Effect of long-range Coulomb interaction on shot-noise suppression in ballistic transport

We present a microscopic analysis of shot-noise suppression due to long-range Coulomb interaction in semiconductor devices under ballistic transport conditions. An ensemble Monte Carlo simulator self-consistently coupled with a Poisson solver is used for the calculations. A wide range of injection-rate densities leading to different degrees of suppression is investigated. A sharp tendency of noise suppression at increasing injection densities is found to scale with a dimensionless Debye length related to the importance of space-charge effects in the structure.

Universality of the 1/3 shot-noise suppression factor in nondegenerate diffusive conductors

Shot-noise suppression is investigated in nondegenerate diffusive conductors by means of an ensemble Monte Carlo simulator. The universal 1/3 suppression value is obtained when transport occurs under elastic collision regime provided the following conditions are satisfied: (i) The applied voltage is much larger than the thermal value; (ii) the length of the device is much greater than both the elastic mean free path and the Debye length. By fully suppressing carrier-number fluctuations, long-range Coulomb interaction is essential to obtain the 1/3 value in the low-frequency limit.

Local noise analysis of a Schottky contact: combined thermionic-emissiondiffusion theory

A theoretical model for the noise properties of Schottky barrier diodes in the framework of the thermionic-emission¿diffusion theory is presented. The theory incorporates both the noise inducedby the diffusion of carriers through the semiconductor and the noise induced by the thermionicemission of carriers across the metal¿semiconductor interface. Closed analytical formulas arederived for the junction resistance, series resistance, and contributions to the net noise localized indifferent space regions of the diode, all valid in the whole range of applied biases. An additionalcontribution to the voltage-noise spectral density is identified, whose origin may be traced back tothe cross correlation between the voltage-noise sources associated with the junction resistance andthose for the series resistance. It is argued that an inclusion of the cross-correlation term as a newelement in the existing equivalent circuit models of Schottky diodes could explain the discrepanciesbetween these models and experimental measurements or Monte Carlo simulations.

Impedance field and noise of submicrometer n+ nn+ diodes: analytical approach

A theoretical model for the noise properties of n+nn+ diodes in the drift-diffusion framework is presented. In contrast with previous approaches, our model incorporates both the drift and diffusive parts of the current under inhomogeneous and hot-carrier conditions. Closed analytical expressions describing the transport and noise characteristics of submicrometer n+nn+ diodes, in which the diode base (n part) and the contacts (n+ parts) are coupled in a self-consistent way, are obtained

Estrutura e propriedades de elipticinas

The ellipticines constitute a broad class of molecules with antitumor activity. In the present work we analyzed the structure and properties of a series of ellipticine derivatives in the gas phase and in solution using quantum mechanical and Monte Carlo methods. The results showed a good correlation between the solvation energies in water obtained with the continuum model and the Monte Carlo simulation. Molecular descriptors were considered in the development of QSAR models using the DNA association constant (log Kapp) as biological data. The results showed that the DNA binding is dominated by electronic parameters, with small contributions from the molecular volume and area.

Análise de imagem em química analítica: empregando metodologias simples e didáticas para entender e prevenir o escurecimento de tecidos vegetais

A simple and didactic experiment was developed for image monitoring of the browning of fruit tissues caused by the enzyme polyphenol oxidase. The procedure, easy and inexpensive, is a valuable tool to teach and demonstrate the redox reaction between the enzyme and the natural polyphenols. To obtain the browning percentage for apple, pear and banana, digital photographs were employed, and the images were analyzed by means of Monte Carlo methods and digital analysis programs. The effects of several experimental conditions were studied, such as pH, light, temperature and the presence of oxygen or anti-oxidants. It was observed that each fruit presented a different condition that better minimized the oxidation process. The absence of oxygen and the application of a bissulphite solution were sufficient to keep the quality of all fruits tested.

Probing quantum gravity using photons from a flare of the active galactic nucleus Markarian 501 observed by the MAGIC telescope

We analyze the timing of photons observed by the MAGIC telescope during a flare of the active galactic nucleus Mkn 501 for a possible correlation with energy, as suggested by some models of quantum gravity (QG), which predict a vacuum refractive index similar or equal to 1 + (E/M-QGn)(n), n = 1, 2. Parametrizing the delay between gamma-rays of different energies as Delta t = +/-tau E-1 or Delta t = +/-tau E-q(2), we find tau(1) = (0.030 +/- 0.012) s/GeV at the 2.5-sigma level, and tau(q) = (3.71 +/- 2.57) x 10(-6) s/GeV2, respectively. We use these results to establish lower limits M-QG1 > 0.21 X 10(18) GeV and M-QG2 > 0.26 x 10(11) GeV at the 95% C.L. Monte Carlo studies confirm the MAGIC sensitivity to propagation effects at these levels. Thermal plasma effects in the source are negligible, but we cannot exclude the importance of some other source effect.

