scholarly journals Emergence of complex structures from nonlinear interactions and noise in coevolving networks

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tomasz Raducha ◽  
Maxi San Miguel
Keyword(s):  
Ad Hoc ◽  
Stochastic Dynamics ◽  
Social Systems ◽  
Analytical Description ◽  
Joint Effect ◽  
Pair Approximation ◽  
Complex Structures ◽  
Analytical Approximations ◽  
Coexistence Phase ◽  
Fragmentation Phases

Abstract We study the joint effect of the non-linearity of interactions and noise on coevolutionary dynamics. We choose the coevolving voter model as a prototype framework for this problem. By numerical simulations and analytical approximations we find three main phases that differ in the absolute magnetisation and the size of the largest component: a consensus phase, a coexistence phase, and a dynamical fragmentation phase. More detailed analysis reveals inner differences in these phases, allowing us to divide two of them further. In the consensus phase we can distinguish between a weak or alternating consensus and a strong consensus, in which the system remains in the same state for the whole realisation of the stochastic dynamics. In the coexistence phase we distinguish a fully-mixing phase and a structured coexistence phase, where the number of active links drops significantly due to the formation of two homogeneous communities. Our numerical observations are supported by an analytical description using a pair approximation approach and an ad-hoc calculation for the transition between the coexistence and dynamical fragmentation phases. Our work shows how simple interaction rules including the joint effect of non-linearity, noise, and coevolution lead to complex structures relevant in the description of social systems.

scholarly journals Improved estimations of stochastic chemical kinetics by finite-state expansion

2021 ◽  
Vol 477 (2251) ◽  
pp. 20200964
Author(s):  
Tabea Waizmann ◽  
Luca Bortolussi ◽  
Andrea Vandin ◽  
Mirco Tribastone
Keyword(s):  
Master Equation ◽  
State Space ◽  
Stochastic Dynamics ◽  
Reaction Network ◽  
Discrete State ◽  
State Expansion ◽  
Analytical Approximations ◽  
Finite State ◽  
Stochastic Reaction ◽  
Discrete State Space

Stochastic reaction networks are a fundamental model to describe interactions between species where random fluctuations are relevant. The master equation provides the evolution of the probability distribution across the discrete state space consisting of vectors of population counts for each species. However, since its exact solution is often elusive, several analytical approximations have been proposed. The deterministic rate equation (DRE) gives a macroscopic approximation as a compact system of differential equations that estimate the average populations for each species, but it may be inaccurate in the case of nonlinear interaction dynamics. Here we propose finite-state expansion (FSE), an analytical method mediating between the microscopic and the macroscopic interpretations of a stochastic reaction network by coupling the master equation dynamics of a chosen subset of the discrete state space with the mean population dynamics of the DRE. An algorithm translates a network into an expanded one where each discrete state is represented as a further distinct species. This translation exactly preserves the stochastic dynamics, but the DRE of the expanded network can be interpreted as a correction to the original one. The effectiveness of FSE is demonstrated in models that challenge state-of-the-art techniques due to intrinsic noise, multi-scale populations and multi-stability.

scholarly journals Hierarchical model of information signals formation at the physical layer in FANET

2020 ◽  
Vol 11 (30) ◽  
pp. 178-188
Author(s):  
G. S. Vasilyev ◽  
O. R. Kuzichkin ◽  
I. A. Kurilov ◽  
D. I. Surzhik
Keyword(s):  
Communication Networks ◽  
Hierarchical Model ◽  
Ad Hoc ◽  
Multipath Propagation ◽  
Communication Channels ◽  
Analytical Description ◽  
Physical Layer ◽  
Network Equipment ◽  
Hoc Networks ◽  
Nonlinear Signal

Creation of reliable and efficient flying ad-hoc networks (FANET) requires detailed development of the model of the physical layer of data transmission, determined by the conditions of operation of the networks. The problems of well-known software simulators of communication networks are the simplified nature of the physical layer, as well as the inability to obtain specific analytical solutions in the process of simulation. The hierarchical model of formation of information signals which allows to represent various types of communication channels and the channel-forming equipment, for providing their analytical description and the further analysis is developed. The model allows to describe communication channels between UAVs and (or) ground control centers taking into account the effects of attenuation, intersymbol interference, multipath propagation of signals; schemes of terminal and intermediate network equipment with linear and nonlinear signal conversion; circuits with forward regulation, backward regulation and combined regulation; circuits with multi-channel signal generation and processing, as well as cross-links between channels. Analytical expressions of the transfer function of the generalized hierarchical model for an arbitrary number of disclosed levels of hierarchy are obtained. An example of the presentation and study of the UAV transmitter circuit on the basis of a hierarchical model of signal formation is considered.

