1,479 research outputs found
Identifying the starting point of a spreading process in complex networks
When dealing with the dissemination of epidemics, one important question that
can be asked is the location where the contamination began. In this paper, we
analyze three spreading schemes and propose and validate an effective
methodology for the identification of the source nodes. The method is based on
the calculation of the centrality of the nodes on the sampled network,
expressed here by degree, betweenness, closeness and eigenvector centrality. We
show that the source node tends to have the highest measurement values. The
potential of the methodology is illustrated with respect to three theoretical
complex network models as well as a real-world network, the email network of
the University Rovira i Virgili
Price Competition, Fluctuations, and Welfare Guarantees
In various markets where sellers compete in price, price oscillations are
observed rather than convergence to equilibrium. Such fluctuations have been
empirically observed in the retail market for gasoline, in airline pricing and
in the online sale of consumer goods. Motivated by this, we study a model of
price competition in which an equilibrium rarely exists. We seek to analyze the
welfare, despite the nonexistence of an equilibrium, and present welfare
guarantees as a function of the market power of the sellers.
We first study best response dynamics in markets with sellers that provide a
homogeneous good, and show that except for a modest number of initial rounds,
the welfare is guaranteed to be high. We consider two variations: in the first
the sellers have full information about the valuation of the buyer. Here we
show that if there are items available across all sellers and is
the maximum number of items controlled by any given seller, the ratio of the
optimal welfare to the achieved welfare will be at most
. As the market power of the largest seller
diminishes, the welfare becomes closer to optimal. In the second variation we
consider an extended model where sellers have uncertainty about the buyer's
valuation. Here we similarly show that the welfare improves as the market power
of the largest seller decreases, yet with a worse ratio of
. The exponential gap in welfare between the two
variations quantifies the value of accurately learning the buyer valuation.
Finally, we show that extending our results to heterogeneous goods in general
is not possible. Even for the simple class of -additive valuations, there
exists a setting where the welfare approximates the optimal welfare within any
non-zero factor only for fraction of the time, where is the number
of sellers
SLOCC determinant invariants of order 2^{n/2} for even n qubits
In this paper, we study SLOCC determinant invariants of order 2^{n/2} for any
even n qubits which satisfy the SLOCC determinant equations. The determinant
invariants can be constructed by a simple method and the set of all these
determinant invariants is complete with respect to permutations of qubits.
SLOCC entanglement classification can be achieved via the vanishing or not of
the determinant invariants. We exemplify the method for several even number of
qubits, with an emphasis on six qubits.Comment: J. Phys. A: Math. Theor. 45 (2012) 07530
Simulating non-Markovian stochastic processes
We present a simple and general framework to simulate statistically correct
realizations of a system of non-Markovian discrete stochastic processes. We
give the exact analytical solution and a practical an efficient algorithm alike
the Gillespie algorithm for Markovian processes, with the difference that now
the occurrence rates of the events depend on the time elapsed since the event
last took place. We use our non-Markovian generalized Gillespie stochastic
simulation methodology to investigate the effects of non-exponential
inter-event time distributions in the susceptible-infected-susceptible model of
epidemic spreading. Strikingly, our results unveil the drastic effects that
very subtle differences in the modeling of non-Markovian processes have on the
global behavior of complex systems, with important implications for their
understanding and prediction. We also assess our generalized Gillespie
algorithm on a system of biochemical reactions with time delays. As compared to
other existing methods, we find that the generalized Gillespie algorithm is the
most general as it can be implemented very easily in cases, like for delays
coupled to the evolution of the system, where other algorithms do not work or
need adapted versions, less efficient in computational terms.Comment: Improvement of the algorithm, new results, and a major reorganization
of the paper thanks to our coauthors L. Lafuerza and R. Tora
Agents Play Mix-game
In mix-game which is an extension of minority game, there are two groups of
agents; group1 plays the majority game, but the group2 plays the minority game.
This paper studies the change of the average winnings of agents and
volatilities vs. the change of mixture of agents in mix-game model. It finds
that the correlations between the average winnings of agents and the mean of
local volatilities are different with different combinations of agent memory
length when the proportion of agents in group 1 increases. This study result
suggests that memory length of agents in group1 be smaller than that of agent
in group2 when mix-game model is used to simulate the financial markets.Comment: 8 pages, 6 figures, 3 table
Adapting Quality Assurance to Adaptive Systems: The Scenario Coevolution Paradigm
From formal and practical analysis, we identify new challenges that
self-adaptive systems pose to the process of quality assurance. When tackling
these, the effort spent on various tasks in the process of software engineering
is naturally re-distributed. We claim that all steps related to testing need to
become self-adaptive to match the capabilities of the self-adaptive
system-under-test. Otherwise, the adaptive system's behavior might elude
traditional variants of quality assurance. We thus propose the paradigm of
scenario coevolution, which describes a pool of test cases and other
constraints on system behavior that evolves in parallel to the (in part
autonomous) development of behavior in the system-under-test. Scenario
coevolution offers a simple structure for the organization of adaptive testing
that allows for both human-controlled and autonomous intervention, supporting
software engineering for adaptive systems on a procedural as well as technical
level.Comment: 17 pages, published at ISOLA 201
Network robustness and fragility: Percolation on random graphs
Recent work on the internet, social networks, and the power grid has
addressed the resilience of these networks to either random or targeted
deletion of network nodes. Such deletions include, for example, the failure of
internet routers or power transmission lines. Percolation models on random
graphs provide a simple representation of this process, but have typically been
limited to graphs with Poisson degree distribution at their vertices. Such
graphs are quite unlike real world networks, which often possess power-law or
other highly skewed degree distributions. In this paper we study percolation on
graphs with completely general degree distribution, giving exact solutions for
a variety of cases, including site percolation, bond percolation, and models in
which occupation probabilities depend on vertex degree. We discuss the
application of our theory to the understanding of network resilience.Comment: 4 pages, 2 figure
Experimental constraints on a dark matter origin for the DAMA annual modulation effect
A claim for evidence of dark matter interactions in the DAMA experiment has
been recently reinforced. We employ a new type of germanium detector to
conclusively rule out a standard isothermal galactic halo of Weakly Interacting
Massive Particles (WIMPs) as the explanation for the annual modulation effect
leading to the claim. Bounds are similarly imposed on a suggestion that dark
pseudoscalars mightlead to the effect. We describe the sensitivity to light
dark matter particles achievable with our device, in particular to
Next-to-Minimal Supersymmetric Model candidates.Comment: v4: introduces recent results from arXiv:0807.3279 and
arXiv:0807.2926. Sensitivity to pseudoscalars is revised in light of the
first. Discussion on the subject adde
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