scholarly journals Generalized stacked contact process with variable host fitness

2020 ◽  
Vol 57 (1) ◽  
pp. 97-121
Author(s):  
Eric Foxall ◽  
Nicolas Lanchier
Keyword(s):  
Spatial Model ◽  
Birth Rate ◽  
Interacting Particle Systems ◽  
Contact Process ◽  
Mean Field ◽  
Field Approximation ◽  
Host Population ◽  
Mean Field Approximation ◽  
Mean Field Model ◽  
State Spin

AbstractThe stacked contact process is a three-state spin system that describes the co-evolution of a population of hosts together with their symbionts. In a nutshell, the hosts evolve according to a contact process while the symbionts evolve according to a contact process on the dynamic subset of the lattice occupied by the host population, indicating that the symbiont can only live within a host. This paper is concerned with a generalization of this system in which the symbionts may affect the fitness of the hosts by either decreasing (pathogen) or increasing (mutualist) their birth rate. Standard coupling arguments are first used to compare the process with other interacting particle systems and deduce the long-term behavior of the host–symbiont system in several parameter regions. The spatial model is also compared with its mean-field approximation as studied in detail by Foxall (2019). Our main result focuses on the case where unassociated hosts have a supercritical birth rate whereas hosts associated to a pathogen have a subcritical birth rate. In this case, the mean-field model predicts coexistence of the hosts and their pathogens provided the infection rate is large enough. For the spatial model, however, only the hosts survive on the one-dimensional integer lattice.

scholarly journals Mean field approximation of network of biophysical neurons driven by conductance-based ion exchange dynamics

2021 ◽  
Author(s):  
Abhirup Bandyopadhyay ◽  
Spase Petkoski ◽  
Viktor Jirsa
Keyword(s):  
Ion Exchange ◽  
Molecular Mechanisms ◽  
Field Model ◽  
Mean Field ◽  
Field Approximation ◽  
Mean Field Approximation ◽  
Mean Field Model ◽  
Ion Concentrations ◽  
The Mean ◽  
Locally Homogeneous

Changes in extracellular ion concentrations are known to modulate neuronal excitability and play a major role in controlling the neuronal firing rate, not just during the healthy homeostasis, but also in pathological conditions such as epilepsy. The microscopic molecular mechanisms of field effects are understood, but the precise correspondence between the microscopic mechanisms of ion exchange in the cellular space of neurons and the macroscopic behavior of neuronal populations remains to be established. We derive a mean field model of a population of Hodgkin Huxley type neurons. This model links the neuronal intra- and extra-cellular ion concentrations to the mean membrane potential and the mean synaptic input in terms of the synaptic conductance of the locally homogeneous mesoscopic network and can describe various brain activities including multi-stability at resting states, as well as more pathological spiking and bursting behaviors, and depolarizations. The results from the analytical solution of the mean field model agree with the mean behavior of numerical simulations of large-scale networks of neurons. The mean field model is analytically exact for non-autonomous ion concentration variables and provides a mean field approximation in the thermodynamic limit, for locally homogeneous mesoscopic networks of biophysical neurons driven by an ion exchange mechanism. These results may provide the missing link between high-level neural mass approaches which are used in the brain network modeling and physiological parameters that drive the neuronal dynamics.

scholarly journals Stochastic Spatial Model of Producer-Consumer Systems on the Lattice

2013 ◽  
Vol 45 (4) ◽  
pp. 1157-1181 ◽  
Author(s):  
N. Lanchier
Keyword(s):  
Spatial Model ◽  
Initial Density ◽  
Mean Field ◽  
Field Approximation ◽  
Square Lattice ◽  
Mean Field Approximation ◽  
Ecological Communities ◽  
Parameter Region ◽  
Dominant Type ◽  
The Individual

The objective of this paper is to give a rigorous analysis of a stochastic spatial model of producer-consumer systems that has been recently introduced by Kang and the author to understand the role of space in ecological communities in which individuals compete for resources. Each point of the square lattice is occupied by an individual which is characterized by one of two possible types, and updates its type in continuous time at rate 1. Each individual being thought of as a producer and consumer of resources, the new type at each update is chosen at random from a certain interaction neighborhood according to probabilities proportional to the ability of the neighbors to consume the resource produced by the individual to be updated. In addition to giving a complete qualitative picture of the phase diagram of the spatial model, our results indicate that the nonspatial deterministic mean-field approximation of the stochastic process fails to describe the behavior of the system in the presence of local interactions. In particular, we prove that, in the parameter region where the nonspatial model displays bistability, there is a dominant type that wins regardless of its initial density in the spatial model, and that the inclusion of space also translates into a significant reduction of the parameter region where both types coexist.

