Power-law tailed statistical distributions and Lorentz transformations
نویسندگان
چکیده
منابع مشابه
Theoretical Foundations and Mathematical Formalism of the Power-Law Tailed Statistical Distributions
We present the main features of the mathematical theory generated by the κ-deformed exponential function expκ(x) = ( √ 1 + κ2x2 + κx), with 0 ≤ κ < 1, developed in the last twelve years, which turns out to be a continuous one parameter deformation of the ordinary mathematics generated by the Euler exponential function. The κ-mathematics has its roots in special relativity and furnishes the theo...
متن کاملLorentz Transformations and Statistical Mechanics
In [Gottlieb (1998)] and [Gottlieb (2000)] we launched a study of Lorentz transformations. We find that every Lorentz transformation can be expressed as an exponential e where F is a skew symmetric operator with respect to the Minkowski metric 〈 , 〉 of form −+++. We provided F with the notation of electromagnetism. Thus we can describe boosts as pure ~ E fields and rotations as pure ~ B fields....
متن کاملStatistical mechanical foundations of power-law distributions
The foundations of the Boltzmann-Gibbs (BG) distributions for describing equilibrium statistical mechanics of systems are examined. Broadly, they fall into: (i) probabilistic approaches based on the principle of equal a priori probability (counting technique and method of steepest descents), law of large numbers, or the state density considerations and (ii) a variational scheme maximum entropy ...
متن کاملOn a Geometric Mean and Power-law Statistical Distributions
For a large class of statistical systems a geometric mean value of the ob-servables is constrained. These observables are characterized by a power-law statistical distribution. In everyday life we find events of very different nature often to follow similar statistical distributions. These distributions arise because the same stochastic process is at work, and this process can be understood bey...
متن کاملStatistical Analyses Support Power Law Distributions Found in Neuronal Avalanches
The size distribution of neuronal avalanches in cortical networks has been reported to follow a power law distribution with exponent close to -1.5, which is a reflection of long-range spatial correlations in spontaneous neuronal activity. However, identifying power law scaling in empirical data can be difficult and sometimes controversial. In the present study, we tested the power law hypothesi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Physics Letters A
سال: 2011
ISSN: 0375-9601
DOI: 10.1016/j.physleta.2010.11.057