Random walk radiosity with generalized absorption probabilities

The author studies random walk estimators for radiosity with generalized absorption probabilities. That is, a path will either die or survive on a patch according to an arbitrary probability. The estimators studied so far, the infinite path length estimator and finite path length one, can be considered as particular cases. Practical applications of the random walks with generalized probabilities are given. A necessary and sufficient condition for the existence of the variance is given, together with heuristics to be used in practical cases. The optimal probabilities are also found for the case when one is interested in the whole scene, and are equal to the reflectivities

Critical behavior in nonequilibrium phase transitions

The nonequilibrium phase transitions occurring in a fast-ionic-conductor model and in a reaction-diffusion Ising model are studied by Monte Carlo finite-size scaling to reveal nonclassical critical behavior; our results are compared with those in related models.

Statistical Analysis and Numerics of Heat Exchanger Models

The identifiability of the parameters of a heat exchanger model without phase change was studied in this Master’s thesis using synthetically made data. A fast, two-step Markov chain Monte Carlo method (MCMC) was tested with a couple of case studies and a heat exchanger model. The two-step MCMC-method worked well and decreased the computation time compared to the traditional MCMC-method. The effect of measurement accuracy of certain control variables to the identifiability of parameters was also studied. The accuracy used did not seem to have a remarkable effect to the identifiability of parameters. The use of the posterior distribution of parameters in different heat exchanger geometries was studied. It would be computationally most efficient to use the same posterior distribution among different geometries in the optimisation of heat exchanger networks. According to the results, this was possible in the case when the frontal surface areas were the same among different geometries. In the other cases the same posterior distribution can be used for optimisation too, but that will give a wider predictive distribution as a result. For condensing surface heat exchangers the numerical stability of the simulation model was studied. As a result, a stable algorithm was developed.

TitGer: uma planilha eletrônica para simulação de titulação de mistura de compostos polipróticos

The aim of this paper is to present a simple way of treating the general equation for acid-base titrations based on the concept of degree of dissociation, and to propose a new spreadsheet approach for simulating the titration of mixtures of polyprotic compounds. The general expression, without any approximation, is calculated a simple iteration method, making number manipulation easy and painless. The user-friendly spreadsheet was developed by using MS-Excel and Visual-Basic-for-Excel. Several graphs are drawn for helping visualizing the titration behavior. A Monte Carlo function for error simulation was also implemented. Two examples for titration of alkalinity and McIlvaine buffer are presented.

Indirect likelihood inference (revised)

Standard indirect Inference (II) estimators take a given finite-dimensional statistic, Z_{n} , and then estimate the parameters by matching the sample statistic with the model-implied population moment. We here propose a novel estimation method that utilizes all available information contained in the distribution of Z_{n} , not just its first moment. This is done by computing the likelihood of Z_{n}, and then estimating the parameters by either maximizing the likelihood or computing the posterior mean for a given prior of the parameters. These are referred to as the maximum indirect likelihood (MIL) and Bayesian Indirect Likelihood (BIL) estimators, respectively. We show that the IL estimators are first-order equivalent to the corresponding moment-based II estimator that employs the optimal weighting matrix. However, due to higher-order features of Z_{n} , the IL estimators are higher order efficient relative to the standard II estimator. The likelihood of Z_{n} will in general be unknown and so simulated versions of IL estimators are developed. Monte Carlo results for a structural auction model and a DSGE model show that the proposed estimators indeed have attractive finite sample properties.

Ratiomuuttujat ja näennäinen korrelaatio

Eri tieteenalojen tutkijat ovat kiistelleet jo yli vuosisadan ajan ratiomuodossa olevien muuttujien käytön vaikutuksista korrelaatio- ja regressioanalyysien tuloksiin ja niiden oikeaan tulkintaan. Strategiatutkimuksen piirissä aiheeseen ei ole kuitenkaan kiinnitetty suuresti huomiota. Tämä on yllättävää, sillä ratiomuuttujat ovat hyvin yleisesti käytettyjä empiirisen strategiatutkimuksen piirissä. Tässä työssä luodaan katsaus ratiomuuttujien ympärillä käytyyn debattiin. Lisäksi selvitetään artikkelikatsauksen avulla niiden käytön yleisyyttä nykypäivän strategiatutkimuksessa. Työssä tutkitaan Monte Carlo –simulaatioiden avulla ratiomuuttujien ominaisuuksien vaikutuksia korrelaatio- ja regressioanalyysin tuloksiin erityisesti yhteisen nimittäjän tapauksissa.

Validação da metodologia da avaliação de incerteza em curvas de calibração melhor ajustadas por polinômios de segundo grau

The most widespread literature for the evaluation of uncertainty - GUM and Eurachem - does not describe explicitly how to deal with uncertainty of the concentration coming from non-linear calibration curves. This work had the objective of describing and validating a methodology, as recommended by the recent GUM Supplement approach, to evaluate the uncertainty through polynomial models of the second order. In the uncertainty determination of the concentration of benzatone (C) by chromatography, it is observed that the uncertainty of measurement between the methodology proposed and Monte Carlo Simulation, does not diverge by more than 0.0005 unit, thus validating the model proposed for one significant digit.

MCMC Analysis Of Classical Time Series Algorithms

Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.