Tsallis distribution and luminescence decays

Predicting Shear Stress Distribution in Rectangular Channels Using Entropy Concept

This study makes use of the Tsallis entropy to predict the shear stress distribution. Given a definition of the Tsallis entropy, it is maximized by using the probability density function, which then is used to attain a novel shear stress equation. This is then employed for calculating the shear stress distribution in rectangular channels in different aspect ratios and finally, for viability, th...

Discharge Estimation by using Tsallis Entropy Concept

Flow-rate measurement in rivers under different conditions is required for river management purposes including water resources planning, pollution prevention, and flood control. This study proposed a new discharge estimation method by using a mean velocity derived from a 2D velocity distribution formula based on Tsallis entropy concept. This procedure is done based on several factors which refl...

Tsallis power laws and finite baths with negative heat capacity.

It is often stated that heat baths with finite degrees of freedom i.e., finite baths, are sources of Tsallis distributions for classical Hamiltonian systems. By using well-known fundamental statistical mechanics expressions, we rigorously show that Tsallis distributions with fat tails are possible only for finite baths with constant negative heat capacity, while constant positive heat capacity ...

Fluorescence spectroscopy and microscopy as tools for monitoring redox transformations of uranium in biological systems† †Electronic supplementary information (ESI) available: Full experimental details. Luminescence decays and fits, PXRD patterns, scintillation experiment results, additional experimental details and results for control experiments including comparative data with Escherichia coli. Anomalous data points resulting from cosmic rays were removed from steady state spectra obtained, and unaltered spectra are included in the ESI. The histogram showing the distribution of lifetime measurements in Fig. 3 shows only pixels with greater than 1000 counts, the full distribution can be found in the ESI. See DOI: 10.1039/c5sc00661a Click here for additional data file.

Generalized Evolutionary Algorithm based on Tsallis Statistics

Generalized evolutionary algorithm based on Tsallis canonical distribution is proposed. The algorithm uses Tsallis generalized canonical distribution to weigh the configurations for ‘selection’ instead of Gibbs-Boltzmann distribution. Our simulation results show that for an appropriate choice of non-extensive index that is offered by Tsallis statistics, evolutionary algorithms based on this gen...