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M. Reza Rahimi Tabar

Publications and source records attributed to M. Reza Rahimi Tabar.

At least 37 records · Page 2Linked to original sources

Molecular Dynamics Simulation of Folding and Diffusion of Proteins in Nanopores

A novel combination of discontinuous molecular dynamics and the Langevin equation, together with an intermediate-resolution model, are used to carry out long (several $μ$s) simulation and study folding transition and transport of proteins in slit nanopores. Both attractive ($U^+$) and repulsive ($U^-$) interaction potentials between the proteins and the pore walls are considered. Near the folding temperature $T_f$ and in the presence of $U^+$ the proteins undergo a repeating sequence of folding/partially-folding/ unfolding transitions, while $T_f$ decreases with decreasing pore sizes. The opposite is true when $U^-$ is present. The proteins' effective diffusivity $D$ is computed as a function of their length (number of the amino acid groups), temperature $T$, the pore size, and the interaction potentials $U^\pm$. Far from $T_f$, $D$ increases (roughly) linearly with $T$, but due to the thermal fluctuations and their effect on the proteins' structure near $T_f$, the dependence of $D$ on $T$ in this region is nonlinear. Under certain conditions, transport of proteins in smaller pores can be {\it faster} than that in larger pores.

cond-mat.soft↗

Roughness of undoped graphene and its short-range induced gauge field

We present both numerical and analytical study of graphene roughness with a crystal structure including $500 \times 500$ atoms. The roughness can effectively result in a random gauge field and has important consequences for its electronic structure. Our results show that its height fluctuations in small scales have scaling behavior with a temperature dependent roughness exponent in the interval of $ 0.6 < χ< 0.7 $. The correlation function of height fluctuations depends upon temperature with characteristic length scale of $ \approx 90 Å$ (at room temperature). We show that the correlation function of the induced gauge field has a short-range nature with correlation length of about $\simeq 2-3 Å$. We also treat the problem analytically by using the Martin-Siggia-Rose method. The renormalization group flows did not yield any delocalized-localized transition arising from the graphene roughness. Our results are in good agreement with recent experimental observations.

cond-mat.mtrl-sci↗

Uncertainty in the Fluctuations of the Price of Stocks

We report on a study of the Tehran Price Index (TEPIX) from 2001 to 2006 as an emerging market that has been affected by several political crises during the recent years, and analyze the non-Gaussian probability density function (PDF) of the log returns of the stocks' prices. We show that while the average of the index did not fall very much over the time period of the study, its day-to-day fluctuations strongly increased due to the crises. Using an approach based on multiplicative processes with a detrending procedure, we study the scale-dependence of the non-Gaussian PDFs, and show that the temporal dependence of their tails indicates a gradual and systematic increase in the probability of the appearance of large increments in the returns on approaching distinct critical time scales over which the TEPIX has exhibited maximum uncertainty.

q-fin.ST↗

Etched Glass Surfaces, Atomic Force Microscopy and Stochastic Analysis

The effect of etching time scale of glass surface on its statistical properties has been studied using atomic force microscopy technique. We have characterized the complexity of the height fluctuation of a etched surface by the stochastic parameters such as intermittency exponents, roughness, roughness exponents, drift and diffusion coefficients and find their variations in terms of the etching time.

physics.data-an↗

Controlling surface statistical properties using bias voltage: Atomic force microscopy and stochastic analysis

The effect of bias voltages on the statistical properties of rough surfaces has been studied using atomic force microscopy technique and its stochastic analysis. We have characterized the complexity of the height fluctuation of a rough surface by the stochastic parameters such as roughness exponent, level crossing, and drift and diffusion coefficients as a function of the applied bias voltage. It is shown that these statistical as well as microstructural parameters can also explain the macroscopic property of a surface. Furthermore, the tip convolution effect on the stochastic parameters has been examined.

physics.data-an↗

Stochastic $ϕ^4-$Theory in the Strong Coupling Limit

The stochastic $ϕ^4$-theory in $d-$dimensions dynamically develops domain wall structures within which the order parameter is not continuous. We develop a statistical theory for the $ϕ^4$-theory driven with a random forcing which is white in time and Gaussian-correlated in space. A master equation is derived for the probability density function (PDF) of the order parameter, when the forcing correlation length is much smaller than the system size, but much larger than the typical width of the domain walls. Moreover, exact expressions for the one-point PDF and all the moments $<ϕ^n>$ are given. We then investigate the intermittency issue in the strong coupling limit, and derive the tail of the PDF of the increments $ϕ(x_2) - ϕ(x_1)$. The scaling laws for the structure functions of the increments are obtained through numerical simulations. It is shown that the moments of field increments defined by, $C_b=< |ϕ(x_2)-ϕ(x_1)|^b>$, behave as $|x_1-x_2|^{ξ_b}$, where $ξ_b=b$ for $b\leq 1$, and $ξ_b=1$ for $b\geq1$

