln ξ + b2 ξ 2 ; for 3 ≤ d ≤ 5,
fd (ξ) ≃ ad ξ 2 + bd ξ d ; for d = 6, f6 (ξ) ≃ a6 ξ 2 + b6 ξ 6 ln ξ; for 7 ≤ d ≤ 9,
fd (ξ) ≃ ad ξ 2 + bd ξ 6 + cd ξ d ; for d = 10, f10 (ξ) ≃ a10 ξ 2 + b10 ξ 6 + c10 ξ 10 ln ξ, etc.
In particular, for d = 2, this implies that the temporal dependence of the probability density of being close to the origin Q2 (r, t) ≡ P2 (r, t)/ρ(r) ≃ t−1/2 ln t.
Pacs: 5.40.+j, 05.60.+w, 66.30.-h
1
I. INTRODUCTION
Random fractals represent useful models for a variety of disordered systems found in
Nature. In addition to their structural properties, fractals have attracted much attention in
recent years because of their interesting transport properties [1–4].
Of particular interest is the question of how the probability density of random walks,
Pd (r, t), is changed on fractal structures with respect to its Gaussian form valid on regular
d−dimensional systems, Pd (r, t) ∼ t−d/2 exp(−const × η 2 ), where η = r/t1/2 . The form of
Pd (r, t) on fractals has been extensively studied in the asymptotic limit ξ = r/t1/dw ≫ 1
[2,5–12], where dw is the anomalous diffusion exponent characterizing the time behavior of
the random walks, hr 2 (t)i ∼ t2/dw . As a result of these investigations, it is now generally
accepted that Pd (r, t) displays a stretched Gaussian form
Pd (r, t) ∼ ρ(r)t−ds /2 exp(−const × ξ u ),
ξ ≫ 1,
(1)
where ρ(r) ∼ r df −d is the density of the fractal structure, df is the fractal dimension,
ds = 2df /dw is the spectral dimension [1], u = dw /(dw − 1), and is normalized according
to
R
dr r d−1 Pd (r, t) = 1. However, much less is known about the behavior of Pd (r, t) in the
opposite limit when ξ approaches zero.
In this paper we concentrate on diffusion in linear random fractal structures generated
by random walks (random-walk chains, RWC) in d-dimensional systems, where Pd (r, t) can
be obtained exactly. Recently, using numerical simulations, it has been suggested that for
such linear fractals [13],
Qd (r, t)/Qd (0, t) ∼ (1 − const × ξ d−2 ),
ξ → 0,
(2)
for all dimensions d, where Qd (r, t) = ρ(r)−1 Pd (r, t) is normalized on the fractal chain,
i.e.,
R
dr r df −1 Qd (r, t) = 1, with df = 2, dw = 4 for RWC, ξ = r/t1/4 and Qd (0, t) is the
probability density to return to the origin.
In the following, we derive an exact expansion for Pd (r, t) in the limit of ξ → 0. Surprisingly, Pd (r, t) displays an extremely rich behavior as a function of both ξ and dimensionality
2
d. We show, among other results, that Eq. (2) can only be valid for 3 ≤ d ≤ 5, and
Pd (r, t) ∼ ρ(r)t−1/2 (1 − const × ξ 4 ),
for d ≥ 7.
(3)
Moreover, we find that the small-ξ expansion of Pd (r, t) is characterized by a hierarchy of critical dimensions, dc = 2, 6, 10, 14, . . ., where logarithmic corrections of the form ξ dc −2 log(1/ξ)
occur. In particular, for d = 2 we obtain P2 (r, t) ≃ 2ρ(r)t−1/2 ln(t1/4 /r).
II. RANDOM WALKS ON RANDOM-WALK CHAINS
We consider linear structures generated by random walks in d-dimensional systems. Such
structures are fractals with fractal dimension df = 2, independently of d. To study diffusion
of particles along such linear chains, we assume that the diffusing particles (random walkers) can move only along the structure (path) which has been created sequentially by the
generating walks. Thus, although the structure can intersect itself in space, the walkers see
just a linear path. We denote such paths as random-walk chains (RWC).
