arXiv subjects

M. Saeedian

Publications and source records attributed to M. Saeedian.

5 recordsLinked to original sources

arXiv2020

Exact solvability and asymptotic aspects of generalized XX0 spin chains

Building on our earlier work \unscite{Sa-Za}, we introduce and study generalized XX0 models. We explicitly construct a long-range interacting spin chain, referred to as the Selberg model, and study the correlation functions of the Selberg and XX0 models. Using a matrix integral representation of the generalized XX0 model and applying asymptotic analysis in non-intersecting Brownian motion, the phase structure of the Selberg model is determined. We find that tails of the Tracy-Widom distribution, of Gaussian unitary ensemble, govern a discrete-to-continuous third-order phase transition in Selberg model. The same method also reproduces the Gross-Witten phase transition of the original XX0 model. Finally, we conjecture universal features for the phase structure of the generalized XX0 model.

math-ph↗

arXiv2017

Emergence of world-stock-market network

In the age of globalization, it is natural that the stock market of each country is not independent form the other markets. In this case, collective behavior could be emerged form their dependency together. This article studies the collective behavior of a set of forty influential markets in the world economy with the aim of exploring a global financial structure that could be called world-stock-market network. Towards this end, we analyze the cross-correlation matrix of the indices of these forty markets using Random Matrix Theory (RMT). We find the degree of collective behavior among the markets and the share of each market in their structural formation. This finding together with the results obtained from the same calculation on four stock markets reinforce the idea of a world financial market. Finally, we draw the dendrogram of the cross-correlation matrix to make communities in this abstract global market visible. The dendrogram, drawn by at least thirty percent of correlation, shows that the world financial market comprises three communities each of which includes stock markets with geographical proximity.

q-fin.ST↗

arXiv2017

Epidemic spreading on evolving signed networks

Most studies of disease spreading consider the underlying social network as obtained without the contagion, though epidemic influences people's willingness to contact others: A "friendly" contact may be turned to "unfriendly" to avoid infection. We study the susceptible-infected disease-spreading model on signed networks, in which each edge is associated with a positive or negative sign representing the friendly or unfriendly relation between its end nodes. In a signed network, according to Heider's theory, edge signs evolve such that finally a state of structural balance is achieved, corresponding to no frustration in physics terms. However, the danger of infection affects the evolution of its edge signs. To describe the coupled problem of the sign evolution and disease spreading, we generalize the notion of structural balance by taking into account the state of the nodes. We introduce an energy function and carry out Monte Carlo simulations on complete networks to test the energy landscape, where we find local minima corresponding to the so-called jammed states. We study the effect of the ratio of initial friendly to unfriendly connections on the propagation of disease. The steady state can be balanced or a jammed state such that a coexistence occurs between susceptible and infected nodes in the system.

physics.soc-ph↗

arXiv2017

Memory effects on epidemic evolution: The susceptible-infected-recovered epidemic model

Memory has a great impact on the evolution of every process related to human societies. Among them, the evolution of an epidemic is directly related to the individuals' experiences. Indeed, any real epidemic process is clearly sustained by a non-Markovian dynamics: memory effects play an essential role in the spreading of diseases. Including memory effects in the susceptible-infected-recovered (SIR) epidemic model seems very appropriate for such an investigation. Thus, the memory prone SIR model dynamics is investigated using fractional derivatives. The decay of long-range memory, taken as a power-law function, is directly controlled by the order of the fractional derivatives in the corresponding nonlinear fractional differential evolution equations. Here we assume "fully mixed" approximation and show that the epidemic threshold is shifted to higher values than those for the memoryless system, depending on this memory "length" decay exponent. We also consider the SIR model on structured networks and study the effect of topology on threshold points in a non- Markovian dynamics. Furthermore, the lack of access to the precise information about the initial conditions or the past events plays a very relevant role in the correct estimation or prediction of the epidemic evolution. Such a "constraint" is analyzed and discussed.

physics.soc-ph↗

arXiv2013

Specific Heat Capacity of TiO2 Nanoparticles

We have calculated heat capacity of TiO2 nanoparticles in three stable polymorphs by applying size and surface effects on heat capacity of the bulk structure. The size and surface corrections were imposed on the acoustic and optical bulk phonons, separately. The model used in the present work is a simple modification of the model proposed by Wang et al. We applied the modified model to obtain the specific heat capacity of 10-100 nm TiO2 nanoparticles. A very good consistency is observed between the computational and experimental data. Based on the modified model, particles with sizes larger than 70 nm behave like bulk structure. In addition, the heat capacity of particles smaller than 15 nm become independent from their structure details while demonstrating a drastic increase.

cond-mat.mtrl-sci↗