Entropy,
Journal Year:
2024,
Volume and Issue:
26(3), P. 248 - 248
Published: March 11, 2024
Diverse
higher-order
structures,
foundational
for
supporting
a
network’s
“meta-functions”,
play
vital
role
in
structure,
functionality,
and
the
emergence
of
complex
dynamics.
Nevertheless,
problem
dismantling
them
has
been
consistently
overlooked.
In
this
paper,
we
introduce
concept
with
objective
disrupting
not
only
network
connectivity
but
also
eradicating
all
structures
each
branch,
thereby
ensuring
thorough
functional
paralysis.
Given
diversity
unknown
specifics
identifying
targeting
individually
is
practical
or
even
feasible.
Fortunately,
their
close
association
k-cores
arises
from
internal
high
connectivity.
Thus,
transform
structure
measurement
into
measurements
on
corresponding
orders.
Furthermore,
propose
Belief
Propagation-guided
Higher-order
Dismantling
(BPHD)
algorithm,
minimizing
costs
while
achieving
maximal
disruption
to
ultimately
converting
forest.
BPHD
exhibits
explosive
vulnerability
counterintuitively
showcasing
decreasing
increasing
structural
complexity.
Our
findings
offer
novel
approach
malignant
networks,
emphasizing
substantial
challenges
inherent
safeguarding
against
such
malicious
attacks.
IEEE/CAA Journal of Automatica Sinica,
Journal Year:
2022,
Volume and Issue:
9(4), P. 573 - 577
Published: March 9, 2022
The
Laplacian
eigenvalue
spectrum
of
a
complex
network
contains
great
deal
information
about
the
topology
and
dynamics,
particularly
affecting
synchronization
process
performance.
This
article
briefly
reviews
recent
progress
in
studies
synchronizability,
regarding
its
spectral
criteria
topological
optimization,
explores
role
higher-order
topologies
measuring
optimal
synchronizability
large-scale
networks.
Physical Review Letters,
Journal Year:
2023,
Volume and Issue:
130(18)
Published: May 2, 2023
Searching
for
key
nodes
and
edges
in
a
network
is
long-standing
problem.
Recently
cycle
structure
has
received
more
attention.
Is
it
possible
to
propose
ranking
algorithm
importance?
We
address
the
problem
of
identifying
cycles
network.
First,
we
provide
concrete
definition
importance-in
terms
Fiedler
value
(the
second
smallest
Laplacian
eigenvalue).
Key
are
those
that
contribute
most
substantially
dynamical
behavior
Second,
by
comparing
sensitivity
different
cycles,
neat
index
provided.
Numerical
examples
given
show
effectiveness
this
method.
Communications Physics,
Journal Year:
2024,
Volume and Issue:
7(1)
Published: Jan. 8, 2024
Abstract
Empirical
networks
exhibit
significant
heterogeneity
in
node
connections,
resulting
a
few
vertices
playing
critical
roles
various
scenarios,
including
decision-making,
viral
marketing,
and
population
immunization.
Thus,
identifying
key
is
fundamental
research
problem
Network
Science.
In
this
paper,
we
introduce
vertex
entanglement
(VE),
an
entanglement-based
metric
capable
of
quantifying
the
perturbations
caused
by
individual
on
spectral
entropy,
residing
at
intersection
quantum
information
network
science.
Our
analytical
analysis
reveals
that
VE
closely
related
to
robustness
transmission
ability.
As
application,
offers
approach
challenging
optimal
dismantling,
empirical
experiments
demonstrate
its
superiority
over
state-of-the-art
algorithms.
Furthermore,
also
contributes
diagnosis
autism
spectrum
disorder
(ASD),
with
distinctions
hub
disruption
indices
based
between
ASD
typical
controls,
promising
diagnostic
role
for
assessment.
Communications Physics,
Journal Year:
2022,
Volume and Issue:
5(1)
Published: April 19, 2022
Abstract
Networks
in
nature
have
complex
interactions
among
agents.
One
significant
phenomenon
induced
by
is
synchronization
of
coupled
agents,
and
the
interactive
network
topology
can
be
tuned
to
optimize
synchronization.
Previous
studies
showed
that
optimized
conventional
with
pairwise
favors
a
homogeneous
degree
distribution
nodes
for
undirected
interactions,
always
structurally
asymmetric
directed
interactions.
However,
optimal
control
on
prevailing
higher-order
less
explored.
Here,
considering
hypergraph
Kuramoto
model
2-hyperlink
we
find
synchronizability
may
distinct
properties.
For
networks
simulated
annealing
tend
become
nodes’
generalized
degree.
We
further
rigorously
demonstrate
structural
symmetry
preserved
optimally
synchronizable
The
results
suggest
controlling
leads
phenomena
beyond
IEEE Transactions on Network Science and Engineering,
Journal Year:
2024,
Volume and Issue:
11(4), P. 3838 - 3850
Published: April 16, 2024
The
connectivity
and
functionality
of
a
network
can
be
significantly
influenced
by
vital
nodes,
subset
whose
behaviors
are
pivotal
in
applications
like
misinformation
suppression
epidemic
containment.
In
this
paper,
we
discuss
the
nodes
identification
problem
from
perspective
percolation
transition
combinatorial
optimization,
then
present
novel
Subsequence-optimized
Genetic-Relationship-related
(SGR)
algorithm
to
target
most
influential
efficiently
effectively
via
integrating
genetic
Relationship
Related
(RR)
strategy.
Specifically,
first
propose
subsequence
optimization
strategy
to,
on
one
hand,
constrain
search
space
RR,
an
adaptive
approach
accelerate
RR
method,
such
that
solution
each
converge
obtained
rapidly.
SGR
iteratively
runs
process
randomly
chosen
subsequences
and,
other
maintains
diversity
enlarge
entire
for
global
optimum.
Extensive
experiments
13
empirical
networks
varied
real-world
scenarios
demonstrate
method's
remarkable
superiority.
tasks
as
dismantling,
synchronization
control,
diffusion
containment,
our
outperforms
state-of-the-art
methods,
underscoring
its
efficacy
identifying
nodes.
