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Mohammad Reza
Rahimi Tabar
Professor of
Physics
Sharif University of Technology
--Contribution to Encyclopedia:
-- Importance of Fluctuations: Complexity in
the View of Stochastic Processes, R. Friedrich, J. Peinke and M.
Reza Rahimi Tabar, Contribution to Encyclopedia
of Complexity and System Science,
3574 ed. by B. Meyers (Springer Verlag Berlin, 2009)
--Book Chapters:
-- Short-Term
Prediction of Medium and Large-Size Earthquakes Based on Markov and Extended
Self-Similarity Analysis of Seismic Data , M. Reza Rahimi Tabar, Muhammad
Sahimi, K. Kaviani, M. Allamehzadeh, , J. Peinke, M. Mokhtari, M.
Vesaghi, M. D. Niry, F. Ghasemi, A. Bahraminasab, S. Tabatabai and F.
Fayazbakhsh., M. Akbari, in:Modeling Critical
and Catastrophic Phenomena in Geoscience: A Statistical Physics Approach, Lecture Notes in Physics, 705, pp. 281-301,
Springer Verlag, Berlin Heidelberg (2007) (Pdf)
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--List of Publications
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-- Selected
Publications:
_______________________________________________________________________________________________________________
1) Irreversibility in response to force acting on the graphene sheets, with N. Abedpour and R. Asgari, Phys. Rev. Lett. 104, 196804 (2010) (Pdf) The
amount of rippling in graphene sheets is related to the interactions with the
substrate or with the suspending structure. Here, we report on an
irreversibility in the response to forces that act on suspended graphene
sheets. This may explain why one always observes a ripple structure on
suspended graphene. We show that a compression-relaxation mechanism produces
static ripples on graphene sheets and determine a peculiar temperature Tc,
such that for T < Tc the free energy of the rippled graphene is smaller
than that of roughened graphene. We also show that Tc depends on the
structural parameters and increases with increasing sample size. _________________________________________________________________ 2) Mapping Stochastic
Processes onto Complex Networks, with A.H. Shirazi, G.R. Jafari, J. Davoudi, J. Peinke and
M. Sahimi, J. Stat. Mech. (2009) P07046 (Pdf) We
introduce a method by which stochastic processes are mapped onto complex
networks. As examples, we construct the networks for such time series as
those for free-jet and low-temperature helium turbulence, the German stock
market index (the DAX), and the white noise. The networks are further studied
by contrasting their geometrical properties, such as the mean-length,
diameter, clustering, average number of connection per node. By comparing the
network properties of the investigated original time series with those for
the shuffled and surrogate series, we are able to quantify the effect of the
long-range correlations and the fatness of the probability distribution
functions of the series on the constructed networks. Most importantly, we
demonstrate that the time series can be reconstructed with high
precisions by a simple random walk on their corresponding networks. (Pdf) _________________________________________________________________ 3)
Turbulencelike
Behavior of Seismic Time Series, P. Manshour, S. Saberi, M. Sahimi, J. Peinke, Amalio
F. Pacheco, M. Reza Rahimi Tabar, Phys. Rev. Lett. 102,
014101 (2009) (Pdf).
A grand challenge in geophysics has been developing a method for predicting
when a significant earthquake may occur. Our team has developed a new method
that may go a long way towards this goal. Using the method, we analyzed the
fluctuations of the detrended increments of the time series for Earth's
vertical velocity for many earthquakes. Our analysis reveals a significant
change in the nature of the probability density functions (PDF) of the
series' increments. For a large earthquake the time at which the PDF
undergoes a transition from a Gaussian to a non-Gaussian is 5-10 hours. The
key quantity that signals the transition is the parameter Lambda^2 that
appears in the PDF. Far from the earthquake, Lambda^2 is almost zero, but
close to it suddenly increases, signaling the transition. The PDF's flatness
also exhibits the same trends. Therefore the transition in the PDF, and the
changes in Lambda^2 and the PDF's flatness, all happening at the same time,
represent a new precursor for detecting impending significant earthquakes. A
key insight is that, due to localization of elastic waves, only stations
close to the epicenter provide the alert. (Pdf)
--The power
point presentation: (Pdf) --Highlight of the paper in
German Media ______________________________________________________________________________________________________________
4) The
Taylor frozen hypothesis in Burgers turbulence, with A. Bahraminasab, M.
D. Niry, J. Davoudi, A. A. Masoudi, and K. R. Sreenivasan, Phys.
Rev. E 77 (Rapid Communication) 065302 (2008)
(Pdf). 5) Analysis of Nonstationary Stochastic Processes with Application to the Fluctuations in the Oil Price, with,F. Ghasemi, M. Sahimi, J. Peinke, R.Friedrich, G. Reza Jafari, M. Reza Rahimi Tabar, Phys. Rev. E 75, (Rapid Communication), 060102(2007) (Pdf) 6) Localization of elastic waves in
heterogeneous media with off-diagonal disorder and long-range correlations,
with, F. Shahbazi, Alireza Bahraminasab,S. Mehdi Vaez Allaei, and Muhammad
Sahimi, Phys. Rev. Lett. 94, 165505
(2005) (Pdf) 7) Stochastic Analysis and Regeneration of Rough Surfaces, with, G. R. Jafari, S. M. Fazeli, F. Ghasemi, S. M. Vaez Allaei, A. Iraji zad and G. Kavei, Phys. Rev. Lett. 91 (2003) 226101 (Pdf) 8) Singularity Time Scale of the Kardar-Parisi-Zhang Equation in the Strong Coupling Limit in 2+1 dimensions, with, F. Shahbazi, and A. A. Masoudi, Journal of Statistical Physics 112, 437 (2003) (Pdf) 9) Statistical Theory of the Kardar-Parisi-Zhang Equation in 1+1 Dimension, with, A.A. Masoudi, F. Shahbazi, and J. Davoudi, Phys. Rev. E (65) 026132 (2002)(Pdf) 10)Theoretical Model for Kramers-Moyal's
description of Turbulence Cascade, with, Jahanshah Davoudi, Phys. Rev. Lett. 82 (1999) 1680 (Pdf) |
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Last
Update May. 2010, M.D. Niry
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