Revisiting Software Engineering in the Social Era

2016 ◽  
Vol 6 (4) ◽  
pp. 36-46 ◽  
Author(s):  
Vanilson Burégio ◽  
Ejub Kajan ◽  
Mohamed Sellami ◽  
Noura Faci ◽  
Zakaria Maamar ◽  
...  
Keyword(s):  
Social Media ◽  
Software Engineering ◽  
Ad Hoc ◽  
Social Systems ◽  
The Social ◽  
The Web

This paper discusses the possible changes that software engineering will have to go through in response to the challenges and issues associated with social media. Indeed, people have never been so connected like nowadays by forming spontaneous relations with others (even strangers) and engaging in ad-hoc interactions. The Web is the backbone of this new social era – an open, global, ubiquitous, and pervasive platform for today's society and world - suggesting that “everything” can socialize or be socialized. This paper also analyzes the evolution of software engineering as a discipline, points out the characteristics of social systems, and finally presents how these characteristics could affect software engineering's models and practices. It is expected that social systems' characteristics will make software engineering evolve one more time to tackle and address the social era's challenges and issues, respectively.

Revisiting Software Engineering in the Social Era

Crowdsourcing ◽  
2019 ◽  
pp. 1014-1025
Author(s):  
Vanilson Burégio ◽  
Ejub Kajan ◽  
Mohamed Sellami ◽  
Noura Faci ◽  
Zakaria Maamar ◽  
...  
Keyword(s):  
Social Media ◽  
Software Engineering ◽  
Ad Hoc ◽  
Social Systems ◽  
The Social ◽  
The Web

This paper discusses the possible changes that software engineering will have to go through in response to the challenges and issues associated with social media. Indeed, people have never been so connected like nowadays by forming spontaneous relations with others (even strangers) and engaging in ad-hoc interactions. The Web is the backbone of this new social era – an open, global, ubiquitous, and pervasive platform for today's society and world - suggesting that “everything” can socialize or be socialized. This paper also analyzes the evolution of software engineering as a discipline, points out the characteristics of social systems, and finally presents how these characteristics could affect software engineering's models and practices. It is expected that social systems' characteristics will make software engineering evolve one more time to tackle and address the social era's challenges and issues, respectively.

scholarly journals Kernel nullers for an arbitrary number of apertures

2020 ◽  
Vol 642 ◽  
pp. A202
Author(s):  
Romain Laugier ◽  
Nick Cvetojevic ◽  
Frantz Martinache
Keyword(s):  
Arbitrary Number ◽  
Ad Hoc ◽  
Extrasolar Planets ◽  
Graphical Representation ◽  
Direct Detection ◽  
Analytical Description ◽  
Optical Path ◽  
Original Design ◽  
Beam Combiner ◽  
Symmetry Properties

Context. The use of interferometric nulling for the direct detection of extrasolar planets is in part limited by the extreme sensitivity of the instrumental response to tiny optical path differences between apertures. The recently proposed kernel-nuller architecture attempts to alleviate this effect with an all-in-one combiner design that enables the production of observables inherently robust to residual optical path differences (≪λ). Aims. To date, a unique kernel-nuller design has been proposed ad hoc for a four-beam combiner. We examine the properties of this original design and generalize them for an arbitrary number of apertures. Methods. We introduce a convenient graphical representation of the complex combiner matrices that model the kernel nuller and highlight the symmetry properties that enable the formation of kernel nulls. The analytical description of the nulled outputs we provide demonstrates the properties of a kernel nuller. Results. Our description helps outline a systematic way to build a kernel nuller for an arbitrary number of apertures. The designs for three- and six-input combiners are presented along with the original four-input concept. The combiner grows in complexity with the square of the number of apertures. While one can mitigate this complexity by multiplexing nullers working independently over a smaller number of sub-apertures, an all-in-one kernel nuller recombining a large number of apertures appears as the most efficient way to characterize a high-contrast complex astrophysical scene. Conclusions. Kernel nullers can be designed for an arbitrary number of apertures that produce observable quantities robust to residual perturbations. The designs we recommend are lossless and take full advantage of all the available interferometric baselines. They are complete, result in as many kernel nulls as the theoretically expected number of closure-phases, and are optimized to require the smallest possible number of outputs.

