Perturbative evolution of far off-resonance driven two-level systems: Coherent population trapping, localization, and harmonic generation

The time evolution of driven two-level systems in the far off-resonance regime is studied analytically. We obtain a general first-order perturbative expression for the time-dependent density operator which is applicable regardless of the coupling strength value. In the strong field regime, our perturbative expansion remains valid even when the far off-resonance condition is not fulfilled. We find that, in the absence of dissipation, driven two-level systems exhibit coherent population trapping in a certain region of parameter space, a property which, in the particular case of a symmetric double-well potential, implies the well-known localization of the system in one of the two wells. Finally, we show how the high-order harmonic generation that this kind of systems display can be obtained as a straightforward application of our formulation.Comment: 14 pages, LaTeX, 2 figures, acknowledgments adde

Oscillation of generalized differences of H\"older and Zygmund functions

In this paper we analyze the oscillation of functions having derivatives in the H\"older or Zygmund class in terms of generalized differences and prove that its growth is governed by a version of the classical Kolmogorov's Law of the Iterated Logarithm. A better behavior is obtained for functions in the Lipschitz class via an interesting connection with Calder\'on-Zygmund operators.Comment: 16 page

Mimicking anti-viruses with machine learning and entropy profiles

The quality of anti-virus software relies on simple patterns extracted from binary files. Although these patterns have proven to work on detecting the specifics of software, they are extremely sensitive to concealment strategies, such as polymorphism or metamorphism. These limitations also make anti-virus software predictable, creating a security breach. Any black hat with enough information about the anti-virus behaviour can make its own copy of the software, without any access to the original implementation or database. In this work, we show how this is indeed possible by combining entropy patterns with classification algorithms. Our results, applied to 57 different anti-virus engines, show that we can mimic their behaviour with an accuracy close to 98% in the best case and 75% in the worst, applied on Windows’ disk resident malware

Microcanonical versus Canonical Analysis of Protein Folding

The microcanonical analysis is shown to be a powerful tool to characterize the protein folding transition and to neatly distinguish between good and bad folders. An off-lattice model with parameter chosen to represent polymers of these two types is used to illustrate this approach. Both canonical and microcanonical ensembles are employed. The required calculations were performed using parallel tempering Monte Carlo simulations. The most revealing features of the folding transition are related to its first-order-like character, namely, the S-bend pattern in the caloric curve, which gives rise to negative microcanonical specific heats, and the bimodality of the energy distribution function at the transition temperatures. Models for a good folder are shown to be quite robust against perturbations in the interaction potential parameters.Comment: 4 pages, 4 figure