126 research outputs found
Quarantine generated phase transition in epidemic spreading
We study the critical effect of quarantine on the propagation of epidemics on
an adaptive network of social contacts. For this purpose, we analyze the
susceptible-infected-recovered (SIR) model in the presence of quarantine, where
susceptible individuals protect themselves by disconnecting their links to
infected neighbors with probability w, and reconnecting them to other
susceptible individuals chosen at random. Starting from a single infected
individual, we show by an analytical approach and simulations that there is a
phase transition at a critical rewiring (quarantine) threshold w_c separating a
phase (w<w_c) where the disease reaches a large fraction of the population,
from a phase (w >= w_c) where the disease does not spread out. We find that in
our model the topology of the network strongly affects the size of the
propagation, and that w_c increases with the mean degree and heterogeneity of
the network. We also find that w_c is reduced if we perform a preferential
rewiring, in which the rewiring probability is proportional to the degree of
infected nodes.Comment: 13 pages, 6 figure
Character evolution and missing (morphological) data across Asteridae
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/1/ajb21050-sup-0007-AppendixS7.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/2/ajb21050_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/3/ajb21050-sup-0019-AppendixS19.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/4/ajb21050-sup-0013-AppendixS13.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/5/ajb21050-sup-0014-AppendixS14.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/6/ajb21050-sup-0012-AppendixS12.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/7/ajb21050-sup-0009-AppendixS9.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/8/ajb21050-sup-0018-AppendixS18.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/9/ajb21050.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/10/ajb21050-sup-0004-AppendixS4.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/11/ajb21050-sup-0008-AppendixS8.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/12/ajb21050-sup-0005-AppendixS5.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/13/ajb21050-sup-0017-AppendixS17.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/14/ajb21050-sup-0006-AppendixS6.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/15/ajb21050-sup-0011-AppendixS11.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/16/ajb21050-sup-0016-AppendixS16.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/17/ajb21050-sup-0015-AppendixS15.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/18/ajb21050-sup-0010-AppendixS10.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143691/19/ajb21050-sup-0003-AppendixS3.pd
Rare region effects at classical, quantum, and non-equilibrium phase transitions
Rare regions, i.e., rare large spatial disorder fluctuations, can
dramatically change the properties of a phase transition in a quenched
disordered system. In generic classical equilibrium systems, they lead to an
essential singularity, the so-called Griffiths singularity, of the free energy
in the vicinity of the phase transition. Stronger effects can be observed at
zero-temperature quantum phase transitions, at nonequilibrium phase
transitions, and in systems with correlated disorder. In some cases, rare
regions can actually completely destroy the sharp phase transition by smearing.
This topical review presents a unifying framework for rare region effects at
weakly disordered classical, quantum, and nonequilibrium phase transitions
based on the effective dimensionality of the rare regions. Explicit examples
include disordered classical Ising and Heisenberg models, insulating and
metallic random quantum magnets, and the disordered contact process.Comment: Topical review, 68 pages, 14 figures, final version as publishe
The physics of spreading processes in multilayer networks
The study of networks plays a crucial role in investigating the structure,
dynamics, and function of a wide variety of complex systems in myriad
disciplines. Despite the success of traditional network analysis, standard
networks provide a limited representation of complex systems, which often
include different types of relationships (i.e., "multiplexity") among their
constituent components and/or multiple interacting subsystems. Such structural
complexity has a significant effect on both dynamics and function. Throwing
away or aggregating available structural information can generate misleading
results and be a major obstacle towards attempts to understand complex systems.
The recent "multilayer" approach for modeling networked systems explicitly
allows the incorporation of multiplexity and other features of realistic
systems. On one hand, it allows one to couple different structural
relationships by encoding them in a convenient mathematical object. On the
other hand, it also allows one to couple different dynamical processes on top
of such interconnected structures. The resulting framework plays a crucial role
in helping achieve a thorough, accurate understanding of complex systems. The
study of multilayer networks has also revealed new physical phenomena that
remain hidden when using ordinary graphs, the traditional network
representation. Here we survey progress towards attaining a deeper
understanding of spreading processes on multilayer networks, and we highlight
some of the physical phenomena related to spreading processes that emerge from
multilayer structure.Comment: 25 pages, 4 figure
- …