1,539 research outputs found
Multi-asset minority games
We study analytically and numerically Minority Games in which agents may invest in different assets (or markets), considering both the canonical and the grand-canonical versions. We find that the likelihood of agents trading in a given asset depends on the relative amount of information available in that market. More specifically, in the canonical game players play preferentially in the stock with less information. The same holds in the grand canonical game when agents have positive incentives to trade, whereas when agents payoff are solely related to their speculative ability they display a larger propensity to invest in the information-rich asset. Furthermore, in this model one finds a globally predictable phase with broken ergodicity
Scale-free networks with an exponent less than two
We study scale free simple graphs with an exponent of the degree distribution
less than two. Generically one expects such extremely skewed networks
-- which occur very frequently in systems of virtually or logically connected
units -- to have different properties than those of scale free networks with
: The number of links grows faster than the number of nodes and they
naturally posses the small world property, because the diameter increases by
the logarithm of the size of the network and the clustering coefficient is
finite. We discuss a simple prototype model of such networks, inspired by real
world phenomena, which exhibits these properties and allows for a detailed
analytical investigation
Redundant Interdependencies Boost the Robustness of Multiplex Networks
12 pages, 10 figures + Supp MatF. R. acknowledges support from the National Science Foundation (Grant No. CMMI-1552487) and the U.S. Army Research Office (Grant No. W911NF-16-1-0104)
Epidemic plateau in critical susceptible-infected-removed dynamics with nontrivial initial conditions
(11 pages, 10 figures)Containment measures implemented by some countries to suppress the spread of COVID-19 have resulted in a slowdown of the epidemic characterized by time series of daily infections plateauing over extended periods of time. We prove that such a dynamical pattern is compatible with critical Susceptible-Infected-Removed (SIR) dynamics. In traditional analyses of the critical SIR model, the critical dynamical regime is started from a single infected node. The application of containment measures to an ongoing epidemic, however, has the effect to make the system enter in its critical regime with a number of infected individuals potentially large. We describe how such non-trivial starting conditions affect the critical behavior of the SIR model. We perform a theoretical and large-scale numerical investigation of the model. We show that the expected outbreak size is an increasing function of the initial number of infected individuals, while the expected duration of the outbreak is a non-monotonic function of the initial number of infected individuals. Also, we precisely characterize the magnitude of the fluctuations associated with the size and duration of the outbreak in critical SIR dynamics with non-trivial initial conditions. Far from heard immunity, fluctuations are much larger than average values, thus indicating that predictions of plateauing time series may be particularly challenging
Weighted simplicial complexes and their representation power of higher-order network data and topology.
Hypergraphs and simplical complexes both capture the higher-order interactions of complex systems, ranging from higher-order collaboration networks to brain networks. One open problem in the field is what should drive the choice of the adopted mathematical framework to describe higher-order networks starting from data of higher-order interactions. Unweighted simplicial complexes typically involve a loss of information of the data, though having the benefit to capture the higher-order topology of the data. In this work we show that weighted simplicial complexes allow one to circumvent all the limitations of unweighted simplicial complexes to represent higher-order interactions. In particular, weighted simplicial complexes can represent higher-order networks without loss of information, allowing one at the same time to capture the weighted topology of the data. The higher-order topology is probed by studying the spectral properties of suitably defined weighted Hodge Laplacians displaying a normalized spectrum. The higher-order spectrum of (weighted) normalized Hodge Laplacians is studied combining cohomology theory with information theory. In the proposed framework we quantify and compare the information content of higher-order spectra of different dimension using higher-order spectral entropies and spectral relative entropies. The proposed methodology is tested on real higher-order collaboration networks and on the weighted version of the simplicial complex model "Network Geometry with Flavor.
Enhancement of Tc in the Superconductor-Insulator Phase Transition on Scale-Free Networks
A road map to understand the relation between the onset of the
superconducting state with the particular optimum heterogeneity in granular
superconductors is to study a Random Tranverse Ising Model on complex networks
with a scale-free degree distribution regularized by and exponential cutoff
p(k) \propto k^{-\gamma}\exp[-k/\xi]. In this paper we characterize in detail
the phase diagram of this model and its critical indices both on annealed and
quenched networks. To uncover the phase diagram of the model we use the tools
of heterogeneous mean-field calculations for the annealed networks and the most
advanced techniques of quantum cavity methods for the quenched networks. The
phase diagram of the dynamical process depends on the temperature T, the
coupling constant J and on the value of the branching ratio / where
k is the degree of the nodes in the network. For fixed value of the coupling
the critical temperature increases linearly with the branching ration which
diverges with the increasing cutoff value \xi or value of the \gamma exponent
\gamma< 3. This result suggests that the fractal disorder of the
superconducting material can be responsible for an enhancement of the
superconducting critical temperature. At low temperature and low couplings T<<1
and J<<1, instead, we observe a different behavior for annealed and quenched
networks. In the annealed networks there is no phase transition at zero
temperature while on quenched network we observe a Griffith phase dominated by
extremely rare events and a phase transition at zero temperature. The Griffiths
critical region, nevertheless, is decreasing in size with increasing value of
the cutoff \xi of the degree distribution for values of the \gamma exponents
\gamma< 3.Comment: (17 pages, 3 figures
Two-bands superconductivity with intra- and interband pairing for synthetic superlattices
We consider a model for superconductivity in a two-band superconductor,
having an anisotropic electronic structure made of two partially overlapping
bands with a first hole-like and a second electron-like fermi surface. In this
pairing scenario, driven by the interplay between interband and
intraband pairing terms, we have solved the two gap equations at the
critical temperature and calculate and the chemical potential
as a function of the number of carriers for various values of pairing
interactions, , , and . The results show the
complexity of the physics of condensates with multiple order parameters with
the chemical potential near band edges.Comment: 6 pages, 2 figure
THE IMAGE OF THE CITY INTERPRETED THROUGH BIOSENSORS PATH ANALYSIS AND IDENTIFICATION OF PERCEPTUAL POLES IN THE NARNI CASE STUDY
Abstract. The research aims to interpret the image of the city, according to the conventions defined by Kevin Lynch, obtained from the analysis of the impact of environmental stimuli on the person. The study relates the digital reconstruction of the spaces analysed with the detection of the trend of valence obtained on a statistical sample using an EEG helmet. The monitoring of the degree of attraction or aversion to the stimuli of the surrounding environment is processed through algorithmic procedures to identify along a path the perceptual poles. This path, reported in GIS environment, allows to reconstruct georeferenced maps that interpret the brain data, synchronized with GNSS. The spatial poles thus identified are further investigated using eye-tracker to understand the reasons for the impact of the environment on humans
THE SEDUCTION OF THE SIMULATION. 3D MODELLING AND STORYTELLING OF UNREALIZED PERUGIA RAIL STATION
Abstract. The study aims at enhancing and requalifying the area of Fontivegge in Perugia. It seeks to instil in the population a sense of identity and belonging to the place through the digital reconstruction of the first design hypothesis of the station itself, transmitting the cultural heritage of the place with new participatory methods, such as serious games and virtual reality. Starting from the project drawings preserved at the academy of San Luca in Rome, conceived by the architect Antonio Cipolla, the project is reconstructed philologically following historical and archival studies, by interpreting the data collected. Following the reconstruction of the 3D model, evocative mook up images and a virtual reality are created, making the intangible tangible and explorable. Through the virtual simulation of the place and its visualisation, new forms of participation are sought, mending the relationship between territory and population, laying the foundations for a different reading of the area and a cultural heritage accessible and open to all
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