Narrow Results

A Consensus Model according to Deffuant on a directed Barabási–Albert network was simulated. Agents have opinions on different subjects. A multi-component subject vector was used. The opinions are discrete. The analysis concerns distribution and clusters of agents which are in agreement with the opinions of the subjects. Remarkable results shown that there mostly exists no absolute consensus. It depends on the ratio of number of agents to the number of subjects, whether the communication ends in a consensus or a pluralism. Mostly a second robust cluster remains, in its size depending on the number of subjects. Two agents agree either in (nearly) all or (nearly) no subject. The operative parameter of the consensus-formating-process is the tolerance in change of views of the group-members.

This paper treats the opinion dynamics of an unequal, initial opinion distribution. We simulate the Deffuant model on a directed Barabási–Albert network with discrete opinions and several subjects. We notice a focusing of the the resulting opinion distribution during the simulation towards the average value of the initial opinion distribution. A small change of the focusing is seen. A dependency of this change on the number of subjects and opinions is detected and indicates the change as a consequence of discretization of the opinions. Hereby the average value of the initial opinion distribution can be identified as the guide of opinion forming.

For most of the important processes in DNA metabolism, a protein has to reach a specific binding site on the DNA. The specific binding site may consist of just a few base-pairs while the DNA is usually several millions of base-pairs long. How does the protein search for the target site? What is the most efficient mechanism for a successful search? Motivated by these fundamental questions on intracellular biological processes, we have developed a model for searching a specific site on a model DNA by a single protein. We have made a comparative quantitative study on the efficiencies of sliding, inter-segmental hoppings and detachment/re-attachments of the particle during its search for the specific site on the DNA. We also introduce some new quantitative measures of efficiency of a search process by defining a relevant quantity, which can be measured in in-vitro experiments.

A model of opinion dynamics with two types of agents as social actors are presented, using the Ising thermodynamic model as the dynamics template. The agents are considered as opportunists which live at sites and interact with the neighbors, or fanatics/missionaries which move from site to site randomly in persuasion of converting agents of opposite opinion with the help of opportunists. Here, the moving agents act as an external influence on the opportunists to convert them to the opposite opinion. It is shown by numerical simulations that such dynamics of opinion formation may explain some details of consensus formation even when one of the opinions are held by a minority. Regardless the distribution of the opinion, different size societies exhibit different opinion formation behavior and time scales. In order to understand general behavior, the scaling relations obtained by comparing opinion formation processes observed in societies with varying population and number of randomly moving agents are studied. For the proposed model two types of scaling relations are observed. In fixed size societies, increasing the number of randomly moving agents give a scaling relation for the time scale of the opinion formation process. The second type of scaling relation is due to the size dependent information propagation in finite but large systems, namely finite-size scaling.

The asymmetric simple exclusion process (ASEP) is a paradigmatic model for nonequilibrium systems and has been used in many applications. Airplane boarding provides another interesting example where this framework can be applied. We propose a simple model for boarding process, in which a particle moves along a one-dimensional aisle after being injected, and finally is removed at a reserved site. Different from the typical ASEP model, particles are removed in a disorderly or a parallel way. Detailed calculations and discussions of some related characteristics, such as mean boarding time and parallelism indicator, are provided based on Monte-Carlo simulations. Results show that three phases exist in the boarding process: free-flow, jamming and maximum current. Transitions between these phases are governed by the difference between the injection and removal rate. Further analysis shows how the scaling behavior depends on the system size and the boarding conditions. Those results emphasize the importance of utilizing the whole length of the aisle to reduce the boarding time when designing an efficient boarding strategy.

A Monte Carlo algorithm for partitioning graphs is presented. The algorithm is based on the self-organizing map, an unsupervised, competitive neural network. A mean-field analysis suggests that the complexity of the algorithm is at most is on the order of O(n³/|E|), where n is the number of vertices of the graph, and |E| the number of edges. This prediction is tested on a class of random graphs. Scaling laws that deviate from the mean-field prediction are obtained. Although the origin of these scaling laws is unclear, their consequences are discussed.

In this paper, the Vehicle Routing Problem with Stochastic Demands (VRPSD) is considered where customer demands are normally distributed. We propose a new model for computing the expected length of a tour. Monte Carlo simulation is used to demonstrate the accuracy of the model on randomly generated test problems. It is assumed that the service policy is non-divisible, meaning that the entire demand at each customer must be served in a single visit by a unique vehicle.

