Magnetization orientation dependence of the quasiparticle spectrum and hysteresis in ferromagnetic metal nanoparticles

We use a microscopic Slater-Koster tight-binding model with short-range exchange and atomic spin-orbit interactions that realistically captures generic features of ferromagnetic metal nanoparticles to address the mesoscopic physics of magnetocrystalline anisotropy and hysteresis in nanoparticle quasiparticle excitation spectra. Our analysis is based on qualitative arguments supported by self-consistent Hartree-Fock calculations for nanoparticles containing up to 260 atoms. Calculations of the total energy as a function of magnetization direction demonstrate that the magnetic anisotropy per atom fluctuates by several percents when the number of electrons in the particle changes by one, even for the largest particles we consider. Contributions of individual orbitals to the magnetic anisotropy are characterized by a broad distribution with a mean more than two orders of magnitude smaller than its variance and with no detectable correlations between anisotropy contribution and quasiparticle energy. We find that the discrete quasiparticle excitation spectrum of a nanoparticle displays a complex non-monotonic dependence on an external magnetic field, with abrupt jumps when the magnetization direction is reversed by the field, explaining recent spectroscopic studies of magnetic nanoparticles. Our results suggests the existence of a broad cross-over from a weak spin-orbit coupling to a strong spin-orbit coupling regime, occurring over the range from approximately 200- to 1000-atom nanoparticles.Comment: 39 pages, 18 figures, to be published in Physical Review

Landau-Zener quantum tunneling in disordered nanomagnets

We study Landau-Zener macroscopic quantum transitions in ferromagnetic metal nanoparticles containing on the order of 100 atoms. The model that we consider is described by an effective giant-spin Hamiltonian, with a coupling to a random transverse magnetic field mimicking the effect of quasiparticle excitations and structural disorder on the gap structure of the spin collective modes. We find different types of time evolutions depending on the interplay between the disorder in the transverse field and the initial conditions of the system. In the absence of disorder, if the system starts from a low-energy state, there is one main coherent quantum tunneling event where the initial-state amplitude is completely depleted in favor of a few discrete states, with nearby spin quantum numbers; when starting from the highest excited state, we observe complete inversion of the magnetization through a peculiar ``backward cascade evolution''. In the random case, the disorder-averaged transition probability for a low-energy initial state becomes a smooth distribution, which is nevertheless still sharply peaked around one of the transitions present in the disorder-free case. On the other hand, the coherent backward cascade phenomenon turns into a damped cascade with frustrated magnetic inversion.Comment: 21 pages, 7 figures, to be published in Phys.Rev.

Thin films of a three-dimensional topological insulator in a strong magnetic field: a microscopic study

The response of thin films of Bi$_2$Se$_3$ to a strong perpendicular magnetic field is investigated by performing magnetic bandstructure calculations for a realistic multi-band tight-binding model. Several crucial features of Landau quantization in a realistic three-dimensional topological insulator are revealed. The $n=0$ Landau level is absent in ultra-thin films, in agreement with experiment. In films with a crossover thickness of five quintuple layers, there is a signature of the $n=0$ level, whose overall trend as a function of magnetic field matches the established low-energy effective-model result. Importantly, we find a field-dependent splitting and a strong spin-polarization of the $n=0$ level which can be measured experimentally at reasonable field strengths. Our calculations show mixing between the surface and bulk Landau levels which causes the character of levels to evolve with magnetic field.Comment: 5 pages, 4 figure

GASP: Genetic algorithms for service placement in fog computing systems

Fog computing is becoming popular as a solution to support applications based on geographically distributed sensors that produce huge volumes of data to be processed and filtered with response time constraints. In this scenario, typical of a smart city environment, the traditional cloud paradigm with few powerful data centers located far away from the sources of data becomes inadequate. The fog computing paradigm, which provides a distributed infrastructure of nodes placed close to the data sources, represents a better solution to perform filtering, aggregation, and preprocessing of incoming data streams reducing the experienced latency and increasing the overall scalability. However, many issues still exist regarding the efficient management of a fog computing architecture, such as the distribution of data streams coming from sensors over the fog nodes to minimize the experienced latency. The contribution of this paper is two-fold. First, we present an optimization model for the problem of mapping data streams over fog nodes, considering not only the current load of the fog nodes, but also the communication latency between sensors and fog nodes. Second, to address the complexity of the problem, we present a scalable heuristic based on genetic algorithms. We carried out a set of experiments based on a realistic smart city scenario: the results show how the performance of the proposed heuristic is comparable with the one achieved through the solution of the optimization problem. Then, we carried out a comparison among different genetic evolution strategies and operators that identify the uniform crossover as the best option. Finally, we perform a wide sensitivity analysis to show the stability of the heuristic performance with respect to its main parameters