Along the linear path, the probability density of random walkers, at chemical distance ℓ
along the RWC from their starting point after time t, p(ℓ, t), subject to the initial condition
p(ℓ, 0) = δ(ℓ), approaches the well-known Gaussian distribution
2
ℓ2
p(ℓ, t) =
,
exp
−
(2πt)1/2
2t
!
normalized according to
R∞
0
(4)
dℓ p(ℓ, t) = 1. Thus, diffusion along the chain (i.e., ℓ-space) is
normal and hℓ2 i = t. On the contrary, in Euclidean r-space diffusion is anomalous with
dw = 2df = 4 (see, e.g., [2]).
To obtain the behavior of the probability density in r-space, averaged over all RWC
configurations, Pd (r, t), we note that it is related to p(ℓ, t) by
Pd (r, t) =
and is normalized according to
the RWC fractal, i.e.,
R∞
0
R
Z
0
∞
dℓ Φd (r, ℓ)p(ℓ, t)
(5)
dd r Pd (r, t) = 1. Another possibility is a normalization on
dr r df −1 Qd (r, t) = 1. Both distributions are simply related to each
other by Pd (r, t) = ρ(r)Qd (r, t).
3
In Eq. (5), Φd (r, ℓ) represents the probability for a site r to belong to a RWC at distance
ℓ from the origin along the chain. The chemical distance ℓ plays the role of the time variable
in Eq. (4), and one can immediately write
Φd (r, ℓ) = Ad
1
2πℓ
where Ad is a normalization factor such that
1
Pd (r, t) =
2π
d/2
2Ad
(2πt)1/2
Z
∞
0
r2
exp −
2ℓ
!
(6)
dd r Φd (r, ℓ) = 1. Therefore, by inserting (4)
R
and (6) in (5) we infer [4,14]
d/2
ℓ2
r2
exp −
.
dℓ ℓ−d/2 exp −
2ℓ
2t
!
!
(7)
Now, the elementary transformation x = ℓ/r 2 brings (7) to the form
Pd (r, t) = 2Ad (2π)−(d+1)/2 r −d fd (ξ),
(8)
where the scaling function fd (ξ) is defined by
fd (ξ) = ξ
2
Z
∞
0
−d/2
dx x
1
1
exp − ξ 4 x2 +
2
x
(9)
for the scaling variable ξ ≡ r/t1/4 . If the RWC normalization is chosen, the distribution
Qd (r, t) = ρ−1 (r)Pd (r, t) ∼
= t−1/2 f˜d (ξ), where f˜d (ξ) = ξ −2 fd (ξ).
To deal now with the evaluation of fd (ξ) when ξ → 0, it is convenient to rewrite the
integrand exponent as
1
1
exp − ξ 4 x2 +
2
x
1
1
= exp − ξ 4x2 + 2
2
x
1
1
1−
exp −
2x
x
and expand the second exponential factor in Taylor series. The remaining integrals can be
solved exactly (see, e.g. [15]), and one arrives at the following expression for (9)
∞
X
1
1
−
fd (ξ) = ξ
2
n=0 n!
2
n X
n
(−1)
k=0
k
!
n d/2−1+n+k
ξ
K 1 (d/2−1+n+k) (ξ 2 ),
2
k
(10)
where Kν is the modified Bessel function of order ν.
Let us consider Eq. (10) in some particular cases of interest. The results for spatial
dimensions d ≤ 7 are summarized in Table I. All the coefficients were calculated numerically
4
by computing the double sums explicitly. In some cases they are available in analytic form,
but we include their numerical values to make the table uniform.