In this paper, by introducing the collision model of the K ion channel, the maximum value of ions inward the channel per second, the average velocity of ions in the channels and the average time of every ion passing through the channel are obtained. Moreover they are reconciled with the experimental data. Base on the experimental data, the empiristic potential function is deduced. With the Monte–Carlo simulation, the curve of average velocity versus time and average displacement versus time are calculated by resolving the over-damping Langevin equation with Gaussian-white noise. They are according with the experimental dada well.

Electron penetration in semi-infinite Au for normal and oblique angles of incidence at energies between 0.5 and 4 keV is simulated within a Monte-Carlo frame work. The elastic scattering cross sections have been obtained from a modified Rutherford differential cross section, whereas inelastic core and valence electron excitation are calculated using the Gryzinski's expression. The dependence of the backscattering coefficient, mean implantation depth and stopping profiles on the angle of incidence has been examined. These quantities are found to be significantly enhanced as the angle of incidence becomes higher which is generally in consistent with previous simulations.

We numerically investigated Mott transitions and mixing-demixing transitions in one-dimensional boson-fermion mixtures at a commensurate filling. The mixing-demixing transition occurred in a qualitatively similar manner to incommensurate filling cases. We also found the Mott insulator phase appeared in both the mixing and the demixing states as the fermion-boson interaction or the boson-boson interaction increased. Phase diagrams were obtained in interaction parameter space.

The electron transport of air in a uniform electric field is investigated by a Monte–Carlo simulation. The simulation results obtained are compared with the available data in the literature. The result of Monte–Carlo simulation shows that electron molecule collision cross sections adopted in the simulation result in good agreement with the experimental values over the range of E/N investigated (E is the electric field and N is the gas number density of background gas molecules).

We introduce a Monte–Carlo simulation approach to thermodynamic Bethe ansatz (TBA). We exemplify the method on one-particle integrable models, which include a free boson and a free fermions systems along with the scaling Lee–Yang model (SLYM). It is confirmed that the central charges and energies are correct to a very good precision, typically 0.1% or so. The advantage of the method is that it allows the calculation of all the dimensions and even the particular partition function.

By considering the effects of the space charges and domain boundaries in ferroelectric thin films, the thickness dependence of coercive field (E_c) is numerically simulated based on the four-state Potts model with the nearest-neighbor interactions between dipole moments. For large thickness, experimental results where E_c decreases with thickness can be produced from our Monte-Carlo simulation. On the other hand, when the thickness is very small, our simulation gets that E_c increases with thickness by the study of the polarization switching in the film. This gives an explanation of the experimental result by Zhu et al. in J. Appl. Phys.83, 1 (1998) for SBT-BTN film, and a similar report by Bune et al. in Nature391, 874 (1998) for the crystalline film. The critical temperature of the thin film is also discussed.

This paper describes a novel complementary metal oxide semiconductor (CMOS) bootstrapped driver circuit for driving large resistive capacitive (RC) loads. The proposed bootstrapped driver reduces the leakage as well as process, voltage and temperature (PVT) variations from the boosted nodes with higher switching speed. Very large scale integration (VLSI) designers need boosted output for the logic circuits which are operating in ultra-deep submicron regime under widespread use of low voltage. Proposed CMOS bootstrapped driver circuit is easy in design; built with minimum number of transistors and have high boosting efficiency with sharp output performance. Comparative evaluations with existing bootstrapped driver circuits are reported. Simulation results are derived by HSPICE tool with predictive technology model (PTM) bulk CMOS process fabrication at 32 nm technology node. The ability of large leakage reduction makes this driver superior as compared to active drivers. An average of 96.97% leakage current is saved at nominal ultra-low voltage of 0.15 V. Monte-Carlo analysis indicates that the proposed bootstrapped driver has less sensitivity of PVT variations. The power consumption and delay sensitivities are reduced by 10 × and 4.12 × as compared to conventional circuit.

The interaction of a mono-energetic neutron beam with a target layer of Boron-10 is studied to characterize the behavior of neutrons and produced charged particles inside the layer. The detection system is modeled through a Monte-Carlo simulation. The quality of the simulation method and controlling parameters is assessed with the response function. The Von Neumann rejection sampling method is used to model the interaction process. The obtained results show high agreement with previous results.

