Andres Mauricio Kowalski

We examine the classical limit of a fairly general nonlinear semiclassical hybrid system within a MaxEnt framework. The consistency of the hybrid dynamics requires algebraic constraints on quantum operators and smoothness conditions for the classical variables. Analytically, we demonstrate that the classical limit is characterized by a pure density matrix representing a single state, which reproduces the dynamics of its classical analogue. To illustrate the methodology, we revisit and synthesize two previously studied examples.

We investigated the dynamics of a regular nonlinear semiclassical system by employing Shannon entropy together with two associated formulations of statistical complexity: the López-Ruiz–Mancini–Calbet (LMC) and Jensen–Shannon approaches. Additionally, Tsallis entropy was used as an alternative quantifier. In this context, quantum variables interacted with a classical environment, and both conservative and dissipative regimes were considered. To compute information-theoretic quantifiers, probability distributions were extracted from the system's temporal evolution using the Bandt–Pompe permutation method. The classical limit was characterized by a motion invariant linked to the uncertainty principle. Our analysis revealed three distinct zones that characterized the structure of transitions across the classical–quantum boundary. These findings confirmed earlier results obtained in markedly different dynamical systems. This consistency supported the idea of a possible generalization, which, if established, would have significant implications for both semiclassical and quantum theories.

In the present investigation diverse information quantifiers have been applied to the study of time-series of COVID-19. First, it has been analyzed how the smoothing of the curves affects the informative content of the series, using permutation and wavelet entropies for the series of new daily cases, by means of a sliding-windows’ method. Besides, in order to evaluate the relationship between the curves of new daily cases of infections and deaths, the wavelet coherence has been calculated. The results show the utility of information quantifiers to understand the unpredictable behaviour of the pandemics in the short and mean time

We analyze the (dynamical) classic limit of a special semiclassical system. We describe the interaction of a quantum system with a classical one. This limit has been well studied before as a function of a constant of motion linked to the Heisenberg principle. In this paper, we investigate the existence of the mentioned limit, but with reference to the total energy of the system. Additionally, we find an attractive result regarding the border of the transition.

Aplicamos diferentes cuantificadores de informacion al estudio de series temporales de COVID-19. En primer lugar, analizamos como el hecho de suavizar las curvas altera el contenido de informacion de la serie, aplicando la entropia de permutaciones y la entropia wavelet a la serie de casos diarios nuevos mediante un metodo de ventana movil. Ademas, para estudiar que tan acopladas estan las curvas asociadas con los nuevos casos diarios de infecciones y muertes, calculamos la coherencia wavelet. Nuestros resultados muestran como se pueden utilizar cuantificadores de información para analizar el comportamiento impredecible de esta pandemia en el corto y mediano plazo.

We analyze the nonlinear dynamics of a quartic semiclassical system able to describe the interaction of matter with a field. We do it in both dissipative and conservative scenarios. In particular, we study the classical limit of both frameworks and compare the associated features. In the two environments, we heavily use a system’s invariant, related to the Uncertainty Principle, that helps to determine how the dynamics tends to the pertinent classical limit. We exhibit the convergence to the classical limit and also verify that the Uncertainty Principle is complied with during the entire process, even in the presence of dissipation.

Since the appearance in China of the first cases, the entire world has been deeply affected by the flagellum of the Coronavirus Disease (COVID-19) pandemic. There have been many mathematical approaches trying to characterize the data collected about this serious issue. One of the most important aspects for attacking a problem is knowing what information is really available. We investigate here the information contained in the COVID-19 data of infected and deceased people in all countries, using informational quantifiers such as entropy and statistical complexity. For the evaluation of these quantities, we use the Bandt–Pompe permutation methodology, as well as the wavelet transform, to obtain the corresponding probability distributions from the available series of data. The period analyzed covers from the appearance of the disease up to the massive use of anti-COVID vaccines.

We associate here the relationship between de-coherence to the statistical notion of disequilibrium with regards to the dynamics of a system that reflects the interaction between matter and a given field. The process is described via information geometry. Some of its tools are shown here to appropriately explain the process’ mechanism. In particular we gain some insight into what is the role of the uncertainty principle (UP) in the pertinent proceedings.