Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userMonotonicity in the averaging process
302
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
We investigate an averaging process that describes how interacting agents approach consensus through binary interactions. In each elementary step, two agents are selected at random and they reach compromise by adopting their opinion average. We show that the fraction of agents with a monotonically decreasing opinion decays as $e^{-alpha t}$, and that the exponent $alpha=tfrac{1}{2}-tfrac{1+ln ln 2}{4ln 2}$ is selected as the extremum from a continuous spectrum of possible values. The opinion distribution of monotonic agents is asymmetric, and it becomes self-similar at large times. Furthermore, the tails of the opinion distribution are algebraic, and they are characterized by two distinct and nontrivial exponents. We also explore statistical properties of agents with an opinion strictly above average.
rate research
Read More
Stochastic processes are proposed whose master equations coincide with classical wave, telegraph, and Klein-Gordon equations. Similar to predecessors based on the Goldstein-Kac telegraph process, the model describes the motion of particles with constant speed and transitions between discreet allowed velocity directions. A new ingredient is that transitions into a given velocity state depend on spatial derivatives of other states populations, rather than on populations themselves. This feature requires the sacrifice of the single-particle character of the model, but allows to imitate the Huygens principle and to recover wave equations in arbitrary dimensions.
We present a treatment of non-Markovian character of memory by incorporating different forms of Mittag-Leffler (ML) function, which generally arises in the solution of fractional master equation, as different memory functions in the Generalized Kolmogorov-Feller Equation (GKFE). The cross-over from the short time (stretched exponential) to long time (inverse power law) approximations of the ML function incorporated in the GKFE is proven. We have found that the GKFE solutions are the same for negative exponential and for upto frst order expansion of stretched exponential function for very small $tau rightarrow 0$. A generalized integro-differential equation form of the GKFE along with an asymptotic case is provided.
Many dynamics are random processes with increments given by a quadratic form of a fast Gaussian process. We find that the rate function which describes path large deviations can be computed from the large interval asymptotic of a certain Fredholm determinant. The latter can be evaluated explicitly using Widoms theorem which generalizes the celebrated Szego-Kac formula to the multi-dimensional case. This provides a large class of dynamics with explicit path large deviation functionals. Inspired by problems in hydrodynamics and atmosphere dynamics, we present the simplest example of the emergence of metastability for such a process.
We study sample-to-sample fluctuations in a critical two-dimensional Ising model with quenched random ferromagnetic couplings. Using replica calculations in the renormalization group framework we derive explicit expressions for the probability distribution function of the critical internal energy and for the specific heat fluctuations. It is shown that the disorder distribution of internal energies is Gaussian, and the typical sample-to-sample fluctuations as well as the average value scale with the system size $L$ like $sim L lnln(L)$. In contrast, the specific heat is shown to be self-averaging with a distribution function that tends to a $delta$-peak in the thermodynamic limit $L to infty$. While previously a lack of self-averaging was found for the free energy, we here obtain results for quantities that are directly measurable in simulations, and implications for measurements in the actual lattice system are discussed.
We investigate, by means of extensive Monte Carlo simulations, the magnetic critical behavior of the three-dimensional bimodal random-field Ising model at the strong disorder regime. We present results in favor of the two-exponent scaling scenario, $bar{eta}=2eta$, where $eta$ and $bar{eta}$ are the critical exponents describing the power-law decay of the connected and disconnected correlation functions and we illustrate, using various finite-size measures and properly defined noise to signal ratios, the strong violation of self-averaging of the model in the ordered phase.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
