| Condensed Matter | |||
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| Strongly Correlated Electron Systems | |||
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Spin systems at low dimensions |
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| Examples of these models are Heisenberg chain and ladders, t-J model and Ferrimagnetic systemsThe study of low-energy properties of these systems and different phases which may take place via a quantum phase transition by varying a parameter is an interesting topic in this branch of physics when the temperature is zero or sufficiently low. The approach to deal with these models might be usual spin-wave, mean-field or other relevant theories. Quantum Renormalization Group (QRG) is also a technique which is used to derive information of the mentioned models. To obtain more accurate results at the other hand the Lanczos method as an exact diagonalization of a lattice Hamiltonian is implemented. Density Matrix Renormalization Group (DMRG) is also another technique which may be used in my study of one-dimensional models to obtain accurate results for larger size of system. | |||
| Collective phenomena of cold glasses | |||
| That is the effect of magnetic field on multi-component glasses at very low temprature (few mili-Kelvin). The effect of interaction between tunneling centers in a disordered model leads to novel phenomena. | |||
| Charge density plateau in t-J model on ladder geometry (in collaboration with Wuppertal group) | |||
| This is an analogous to magnetization curve in a magnetic field for charge density excitations. In an area of coupling constants the charge density gap opens which appears as a charge density plateau at some special value of charge density. | |||
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| Theoritical Mesoscopic Physics | |||
| Mesoscopic Superconductivity in particular Mesoscopic Josephson Junctions, Quasiclassical theory of superconductivity, Proximity effect , Ferromagnet-superconductor hetero-structuresand Unconventional superconductors. more... | |||
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| Complex networks | |||
| Recently people are interested in the study of real networks such as social, biological and communication networks. Here the main questions are: what is the structure and function of real networks and the relation between structure and function? what are the principal rules in the evolution of real networks? To answer these question one first identifies the essential structural properties of real networks. Now we know that almost all the real networks have a low diameter (Small-World phenomenon), a considerable clustering and a heterogenous structure. We know that these features of networks can strongly alter the behavior of systems living on them. We can also name the preferential attachment as the main rule in the evolution of real networks. This mechanism is (directly or indirectly) responsible of heterogenous structures in reality. However there are still some aspects of real networks that demand more investigations. Most of the analytical studies are concerned with locally tree-like networks. We need to consider more complex structures for example by introducing weights for links and so on. Moreover we do not know a lot about dynamical phenomena in complex networks. | |||
| Optimization problems | |||
| Statistical physics of optimization problems is one of the interesting applications of physics in this interdisciplinary field. Finding the ground state energy of a complex system like a spin glass is a well known example of optimization problems. The other examples are satisfiability of random Boolean formula (K-SAT), traveling sales man problem and graph coloring. From a computational point of view all the above examples are hard and indeed NP-complete. The interesting points for a physicist are the presence of phase transition (in the thermodynamic limit) and disorder in these problems. Fortunately most of the necessary tools and concepts to study the above problems have already been introduced in the study of spin glasses. Properties of ground state and excited states, the structure of solution space, the nature of possible phase transitions and a deeper understanding of the typical complexity of optimization problems are the main questions that people study. | |||
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