Dynamical Mean Field Model of a Neural-Glial Mass

2010 ◽  
Vol 22 (4) ◽  
pp. 969-997 ◽  
Author(s):  
Roberto C. Sotero ◽  
Ramón Martínez-Cancino
Keyword(s):  
Differential Equations ◽  
Field Model ◽  
Mean Field ◽  
Field Approximation ◽  
Presynaptic Terminal ◽  
Mean Field Approximation ◽  
Nerve Terminals ◽  
Mean Field Model ◽  
Wide Range ◽  
Activity Dependent

Our goal is to model the behavior of an ensemble of interacting neurons and astrocytes (the neural-glial mass). For this, a model describing N tripartite synapses is proposed. Each tripartite synapse consists of presynaptic and postsynaptic nerve terminals, as well as the synaptically associated astrocytic microdomain, and is described by a system of 13 stochastic differential equations. Then, by applying the dynamical mean field approximation (DMA) (Hasegawa, 2003a , 2003b ) the system of 13N equations is reduced to 13(13 + 2) = 195 deterministic differential equations for the means and the second-order moments of local and global variables. Simulations are carried out for studying the response of the neural-glial mass to external inputs applied to either the presynaptic terminals or the astrocytes. Three cases were considered: the astrocytes influence only the presynaptic terminal, only the postsynaptic terminal, or both the presynaptic and postsynaptic terminals. As a result, a wide range of responses varying from singles spikes to train of spikes was evoked on presynaptic and postsynaptic terminals. The experimentally observed phenomenon of spontaneous activity in astrocytes was replicated on the neural-glial mass. The model predicts that astrocytes can have a strong and activity-dependent influence on synaptic transmission. Finally, simulations show that the dynamics of astrocytes influences the synchronization ratio between neurons, predicting a peak in the synchronization for specific values of the astrocytes’ parameters.

scholarly journals The structure of musical harmony as an ordered phase of sound: A statistical mechanics approach to music theory

2019 ◽  
Vol 5 (5) ◽  
pp. eaav8490 ◽  
Author(s):  
Jesse Berezovsky
Keyword(s):  
Phase Transitions ◽  
Statistical Mechanics ◽  
Music Theory ◽  
Mean Field ◽  
Field Approximation ◽  
Mean Field Approximation ◽  
Mean Field Model ◽  
Musical Harmony ◽  
Emergent Order ◽  
The Mean

Music, while allowing nearly unlimited creative expression, almost always conforms to a set of rigid rules at a fundamental level. The description and study of these rules, and the ordered structures that arise from them, is the basis of the field of music theory. Here, I present a theoretical formalism that aims to explain why basic ordered patterns emerge in music, using the same statistical mechanics framework that describes emergent order across phase transitions in physical systems. I first apply the mean field approximation to demonstrate that phase transitions occur in this model from disordered sound to discrete sets of pitches, including the 12-fold octave division used in Western music. Beyond the mean field model, I use numerical simulation to uncover emergent structures of musical harmony. These results provide a new lens through which to view the fundamental structures of music and to discover new musical ideas to explore.

scholarly journals Stochastic Spatial Model of Producer-Consumer Systems on the Lattice

2013 ◽  
Vol 45 (04) ◽  
pp. 1157-1181 ◽  
Author(s):  
N. Lanchier
Keyword(s):  
Spatial Model ◽  
Initial Density ◽  
Mean Field ◽  
Field Approximation ◽  
Square Lattice ◽  
Mean Field Approximation ◽  
Ecological Communities ◽  
Parameter Region ◽  
Dominant Type ◽  
The Individual

The objective of this paper is to give a rigorous analysis of a stochastic spatial model of producer-consumer systems that has been recently introduced by Kang and the author to understand the role of space in ecological communities in which individuals compete for resources. Each point of the square lattice is occupied by an individual which is characterized by one of two possible types, and updates its type in continuous time at rate 1. Each individual being thought of as a producer and consumer of resources, the new type at each update is chosen at random from a certain interaction neighborhood according to probabilities proportional to the ability of the neighbors to consume the resource produced by the individual to be updated. In addition to giving a complete qualitative picture of the phase diagram of the spatial model, our results indicate that the nonspatial deterministic mean-field approximation of the stochastic process fails to describe the behavior of the system in the presence of local interactions. In particular, we prove that, in the parameter region where the nonspatial model displays bistability, there is a dominant type that wins regardless of its initial density in the spatial model, and that the inclusion of space also translates into a significant reduction of the parameter region where both types coexist.

