Four Dimensional Graphene

Mimicking pristine 2D graphene, we revisit the BBTW model for 4D lattice QCD given in ref.[5] by using the hidden SU(5) symmetry of the 4D hyperdiamond lattice H_4. We first study the link between the H_4 and SU(5); then we refine the BBTW 4D lattice action by using the weight vectors \lambda_1, \lambda_2, \lambda_3, \lambda_4, \lambda_5 of the 5-dimensional representation of SU(5) satisfying {\Sigma}_i\lambda_i=0. After that we study explicitly the solutions of the zeros of the Dirac operator D in terms of the SU(5) simple roots \alpha_1, \alpha_2, \alpha_3, \alpha_4 generating H_4; and its fundamental weights \omega_1, \omega_2, \omega_3, \omega_4 which generate the reciprocal lattice H_4^\ast. It is shown, amongst others, that these zeros live at the sites of H_4^\ast; and the continuous limit D is given by ((id\surd5)/2) \gamma^\muk_\mu with d, \gamma^\mu and k_\mu standing respectively for the lattice parameter of H_4, the usual 4 Dirac matrices and the 4D wave vector. Other features such as differences with BBTW model as well as the link between the Dirac operator following from our construction and the one suggested by Creutz using quaternions, are also given. Keywords: Graphene, Lattice QCD, 4D hyperdiamond, BBTW model, SU(5) Symmetry.Comment: LaTex, 26 pages, 1 figure, To appear in Phys Rev

Extremal Black Attractors in 8D Maximal Supergravity

Motivated by the new higher D-supergravity solutions on intersecting attractors obtained by Ferrara et al. in [Phys.Rev.D79:065031-2009], we focus in this paper on 8D maximal supergravity with moduli space [SL(3,R)/SO(3)]x[SL(2,R)/SO(2)] and study explicitly the attractor mechanism for various configurations of extremal black p- branes (anti-branes) with the typical near horizon geometries AdS_{p+2}xS^{m}xT^{6-p-m} and p=0,1,2,3,4; 2<=m<=6. Interpretations in terms of wrapped M2 and M5 branes of the 11D M-theory on 3-torus are also given. Keywords: 8D supergravity, black p-branes, attractor mechanism, M-theory.Comment: 37 page

Reduction of Conducted Perturbations in DC-DC Voltage Converters by a Dual Randomized PWM Scheme

Randomized Pulse Width Modulation (RPWM) deals better than Deterministic PWM (DPWM) with Electro-Magnetic Compatibility (EMC) standards for conducted Electro-Magnetic Interferences (EMI). In this paper, we propose a dual RPWM scheme for DC-DC voltage converters: the buck converter and the full bridge converter. This scheme is based on the comparison of deterministic reference signals (one signal for the buck converter and two signals for the full bridge converter) to a single triangular carrier having two randomized parameters. By using directly the randomized parameters of the carrier, a mathematical model of the Power Spectral Density (PSD) of output voltage is developed for each converter. The EMC advantage of the proposed dual randomization scheme compared to the classical simple randomization schemes is clearly highlighted by the PSD analysis and confirmed by FFT (Fast Fourier Transform) analysis of the output voltage

Transient Analysis of Grounding Systems Associated to Substation Structures under Lightning Strokes

In this paper we propose a new formalism for analyzing the transient behavior of grounding systems associated to substation structures (Faraday-cage) under lightning strokes in unsettled regime. The protective device to study is formed of a guard filet connected to a grounding grid by simple conductors called down conductors. Our formalism is based on the resolution of the propagation equation in potential on 3D. The purpose of our proposition is the direct analyzing in time domain and simple implementation. We compare the results obtained by this new approach to results published in literature

Machine learning one-dimensional spinless trapped fermionic systems with neural-network quantum states

We compute the ground-state properties of fully polarized, trapped, one-dimensional fermionic systems interacting through a gaussian potential. We use an antisymmetric artificial neural network, or neural quantum state, as an ansatz for the wavefunction and use machine learning techniques to variationally minimize the energy of systems from 2 to 6 particles. We provide extensive benchmarks with other many-body methods, including exact diagonalisation and the Hartree-Fock approximation. The neural quantum state provides the best energies across a wide range of interaction strengths. We find very different ground states depending on the sign of the interaction. In the non-perturbative repulsive regime, the system asymptotically reaches crystalline order. In contrast, the strongly attractive regime shows signs of bosonization. The neural quantum state continuously learns these different phases with an almost constant number of parameters and a very modest increase in computational time with the number of particles

A Review on Multi-Terminal High Voltage Direct Current Networks for Wind Power Integration

With the growing pressure to substitute fossil fuel-based generation, Renewable Energy Sources (RES) have become one of the main solutions from the power sector in the fight against climate change. Offshore wind farms, for example, are an interesting alternative to increase renewable power production, but they represent a challenge when being interconnected to the grid, since new installations are being pushed further off the coast due to noise and visual pollution restrictions. In this context, Multi-Terminal High Voltage Direct Current (MT-HVDC) networks are the most preferred technology for this purpose and for onshore grid reinforcements. They also enable the delivery of power from the shore to offshore Oil and Gas (O&amp;G) production platforms, which can help lower the emissions in the transition away from fossil fuels. In this work, we review relevant aspects of the operation and control of MT-HVDC networks for wind power integration. The review approaches topics such as the main characteristics of MT-HVDC projects under discussion/commissioned around the world, rising challenges in the control and the operation of MT-HVDC networks and the modeling and the control of the Modular Multilevel Converter (MMC) stations. To illustrate the challenges on designing the control system of a MT-HVDC network and to corroborate the technical discussions, a simulation of a three-terminal MT-HVDC network integrating wind power generation and offshore O&amp;G production units to the onshore grid is performed in Matlab's Simscape Electrical toolbox. The results highlight the main differences between two alternatives to design the control system for an MT-HVDC network