However, besides the coefficients, the main properties of these expansions can be obtained
readily as follows. The key parameter is s = 21 ( d2 − 1). The corresponding values of d =
2(2s + 1) for integer s should be referred to as critical dimensions, dc = 2, 6, 10, . . .. Each
order in the expansion has its own critical dimension. The leading term has dc = 2, the
first correction term has dc = 6, the second correction term has dc = 10, etc. This has to
do with the functional form of fd (ξ) in the corresponding order which for d < dc depends
on d, at d = dc it has a logarithmic correction and for d > dc becomes independent of d. In
particular, the leading term of fd (ξ) behaves as ξ for d = 1 and ξ 2 ln(1/ξ) for d = dc = 2
and as ξ 2 for all d > dc = 2, the first correction term behaves as ξ d for 2 ≤ d < 6, and for
d = dc = 6 as ξ 6 ln(1/ξ) and as ξ 6 , for all d > dc = 6, and so on.
Mathematically, this behavior can be explained by the intrinsic properties of the Bessel
function Ks (ξ 2). By its definition, Ks (ξ 2) = π2 cosec(πs)[Is (ξ 2 ) − I−s (ξ 2 )] for non-integer s
and, in turn, Is (ξ 2 ) = ξ 2s
P∞
k=0 bk (s)ξ
4k
and ξ 2s I−s (ξ 2 ) =
P∞
k=0 bk (−s)ξ
4k
. As one can see
this expansion has s-independent powers of ξ that form the invariant part of fd (ξ). The
first terms of ξ 2s Ks (ξ 2 ) expansion are
ξ 2s Ks (ξ 2 ) ≈ b0 (s)ξ 4s + b1 (s)ξ 4s+4 + . . . − b0 (−s) − b1 (−s)ξ 4 − . . . .
Thus, for 0 < s < 1 (i.e., 2 < d < 6) fd (ξ) has the form fd (ξ) ≈ ξ 2 [a0 (−d) − a0 (d)ξ d−2 ]. We
see that the first term of this expansion is the invariant part (up to numerical coefficients)
of fd (ξ), which remains unchanged when varying d. The same argument shows that for
1 < s < 2 (6 < d < 10) fd (ξ) takes the form fd (ξ) ≈ ξ 2[a0 (−d) − a1 (−d)ξ 4 + a0 (d)ξ d−2 ] and
now two first terms of this expansion are the invariant part of fd (ξ). A special case in our
problem is d = 1, i.e., s = − 41 < 0. Then the leading term of fd (ξ) is ξ 2 ξ −4|s| = ξ, which is
easily seen by noting that K−s (ξ 2) = Ks (ξ 2 ).
For integer values of s, the small-ξ expansion of ξ 2s Ks (ξ 2 ) has a logarithmic term of form
ξ 4s log(1/ξ) = ξ d−2 log(1/ξ) [15].
5
In general, there are [s] + 1 ([s] is the integer part of s) terms in the invariant part of
fd (ξ).
III. CONCLUSIONS
We have studied analytically the small-ξ expansion of the mean probability density,
Pd (r, t), of random walks on random-walk chains in d-dimensional space. We have shown
that the leading terms of the expansion of, Pd (r, t), behaves, in the limit ξ = r/t1/4 → 0, as
Pd (r, t) ∝ ρ(r)t−1/2 (1 − ad ξ d−2 ),
when 3 ≤ d ≤ 5,
and as
Pd (r, t) ∝ ρ(r)t−1/2 (1 − cd ξ 4 ),
when d ≥ 7,
where ρ(r) ∼ r df −d and df = 2. This implies that the probability density Qd (r, t) =
Pd (r, t)/ρ(r) on the fractal chain behaves for d ≥ 7 as Qd (r, t) ∼ t−1/2 (1 − cd r 4 /t), consistent
with the behavior of diffusion in ℓ-space, i.e., p(ℓ, t) ∼ t−1/2 (1 − ℓ2 /2t), for ℓ2 ≪ t, and the
fact that Qd (r = 1, t) ∼ p(ℓ = 1, t) when d → ∞. We see that this already occurs when
d ≥ 7.
