Two component Bose-Hubbard model with higher angular momentum states

We study a Bose-Hubbard Hamiltonian of ultracold two component gas of spinor Chromium atoms. Dipolar interactions of magnetic moments while tuned resonantly by ultralow magnetic field can lead to spin flipping. Due to approximate axial symmetry of individual lattice site, total angular momentum is conserved. Therefore, all changes of the spin are accompanied by the appearance of the angular orbital momentum. This way excited Wannier states with non vanishing angular orbital momentum can be created. Resonant dipolar coupling of the two component Bose gas introduces additional degree of control of the system, and leads to a variety of different stable phases. The phase diagram for small number of particles is discussed.Comment: 4 pages, 2 figure

On the stability of Bose-Fermi mixtures

We consider the stability of a mixture of degenerate Bose and Fermi gases. Even though the bosons effectively repel each other the mixture can still collapse provided the Bose and Fermi gases attract each other strongly enough. For a given number of atoms and the strengths of the interactions between them we find the geometry of a maximally compact trap that supports the stable mixture. We compare a simple analytical estimation for the critical axial frequency of the trap with results based on the numerical solution of hydrodynamic equations for Bose-Fermi mixture.Comment: 4 pages, 3 figure

Free expansion of a Bose-Einstein condensate at the presence of a thermal cloud

We investigate numerically the free-fall expansion of a $^{87}$Rb atoms condensate at nonzero temperatures. The classical field approximation is used to separate the condensate and the thermal cloud during the expansion. We calculate the radial and axial widths of the expanding condensate and find clear evidence that the thermal component changes the dynamics of the condensate. Our results are confronted against the experimental data

Physicochemical Characterization and Dissolution Studies of Solid Dispersions of Clotrimazole with Pluronic F127

Purpose: To evaluate the physicochemical properties of clotrimazole (CLT) solid dispersion with Pluronic F127 (PLU).Methods: Solid dispersions of the antifungal drug, clotrimazole, were prepared with Pluronic F127 using grinding (PM) and fusion (FUS) methods. Physicochemical characterization of the dispersions were performed using differential scanning calorimetry (DSC), x-ray powder diffraction (XRPD) and Fourier transform infrared spectroscopy (FTIR). In vitro drug release was carried out using the rotating disc method.Results: These studies showed that there was no chemical interaction between CLT and PLU. Release studies on the SDs showed a significant (> 90-fold) improvement in dissolution rate compared to pure CLT. The greatest increase in dissolution (< 80 %) was observed for the solid dispersion (CLT/PLU) prepared by FUS in the ratio 60:40 % w/w.Conclusion: The results demonstrate that the developed solid dispersion system is a suitable approach for enhancing the dissolution rate of CLT.Keywords: Clotrimazole, Pluronic F127, Solid dispersion, Dissolution, Differential scanning calorimetry, Phase diagra

A multi-objective memetic inverse solver reinforced by local optimization methods

We propose a new memetic strategy that can solve the multi-physics, complex inverse problems, formulated as the multi-objective optimization ones, in which objectives are misfits between the measured and simulated states of various governing processes. The multi-deme structure of the strategy allows for both, intensive, relatively cheap exploration with a moderate accuracy and more accurate search many regions of Pareto set in parallel. The special type of selection operator prefers the coherent alternative solutions, eliminating artifacts appearing in the particular processes. The additional accuracy increment is obtained by the parallel convex searches applied to the local scalarizations of the misfit vector. The strategy is dedicated for solving ill-conditioned problems, for which inverting the single physical process can lead to the ambiguous results. The skill of the selection in artifact elimination is shown on the benchmark problem, while the whole strategy was applied for identification of oil deposits, where the misfits are related to various frequencies of the magnetic and electric waves of the magnetotelluric measurement

Multi-objective hierarchic memetic solver for inverse parametric problems

We propose a multi-objective approach for solving challenging inverse parametric problems. The objectives are misfits for several physical descriptions of a phenomenon under consideration, whereas their domain is a common set of admissible parameters. The resulting Pareto set, or parameters close to it, constitute various alternatives of minimizing individual misfits. A special type of selection applied to the memetic solution of the multi-objective problem narrows the set of alternatives to the ones that are sufficiently coherent. The proposed strategy is exemplified by solving a real-world engineering problem consisting of the magnetotelluric measurement inversion that leads to identification of oil deposits located about 3 km under the Earth's surface, where two misfit functions are related to distinct frequencies of the electric and magnetic waves

Probabilistic properties of detrended fluctuation analysis for Gaussian processes

Detrended fluctuation analysis (DFA) is one of the most widely used tools for the detection of long-range dependence in time series. Although DFA has found many interesting applications and has been shown to be one of the best performing detrending methods, its probabilistic foundations are still unclear. In this paper, we study probabilistic properties of DFA for Gaussian processes. Our main attention is paid to the distribution of the squared error sum of the detrended process. We use a probabilistic approach to derive general formulas for the expected value and the variance of the squared fluctuation function of DFA for Gaussian processes. We also get analytical results for the expected value of the squared fluctuation function for particular examples of Gaussian processes, such as Gaussian white noise, fractional Gaussian noise, ordinary Brownian motion, and fractional Brownian motion. Our analytical formulas are supported by numerical simulations. The results obtained can serve as a starting point for analyzing the statistical properties of DFA-based estimators for the fluctuation function and long-memory parameter