scholarly journals DYNAMIC DIPOLE AND QUADRUPOLE PHASE TRANSITIONS IN THE KINETIC SPIN-1 MODEL

2006 ◽  
Vol 17 (09) ◽  
pp. 1239-1255 ◽  
Author(s):  
MUSTAFA KESKİN ◽  
OSMAN CANKO ◽  
ERSIN KANTAR
Keyword(s):  
Magnetic Field ◽  
Phase Transitions ◽  
Phase Diagrams ◽  
Stochastic Dynamics ◽  
Mean Field ◽  
Dynamic Phase Transitions ◽  
Coexistence Phase ◽  
Dynamic Phase ◽  
Model Hamiltonian ◽  
Sinusoidal Magnetic Field

The dynamic phase transitions have been studied, within a mean-field approach, in the kinetic spin-1 Ising model Hamiltonian with arbitrary bilinear and biquadratic pair interactions in the presence of a time varying (sinusoidal) magnetic field by using the Glauber-type stochastic dynamics. The nature (first- or second-order) of the transition is characterized by investigating the behavior of the thermal variation of the dynamic order parameters. The dynamic phase transitions (DPTs) are obtained and the phase diagrams are constructed in the temperature and magnetic field amplitude plane and found six fundamental types of phase diagrams. Phase diagrams exhibit one or two dynamic tricritical points depending on the biquadratic interaction (K). Besides the disordered (D) and ferromagnetic (F) phases, the FQ + D, F + FQ and F + D coexistence phase regions also exist in the system and the F and F + D phases disappear for high values of K.

scholarly journals Evolutionary games of multiplayer cooperation on graphs

2016 ◽  
Author(s):  
Jorge Peña ◽  
Bin Wu ◽  
Jordi Arranz ◽  
Arne Traulsen
Keyword(s):  
Spatial Structure ◽  
Computer Simulations ◽  
Evolutionary Games ◽  
Structured Populations ◽  
Evolution Of Cooperation ◽  
Pair Approximation ◽  
Regular Graphs ◽  
Multiplayer Games ◽  
Cooperative Interactions ◽  
Analytical Approximations

AbstractThere has been much interest in studying evolutionary games in structured populations, often modelled as graphs. However, most analytical results so far have only been obtained for two-player or linear games, while the study of more complex multiplayer games has been usually tackled by computer simulations. Here we investigate evolutionary multiplayer games on graphs updated with a Moran death-Birth process. For cycles, we obtain an exact analytical condition for cooperation to be favored by natural selection, given in terms of the payoffs of the game and a set of structure coefficients. For regular graphs of degree three and larger, we estimate this condition using a combination of pair approximation and diffusion approximation. For a large class of cooperation games, our approximations suggest that graph-structured populations are stronger promoters of cooperation than populations lacking spatial structure. Computer simulations validate our analytical approximations for random regular graphs and cycles, but show systematic differences for graphs with many loops such as lattices. In particular, our simulation results show that these kinds of graphs can even lead to more stringent conditions for the evolution of cooperation than well-mixed populations. Overall, we provide evidence suggesting that the complexity arising from many-player interactions and spatial structure can be captured by pair approximation in the case of random graphs, but that it need to be handled with care for graphs with high clustering.Author SummaryCooperation can be defined as the act of providing fitness benefits to other individuals, often at a personal cost. When interactions occur mainly with neighbors, assortment of strategies can favor cooperation but local competition can undermine it. Previous research has shown that a single coefficient can capture this trade-off when cooperative interactions take place between two players. More complicated, but also more realistic models of cooperative interactions involving multiple players instead require several such coefficients, making it difficult to assess the effects of population structure. Here, we obtain analytical approximations for the coefficients of multiplayer games in graph-structured populations. Computer simulations show that, for particular instances of multiplayer games, these approximate coefficients predict the condition for cooperation to be promoted in random graphs well, but fail to do so in graphs with more structure, such as lattices. Our work extends and generalizes established results on the evolution of cooperation on graphs, but also highlights the importance of explicitly taking into account higher-order statistical associations in order to assess the evolutionary dynamics of cooperation in spatially structured populations.

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