PHASE DIAGRAMS AND CORRELATION INEQUALITIES OF A THREE-STATE STOCHASTIC EPIDEMIC MODEL ON THE SQUARE LATTICE

2006 ◽  
Vol 16 (12) ◽  
pp. 3687-3693 ◽  
Author(s):  
KAZUMICHI OHTSUKA ◽  
NORIO KONNO ◽  
NAOKI MASUDA ◽  
KAZUYUKI AIHARA
Keyword(s):  
Particle System ◽  
Contact Process ◽  
Mean Field ◽  
Field Approximation ◽  
Correlation Inequalities ◽  
Square Lattice ◽  
Mean Field Approximation ◽  
Pair Approximation ◽  
Stochastic Particle System ◽  
Stochastic Epidemic

We study a three-state stochastic particle system on the square lattice, which extends the contact process. The phase diagram is analyzed by the mean-field approximation, the pair approximation, and numerics. The pair approximation turns out to be better than the meanfield ansatz. We also show that the Harris-FKG type correlation inequalities approximately hold in the present model.

scholarly journals Methods of modelling viral disease dynamics across the within- and between-host scales: the impact of virus dose on host population immunity

2010 ◽  
Vol 365 (1548) ◽  
pp. 1931-1941 ◽  
Author(s):  
Shelby H. Steinmeyer ◽  
Claus O. Wilke ◽  
Kim M. Pepin
Keyword(s):  
Mean Field ◽  
Viral Disease ◽  
Field Approximation ◽  
Equation Model ◽  
Host Population ◽  
Model Complexity ◽  
Mean Field Approximation ◽  
Virus Dose ◽  
The Impact ◽  
Dose Dependent

We study the epidemiology of a viral disease with dose-dependent replication and transmission by nesting a differential-equation model of the within-host viral dynamics inside a between-host epidemiological model. We use two complementary approaches for nesting the models: an agent-based (AB) simulation and a mean-field approximation called the growth-matrix (GM) model. We find that although infection rates and predicted case loads are somewhat different between the AB and GM models, several epidemiological parameters, e.g. mean immunity in the population and mean dose received, behave similarly across the methods. Further, through a comparison of our dose-dependent replication model against two control models that uncouple dose-dependent replication from transmission, we find that host immunity in a population after an epidemic is qualitatively different than when transmission depends on time-varying viral abundances within hosts. These results show that within-host dynamics and viral dose should not be neglected in epidemiological models, and that the simpler GM approach to model nesting provides a reasonable tradeoff between model complexity and accuracy of results.

scholarly journals Relativistic Mean-Field Approximation with Density-Dependent Screening Meson Masses in Nuclear Matter

2003 ◽  
Vol 12 (04) ◽  
pp. 543-554 ◽  
Author(s):  
Bao-Xi Sun ◽  
Xiao-Fu Lu ◽  
Peng-Nian Shen ◽  
En-Guang Zhao
Keyword(s):  
Nuclear Matter ◽  
Field Model ◽  
Mean Field ◽  
Field Approximation ◽  
Mean Field Approximation ◽  
Mean Field Model ◽  
Density Dependent ◽  
Relativistic Mean Field ◽  
Saturation Properties ◽  
The Masses

The Debye screening masses of the σ, ω and neutral ρ mesons and the photon are calculated in the relativistic mean-field approximation. As the density of the nucleon increases, all the screening masses of mesons increase. A different result with Brown–Rho scaling is shown, which implies a reduction in the mass of all the mesons in the nuclear matter, except the pion. Replacing the masses of the mesons with their corresponding screening masses in the Walecka-1 model, five saturation properties of the nuclear matter are fixed reasonably, and then a density-dependent relativistic mean-field model is proposed without introducing the nonlinear self-coupling terms of mesons.

The Determination of the Magnetoelectric Coupling Coefficient in Ferroelectric–Ferromagnetic Composite Based on PZT–Ferrite

2013 ◽  
Vol 58 (4) ◽  
pp. 1401-1403 ◽  
Author(s):  
J.A. Bartkowska ◽  
R. Zachariasz ◽  
D. Bochenek ◽  
J. Ilczuk
Keyword(s):  
Dielectric Permittivity ◽  
Coupling Coefficient ◽  
Mean Field ◽  
Field Approximation ◽  
Theoretical Description ◽  
Magnetoelectric Coupling ◽  
Mean Field Approximation ◽  
Dielectric Measurements ◽  
Temperature Dependences ◽  
Multiferroic Composite

Abstract In the present work, the magnetoelectric coupling coefficient, from the temperature dependences of the dielectric permittivity for the multiferroic composite was determined. The research material was ferroelectric-ferromagnetic composite on the based PZT and ferrite. We investigated the temperature dependences of the dielectric permittivity (") for the different frequency of measurement’s field. From the dielectric measurements we determined the temperature of phase transition from ferroelectric to paraelectric phase. For the theoretical description of the temperature dependence of the dielectric constant, the Hamiltonian of Alcantara, Gehring and Janssen was used. To investigate the dielectric properties of the multiferroic composite this Hamiltonian was expressed under the mean-field approximation. Based on dielectric measurements and theoretical considerations, the values of the magnetoelectric coupling coefficient were specified.

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