793 research outputs found
Motif Dynamics in Signed Directional Complex Networks
Complex networks evolve and vary their structure as time goes by. In
particular, the links in those networks have both a sign and a directionality.
To understand their structural principles, we measure the network motifs, which
are patterns that appear much more than one would expect in randomized
networks, considering both link properties. We propose motif dynamics, which is
a study to investigate the change in the number of motifs, and applied the
motif dynamics to an open evolving network model and empirical data. We confirm
that a non-cyclic motif has a greater correlation with the system size than a
cyclic structural motif. Furthermore, the motif dynamics can give us insight
into the friendship between freshmen in a university
Does three-tangle properly quantify the three-party entanglement for Greenberger-Horne-Zeilinger-type states?
Some mixed states composed of only GHZ states can be expressed in terms of
only W-states. This fact implies that such states have vanishing three-tangle.
One of such rank-3 states, , is explicitly presented in this paper.
These results are used to compute analytically the three-tangle of a rank-4
mixed state composed of four GHZ states. This analysis with
considering Bloch sphere of qudit system allows us to derive the
hyper-polyhedron. It is shown that the states in this hyper-polyhedron have
vanishing three-tangle. Computing the one-tangles for and ,
we prove the monogamy inequality explicitly. Making use of the fact that the
three-tangle of is zero, we try to explain why the W-class in the
whole mixed states is not of measure zero contrary to the case of pure states.Comment: 10 pages, no figure V2: new calculational results are included. 11
pages: V3 accepted in the Rapid Communication of PRA, 4 pages (two column
Effectiveness of vaccination and quarantine policies to curb the spread of COVID-19
A pandemic, the worldwide spread of a disease, can threaten human beings from
the social as well as biological perspectives and paralyze existing living
habits. To stave off the more devastating disaster and return to a normal life,
people make tremendous efforts at multiscale levels from individual to
worldwide: paying attention to hand hygiene, developing social policies such as
wearing masks, social distancing, quarantine, and inventing vaccines and
remedy. Regarding the current severe pandemic, namely the coronavirus disease
2019, we explore the spreading-suppression effect when adopting the
aforementioned efforts. Especially the quarantine and vaccination are
considered since they are representative primary treatments for block spreading
and prevention at the government level. We establish a compartment model
consisting of susceptible (S), vaccination (V), exposed (E), infected (I),
quarantined (Q), and recovered (R) compartments, called SVEIQR model. We look
into the infected cases in Seoul and consider three kinds of vaccines, Pfizer,
Moderna, and AstraZeneca. The values of the relevant parameters are obtained
from empirical data from Seoul and clinical data for vaccines and estimated by
Bayesian inference. After confirming that our SVEIQR model is plausible, we
test the various scenarios by adjusting the associated parameters with the
quarantine and vaccination policies around the current values. The quantitative
result obtained from our model could suggest a guideline for policy making on
effective vaccination and social policies.Comment: 8 pages, 5 figure
Invasion and Interaction Determine Population Composition in an Open Evolving System
It is well-known that interactions between species determine the population
composition in an ecosystem. Conventional studies have focused on fixed
population structures to reveal how interactions shape population compositions.
However, interaction structures are not fixed, but change over time due to
invasions. Thus, invasion and interaction play an important role in shaping
communities. Despite its importance, however, the interplay between invasion
and interaction has not been well explored. Here, we investigate how invasion
affects the population composition with interactions in open evolving systems
considering generalized Lotka-Volterra-type dynamics. Our results show that the
system has two distinct regimes. One is characterized by low diversity with
abrupt changes of dominant species in time, appearing when the interaction
between species is strong and invasion slowly occurs. On the other hand,
frequent invasions can induce higher diversity with slow changes in abundances
despite strong interactions. It is because invasion happens before the system
reaches its equilibrium, which drags the system from its equilibrium all the
time. All species have similar abundances in this regime, which implies that
fast invasion induces regime shift. Therefore, whether invasion or interaction
dominates determines the population composition.Comment: 15 pages (including supplementary material), 8 figures (4 figures in
main, 4 figures in SI
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