With the explosion of data on jet-based observables in relativistic heavy-ion collisions at the Large Hadron Collider and the Relativistic Heavy-Ion Collider, perturbative Quantum Chromodynamics (pQCD)-based simulations of these processes, often interacting with an expanding viscous fluid dynamical background, have taken center stage. This review is meant to bridge the gap between theory, simulation and phenomenology of jet modification in a dense medium. We will demonstrate how the existence of such end-to-end event generators with semi-realistic or even fully realistic final states allows for the most rigorous comparisons between pQCD-based jet modification theory and experiment. State-of-the-art calculations of several jet-based observables are presented. Extensions of this theory to jets in the small systems of p–A and e–A collisions are discussed.

The stochastic transition behavior of tri-stable states in a fractional-order generalized Van der Pol (VDP) system under multiplicative Gaussian white noise (GWN) excitation is investigated. First, according to the minimal mean square error (MMSE) concept, the fractional derivative can be equivalent to a linear combination of damping and restoring forces, and the original system can be simplified into an equivalent integer-order system. Secondly, the stationary Probability Density Function (PDF) of system amplitude is obtained by stochastic averaging, and based on singularity theory, the critical parameters for stochastic $P$-bifurcation of the system are found. Finally, the properties of stationary PDF curves of the system amplitude are qualitatively analyzed by choosing the corresponding parameters in each sub-region divided by the transition set curves. The consistency between numerical results obtained by Monte-Carlo simulation and analytical solutions verified the accuracy of the theoretical analysis process and the method used in this paper has a direct guidance in the design of fractional-order controller to adjust the system behavior.

Analysis of field failure data collected from various wind farm databases indicates that the power converters are among the most critical components in offshore wind turbines, since they suffer from a high failure rate. One efficient approach to enhance the reliability and availability of the wind power systems is through using a redundant converter design, in which a set of power converters is placed together in parallel. The main advantage of a multiple parallel converter system is that the failure of one converter will not necessarily lead to the failure of the entire system. It may however increase the wind turbine's acquisition cost, volume, and weight. In this paper, we propose an approach of joint redundancy and maintenance strategy optimization for offshore wind power converters, aiming to simultaneously determine the "optimal allocation of redundant converters" and the "optimal threshold number of converters that are allowed to fail before sending a maintenance crew to the offshore platform". The optimal solution under various system-level constraints (such as reliability, weight, and the available space in nacelle) is derived and the conditions required to make using a redundant system beneficial are discussed. The proposed design is applied to an offshore wind turbine system and its performance is evaluated using a Monte-Carlo simulation technique. Finally, the results are compared with the conventional power converter system and a sensitivity analysis is conducted in order to make the proposed approach applicable for the next generation of wind turbines.

In this paper, we present a generic method for the Monte-Carlo pricing of (generalized) auto-callable products (aka. trigger products), i.e., products for which the payout function features a discontinuity with a (possibly) stochastic location (the trigger) and value (the payout).

The Monte-Carlo pricing of products with discontinuous payout is known to come with a high Monte-Carlo error. The numerical calculation of sensitivities (i.e., partial derivatives) of such prices by finite differences gives very noisy results, since the Monte-Carlo approximation (being a finite sum of discontinuous functions) is not smooth. Additionally, the Monte-Carlo error of the finite-difference approximation explodes as the shift size tends to zero.

Our method combines a product specific modification of the underlying numerical scheme, which is to some extent similar to an importance sampling and/or partial proxy simulation scheme and a reformulation of the payoff function into an equivalent smooth payout.

From the financial product we merely require that hitting of the stochastic trigger will result in an conditionally analytic value. Many complex derivatives can be written in this form. A class of products where this property is usually encountered are the so called auto-callables, where a trigger hit results in cancellation of all future payments except for one redemption payment, which can be valued analytically, conditionally on the trigger hit.

From the model we require that its numerical implementation allows for a calculation of the transition probability of survival (i.e., non-trigger hit). Many models allows this, e.g., Euler schemes of Itô processes, where the trigger is a model primitive.

The method presented is effective across a large range of cases where other methods fail, e.g. small finite difference shift sizes or short time to trigger reset (approaching maturity); this means that a practitioner can use this method and be confident that it will work consistently.

The method itself can be viewed as a generalization of the method proposed by Glasserman and Staum (2001), both with respect to the type (and shape) of the boundaries, as well as, with respect to the class of products considered. In addition we explicitly consider the calculation of sensitivities.

We perform a Laplace transform inversion in the time parameter on the two Wiener-Hopf factors for a spectrally negative tempered stable Lévy process. This yields the issuing price of continuously monitored lookback options. We also propose a simulation technique for the purpose of Monte-Carlo valuation and discuss the convergence rate to continuous prices when the number of discretization steps (i.e. monitoring dates) goes to infinity.