cond-mat.other↗

Characteristic Angular Scales in Cosmic Microwave Background Radiation

We investigate the stochasticity in temperature fluctuations in the cosmic microwave background (CMB) radiation data from {\it Wilkinson Microwave Anisotropy Probe}. We show that the angular fluctuations of the temperature is a Markov process with a {\it Markov angular scale}, $Θ_{\rm Markov}=1.01^{+0.09}_{-0.07}$. We characterize the complexity of the CMB fluctuations by means of a Fokker-Planck or Langevin equation and measure the associated Kramers-Moyal coefficients for the fluctuating temperature field $T(\hat n)$ and its increment, $ΔT =T(\hat n_1) - T(\hat n_2)$. Through this method we show that temperature fluctuations in the CMB has fat tails compared to a Gaussian distribution.

astro-ph↗

Level Crossing Analysis of the Stock Markets

We investigate the average frequency of positive slope $ν_α^{+}$, crossing for the returns of market prices. The method is based on stochastic processes which no scaling feature is explicitly required. Using this method we define new quantity to quantify stage of development and activity of stocks exchange. We compare the Tehran and western stock markets and show that some stocks such as Tehran (TEPIX) and New Zealand (NZX) stocks exchange are emerge, and also TEPIX is a non-active market and financially motivated to absorb capital.

physics.data-an↗

A water film motor

We report on electrically-induced rotations in water films, which can function at many length scales. The device consists of a two-dimensional cell used for electrolysis of water films, as simple as an insulator frame with two electrodes on the sides, to which an external in-plane electric field perpendicular to the mean electrolysis current density is applied. If either the external field or the electrolysis current exceeds some threshold (while the other one is not zero), the liquid film begins to rotate.

cond-mat.soft↗

Analysis of Non-stationary Data for Heart-Rate Fluctuations in Terms of Drift and Diffusion Coefficients

We describe a method for analyzing the stochasticity in the non-stationary data for the beat-to-beat fluctuations in the heart rates of healthy subjects, as well as those with congestive heart failure. The method analyzes the returns time series of the data as a Markov process, and computes the Markov time scale, i.e., the time scale over which the data are a Markov process. We also construct an effective stochastic continuum equation for the return series. We show that the drift and diffusion coefficients, as well as the amplitude of the returns time series for healthy subjects are distinct from those with CHF. Thus, the method may potentially provide a diagnostic tool for distinguishing healthy subjects from those with congestive heart failure, as it can distinguish small differences between the data for the two classes of subjects in terms of well-defined and physically-motivated quantities.

physics.bio-ph↗

Multifractal Detrended Fluctuation Analysis of Sunspot Time Series

We use multifractal detrended fluctuation analysis (MF-DFA), to See query 1 study sunspot number fluctuations. The result of the MF-DFA shows that there are three crossover timescales in the fluctuation function. We discuss how the existence of the crossover timescales is related to a sinusoidal trend. Using Fourier detrended fluctuation analysis, the sinusoidal trend is eliminated. The Hurst exponent of the time series without the sinusoidal trend is $0.12\pm 0.01$. Also we find that these fluctuations have multifractal nature. Comparing the MF-DFA results for the remaining data set to those for shuffled and surrogate series, we conclude that its multifractal nature is almost entirely due to long range correlations.

physics.data-an↗

New Computational Approaches to Analysis of Interbeat Intervals in Human Subjects

We investigate the Markov nature, Cascade of information from large time scale to small scale and extended self similarity properties of the beat to beat fluctuations of healthy subjects as well as those with congestive heart failure. To check the Markov nature, we use a novel inverse method that utilizes a set of data to construct a simple equation that governs the stochastic process for which the data have been measured, hence enabling us to reconstruct the stochastic process. The inverse method provides a novel technique for distinguishing the two classes of subjects in terms of a drift and a diffusion coefficients which behave completely differently for the two classes of subjects.To investigate the cascade of information from large to small time scales we also analyze the statistical properties of interbeat intervals cascade by considering the joint probability distribution for two interbeat increments. As a result, the joint probability distributions of the increments in the interbeat intervals obey a Fokker-Planck equation. Finally we analyze the extended self-similarity (ESS) in the beat-to-beat fluctuations in the heart rates of healthy and congestive heart failure subjects.The proposed methods provide the novel techniques for distinguishing the two classes of subjects in terms of the drift and diffusion coefficients, intermittency exponents which behave differently for two classes of the subjects, namely, healthy subjects and those with congestive heart failure.