We have shown that logarithmic corrections occur at critical dimensions d = dc = 4n + 2,
with n = 0, 1, 2, . . ., i.e., dc = 2, 6, 10, . . ., for the terms ξ dc −2 log(1/ξ). In particular for d = 2,
Q2 (r, t) ≃ t−1/2 ln(t1/4 /r), for r ≪ t1/4 , and the probability density for the random walker
to be close to the origin, Q2 (r, t) behaves as t−1/2 ln t. This logarithmic correction is due to
the fact that in two dimensions the RWC returns to its starting point with probability one.
In one dimension, Q1 (r, t) ≃ t−1/4 /r, and in d = 3, Q3 (0, t) ≃ t−1/2 . One can say that d = 2
plays the role of a marginal dimensionality for the probability density of being at the origin
of random walks on RWC, while for larger r each order in the expansion has its own critical
dimension.
Acknowledgments:
6
We like to thank Julia Dräger, Markus Porto and Grisha Berkolaiko for valuable discussions. Financial support by the Alexander-von-Humboldt foundation, and the Deutsche
Forschungsgemeinshaft is gratefully acknowledged.
7
REFERENCES
[1] S. Alexander and R. Orbach, J. Phys. Lett. 43, L625 (1982)
[2] S. Havlin and D. Ben-Avraham, Adv. Phys. 36, 695 (1987)
[3] K. W. Kehr and R. Kutner, Physica A110, 535 (1982)
[4] A. Bunde and S. Havlin, eds., Fractals and disordered systems (Springer Verlag, Heidelberg, 1991)
[5] R. A. Guyer, Phys. Rev. A29, 2751 (1984)
[6] B. O’Shaughnessy and I. Procaccia, Phys. Rev. Lett. 54, 455 (1985); J. P. Bouchaud
and A. Georges, Phys. Rep. 195 (1990)
[7] A. Bunde, S. Havlin, and H. E. Roman, Phys. Rev. A42, 6274 (1990)
[8] J. Klafter, G. Zumofen and A. Blumen, J. Phys. A24, 4835 (1991)
[9] H. E. Roman and M. Giona, J. Phys. A25, 2107 (1992); M. Giona and H. E. Roman,
Physica A185, 87 (1992)
[10] A. Aharony and A. B. Harris, Physica A25, (1992); G. H. Weiss, Aspects and Applications of the Random Walk (North Holland, Amsterdam, 1994)
[11] H. E. Roman, Phys. Rev. E51, 5422 (1995)
[12] S. B. Yuste, J. Phys. A28, 7027 (1995)
[13] J. Dräger, S. Russ and A. Bunde, Europhys. Lett. 31, 425 (1995)
[14] Actually, the function Φd (r, ℓ) = 0 when ℓ < ℓmin, and ℓmin = r when all RWC configurations are considered (see [16]). Thus, the lower integration limit in Eq. (7) corresponds
to ℓmin = r. However, by performing the transformation x = ℓ/t1/2 , it can be shown
to vanish, for fixed ξ = r/t1/4 , as ξ/t1/4 → 0 when t → ∞. Hence, we set the lower
integration limit ℓmin = 0 in Eq. (7).
8
[15] I. S. Gradshteyn and I. M. Ryzhik, Table of Integrals, Series and Products (Academic
Press, New York 1965)
[16] A. Bunde and J. Dräger, Phys. Rev. E52, 53 (1995)
9
TABLES
TABLE I. The leading and correction terms for the series expansion of fd (ξ), with ξ ≡ r/t1/4 ,
when ξ → 0, Eq. (10), as a function of dimension d.
d
Leading term
First correction
Second correction
1
2.1558 ξ
−2.5066 ξ 2
O(ξ 5 )
2
2ξ 2 ln(1/ξ)
0.1738ξ 2
O(ξ 6 )
3
2.5066 ξ 2
−0.0609 ξ 3
O(ξ 6 )
4
2 ξ2
−1.2533 ξ 4
O(ξ 6 )
5
2.5066 ξ 2
−1.4372 ξ 5
O(ξ 6 )
6
4 ξ2
−ξ 6 ln(1/ξ)
−0.3369ξ 6
7
7.5199 ξ 2
−1.2533 ξ 6
0.8244 ξ 7
10