Coherent States of Accelerated Relativistic Quantum Particles, Vacuum Radiation and the Spontaneous Breakdown of the Conformal SU(2,2) Symmetry

We give a quantum mechanical description of accelerated relativistic particles in the framework of Coherent States (CS) of the (3+1)-dimensional conformal group SU(2,2), with the role of accelerations played by special conformal transformations and with the role of (proper) time translations played by dilations. The accelerated ground state $\tilde\phi_0$ of first quantization is a CS of the conformal group. We compute the distribution function giving the occupation number of each energy level in $\tilde\phi_0$ and, with it, the partition function Z, mean energy E and entropy S, which resemble that of an "Einstein Solid". An effective temperature T can be assigned to this "accelerated ensemble" through the thermodynamic expression dE/dS, which leads to a (non linear) relation between acceleration and temperature different from Unruh's (linear) formula. Then we construct the corresponding conformal-SU(2,2)-invariant second quantized theory and its spontaneous breakdown when selecting Poincar\'e-invariant degenerated \theta-vacua (namely, coherent states of conformal zero modes). Special conformal transformations (accelerations) destabilize the Poincar\'e vacuum and make it to radiate.Comment: 25 pages, LaTeX, 3 figures. Additional information (resulting in four extra pages) and a slight change of focus has been introduced in order to make the line of arguments more clear. Title changed accordingl

Applications of Cognitive Radio Networks

The term cognitive radio (CR), originally coined in the late 1990s, envisaged a radio that is aware of its operational environment so that it can dynamically and autonomously adjust its radio-operating parameters to accordingly adapt to the different situations. Cognition is achieved through the so-called cognitive cycle, consisting of the observation of the environment, the orientation and planning that leads to making appropriate decisions in accordance with specific operation goals, and finally, the execution of these decisions (e.g., access to the appropriate channel). Decisions can be reinforced by learning procedures based on the past observations and the corresponding results of prior actuations

A mirror in fiction: drawing parallelisms between Camus's La Peste and COVID-19

COVID-19 represents one of the most challenging global health issues in modern times. However, as epidemics have affected humans since our origins, many before us have described how significantly they compromise human lives. Leaving apart the aspects more linked to medicine and health sciences, we focus here on analysing how epidemics force people to change their habits, what type of emotions and behaviours they promote, and which roles are played by different social actors. For such a purpose, especially if we wish to draw some parallels between past epidemics and COVID-19, historical records seemed to be more suitable than literary works. Nonetheless, we have taken this approach relying on La Peste (Albert Camus, 1947), a novel based on a fictional epidemic of plague in the Algerian town of Oran. Far from creating a barrier separating fiction from reality, this reading allowed us to establish several links with our current situation. Recognising that context and solutions vary widely between the two scenarios, core matters concerning epidemics seemed to remain invariable. The important role of data and statistics, the leadership acquired by health authorities, the separations of relatives or the negative effects on trade and business are some issues which took place in Oran as well as nowadays. Besides that, epidemics also affect humans at an individual level, and certain thoughts and feelings in La Peste's main characters may make us identify with our own fears and desires.S

Accretion disks around black holes in modified strong gravity

Stellar-mass black holes offer what is perhaps the best scenario to test theories of gravity in the strong-field regime. In particular, f(R) theories, which have been widely discuss in a cosmological context, can be constrained through realistic astrophysical models of phenomena around black holes. We aim at building radiative models of thin accretion disks for both Schwarzschild and Kerr black holes in f(R) gravity. We study particle motion in f(R)-Schwarzschild and Kerr space-times. We present the spectral energy distribution of the accretion disk around constant Ricci scalar f(R) black holes, and constrain specific f(R) prescriptions using features of these systems. A precise determination of both the spin and accretion rate onto black holes along with X-ray observations of their thermal spectrum might allow to identify deviations of gravity from General Relativity. We use recent data on the high-mass X-ray binary Cygnus X-1 to restrict the values of the parameters of a class of f(R) models.Comment: 16 pages, 20 figures, accepted for publication in Astronomy & Astrophysic

Seed beetles (Coleoptera: Bruchidae) associated with Acacia cornigera (L.) Willd., with description of a new species of Acanthoscelides Schilsky

Presented herein is a key to identify species of Bruchidae associated with Acacia cornigera (L.). For each species, host records, distributions and bionomics are given. A new species of Acanthoscelides Schilsky is described and figured; Acanthoscelides sauli Romero, Cruz, and Kingsolver

A minimalistic approach for fast computation of geodesic distances on triangular meshes

The computation of geodesic distances is an important research topic in Geometry Processing and 3D Shape Analysis as it is a basic component of many methods used in these areas. In this work, we present a minimalistic parallel algorithm based on front propagation to compute approximate geodesic distances on meshes. Our method is practical and simple to implement and does not require any heavy pre-processing. The convergence of our algorithm depends on the number of discrete level sets around the source points from which distance information propagates. To appropriately implement our method on GPUs taking into account memory coalescence problems, we take advantage of a graph representation based on a breadth-first search traversal that works harmoniously with our parallel front propagation approach. We report experiments that show how our method scales with the size of the problem. We compare the mean error and processing time obtained by our method with such measures computed using other methods. Our method produces results in competitive times with almost the same accuracy, especially for large meshes. We also demonstrate its use for solving two classical geometry processing problems: the regular sampling problem and the Voronoi tessellation on meshes.Comment: Preprint submitted to Computers & Graphic