q-bio.QM↗

Statistical Properties of the Interbeat Interval Cascade in Human Subjects

Statistical properties of interbeat intervals cascade are evaluated by considering the joint probability distribution $P(Δx_2,τ_2;Δx_1,τ_1)$ for two interbeat increments $Δx_1$ and $Δx_2$ of different time scales $τ_1$ and $τ_2$. We present evidence that the conditional probability distribution $P(Δx_2,τ_2|Δx_1,τ_1)$ may obey a Chapman-Kolmogorov equation. The corresponding Kramers-Moyal (KM) coefficients are evaluated. It is shown that while the first and second KM coefficients, i.e., the drift and diffusion coefficients, take on well-defined and significant values, the higher-order coefficients in the KM expansion are very small. As a result, the joint probability distributions of the increments in the interbeat intervals obey a Fokker-Planck equation. The method provides a novel technique for distinguishing the two classes of subjects in terms of the drift and diffusion coefficients, which behave differently for two classes of the subjects, namely, healthy subjects and those with congestive heart failure.

q-bio.QM↗

Regeneration of Stochastic Processes: An Inverse Method

We propose a novel inverse method that utilizes a set of data to construct a simple equation that governs the stochastic process for which the data have been measured, hence enabling us to reconstruct the stochastic process. As an example, we analyze the stochasticity in the beat-to-beat fluctuations in the heart rates of healthy subjects as well as those with congestive heart failure. The inverse method provides a novel technique for distinguishing the two classes of subjects in terms of a drift and a diffusion coefficients which behave completely differently for the two classes of subjects, hence potentially providing a novel diagnostic tool for distinguishing healthy subjects from those with congestive heart failure, even at the early stages of the disease development.

cond-mat.stat-mech↗

Dynamics of the Markov Time Scale of Seismic Activity May Provide a Short-Term Alert for Earthquakes

We propose a novel method for analyzing precursory seismic data before an earthquake that treats them as a Markov process and distinguishes the background noise from real fluctuations due to an earthquake. A short time (on the order of several hours) before an earthquake the Markov time scale $t_M$ increases sharply, hence providing an alarm for an impending earthquake. To distinguish a false alarm from a reliable one, we compute a second quantity, $T_1$, based on the concept of extended self-similarity of the data. $T_1$ also changes strongly before an earthquake occurs. An alarm is accepted if {\it both} $t_M$ and $T_1$ indicate it {\it simultaneously}. Calibrating the method with the data for one region provides a tool for predicting an impending earthquake within that region. Our analysis of the data for a large number of earthquakes indicate an essentially zero rate of failure for the method.

physics.geo-ph↗

Zero tension Kardar-Parisi-Zhang equation in (d+1)- Dimensions

The joint probability distribution function (PDF) of the height and its gradients is derived for a zero tension $d+1$-dimensional Kardar-Parisi-Zhang (KPZ) equation. It is proved that the height`s PDF of zero tension KPZ equation shows lack of positivity after a finite time $t_{c}$. The properties of zero tension KPZ equation and its differences with the case that it possess an infinitesimal surface tension is discussed. Also potential relation between the time scale $t_{c}$ and the singularity time scale $t_{c, ν\to 0}$ of the KPZ equation with an infinitesimal surface tension is investigated.

nlin.CD↗

Intermittency of Height Fluctuations and Velocity Increment of The Kardar-Parisi-Zhang and Burgers Equations with infinitesimal surface tension and Viscosity in 1+1 Dimensions

The Kardar-Parisi-Zhang (KPZ) equation with infinitesimal surface tension, dynamically develops sharply connected valley structures within which the height derivative is not continuous. We discuss the intermittency issue in the problem of stationary state forced KPZ equation in 1+1--dimensions. It is proved that the moments of height increments $C_a = < | h (x_1) - h (x_2) |^a > $ behave as $ |x_1 -x_2|^{ξ_a}$ with $ξ_a = a$ for length scales $|x_1-x_2| << σ$. The length scale $σ$ is the characteristic length of the forcing term. We have checked the analytical results by direct numerical simulation.

physics.flu-dyn↗

Localization of elastic waves in heterogeneous media with off-diagonal disorder and long-range correlations

Using the Martin-Siggia-Rose method, we study propagation of acoustic waves in strongly heterogeneous media which are characterized by a broad distribution of the elastic constants. Gaussian-white distributed elastic constants, as well as those with long-range correlations with non-decaying power-law correlation functions, are considered. The study is motivated in part by a recent discovery that the elastic moduli of rock at large length scales may be characterized by long-range power-law correlation functions. Depending on the disorder, the renormalization group (RG) flows exhibit a transition to localized regime in {\it any} dimension. We have numerically checked the RG results using the transfer-matrix method and direct numerical simulations for one- and two-dimensional systems, respectively.

cond-mat.stat-mech↗