scholarly journals Synchronization in scale-free networks: The role of finite-size effects

2015 ◽  
Vol 110 (6) ◽  
pp. 66001 ◽  
Author(s):  
D. Torres ◽  
M. A. Di Muro ◽  
C. E. La Rocca ◽  
L. A. Braunstein
Keyword(s):  
Size Effects ◽  
Finite Size ◽  
Finite Size Effects ◽  
Scale Free ◽  
Scale Free Networks

scholarly journals Cut-offs and finite size effects in scale-free networks

2004 ◽  
Vol 38 (2) ◽  
pp. 205-209 ◽  
Author(s):  
M. Bogu�� ◽  
R. Pastor-Satorras ◽  
A. Vespignani
Keyword(s):  
Size Effects ◽  
Finite Size ◽  
Finite Size Effects ◽  
Scale Free ◽  
Scale Free Networks

scholarly journals Lattice induced crystallization of nanodroplets: the role of finite-size effects and substrate properties in controlling polymorphism

Nanoscale ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 4921-4926 ◽  
Author(s):  
Julien Lam ◽  
James F. Lutsko
Keyword(s):  
Molecular Dynamics ◽  
Size Effects ◽  
Finite Size ◽  
Solid Substrate ◽  
General Phenomenon ◽  
Finite Size Effects ◽  
Substrate Properties ◽  
Dynamics Simulations ◽  
Induced Crystallization

Freezing a nanodroplet deposited on a solid substrate leads to the formation of crystalline structures. We study the inherent mechanisms underlying this general phenomenon by means of molecular dynamics simulations.

scholarly journals True scale-free networks hidden by finite size effects

2020 ◽  
Vol 118 (2) ◽  
pp. e2013825118
Author(s):  
Matteo Serafino ◽  
Giulio Cimini ◽  
Amos Maritan ◽  
Andrea Rinaldo ◽  
Samir Suweis ◽  
...  
Keyword(s):  
Power Law ◽  
Size Effects ◽  
Finite Size ◽  
Statistical Testing ◽  
Finite Size Scaling ◽  
Finite Size Effects ◽  
Scale Free ◽  
Size Scaling ◽  
Naturally Occurring ◽  
Scaling Hypothesis

We analyze about 200 naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned on the basis of statistical testing of the validity of power law distributions of network degrees. Specifically, we analyze by finite size scaling analysis the datasets of real networks to check whether the purported departures from power law behavior are due to the finiteness of sample size. We find that a large number of the networks follows a finite size scaling hypothesis without any self-tuning. This is the case of biological protein interaction networks, technological computer and hyperlink networks, and informational networks in general. Marked deviations appear in other cases, especially involving infrastructure and transportation but also in social networks. We conclude that underlying scale invariance properties of many naturally occurring networks are extant features often clouded by finite size effects due to the nature of the sample data.

scholarly journals Aeolian and subaqueous bedforms in shear flows

2013 ◽  
Vol 371 (2004) ◽  
pp. 20120364 ◽  
Author(s):  
Bruno Andreotti ◽  
Philippe Claudin
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Water Depth ◽  
Size Effects ◽  
Finite Size ◽  
Linear Instability ◽  
Laboratory Measurements ◽  
Finite Size Effects ◽  
Sediment Bed

A sediment bed sheared by an unbounded flow is unconditionally unstable towards the growth of bedforms called ripples under water and dunes in the aeolian case. We review here the dynamical mechanisms controlling this linear instability, putting the emphasis on testing models against field and laboratory measurements. We then discuss the role of nonlinearities and the influence of finite size effects, namely the depth of the atmospheric boundary layer in the aeolian case and the water depth in the case of rivers.

Finite-size effects on semi-directed Barabási–Albert networks

2016 ◽  
Vol 27 (09) ◽  
pp. 1650109 ◽  
Author(s):  
M. A. Radwan ◽  
Muneer A. Sumour ◽  
A. M. Elbitar ◽  
M. M. Shabat ◽  
F. W. S. Lima
Keyword(s):  
Size Effect ◽  
Size Effects ◽  
Finite Size ◽  
Network Size ◽  
Finite Size Effect ◽  
Finite Size Effects ◽  
Scale Free ◽  
Number Formula

In scale-free Barabási–Albert (BA) networks, we study the finite-size effect at different number m of neighbors. So, we investigate the effects of finite network size N for the recently developed semi-directed BA networks (SDBA1 and SDBA2) at fixed [Formula: see text]) and show and explain the gap in the distribution of the number [Formula: see text] of neighbors of the nodes i.

Sign in / Sign up

Export Citation Format

Share Document