Nonlinear Electromagnetic Quasinormal Modes and Hawking Radiation of A Regular Black Hole with Magnetic Charge

Based on a regular exact black hole (BH) from nonlinear electrodynamics (NED) coupled to General Relativity, we investigate its stability of such BH through the Quasinormal Modes (QNMs) of electromagnetic (EM) field perturbation and its thermodynamics through Hawking radiation. In perturbation theory, we can deduce the effective potential from nonlinear EM field. The comparison of potential function between regular and RN BHs could predict their similar QNMs. The QNMs frequencies tell us the effect of magnetic charge $q$, overtone $n$, angular momentum number $l$ on the dynamic evolution of NLED EM field. Furthermore we also discuss the cases near extreme condition of such magnetically charged regular BH. The corresponding QNMs spectrum illuminates some special properties in the near-extreme cases. For the thermodynamics, we employ Hamilton-Jacobi method to calculate the near-horizon Hawking temperature of the regular BH and reveal the relationship between classical parameters of black hole and its quantum effect

What are the Latest Trends in Career Pathing Models as Well as the Most Effective Ways to Accelerate High Potential Development?

The war for talent is raging, making attracting, retaining, and developing high-performers more challenging than ever. Many of the “Baby Boomer” executives will be retiring in the near future, and only 15% of organizations in North America and Asia believe they have sufficient qualified successors for key positions. Additionally, 25% of surveyed organizations said they fail to keep top-performers, further illustrating the urgency and importance of the need to design optimal programs for developing future leaders. Thus, the content below will provide insight into the factors that make development program for “high potentials” successful

Soft Gluon Resummation Effects in Single Graviton Production at the CERN Large Hadron Collider in the Randall-Sundrum Model

We study QCD effects in single graviton production at the CERN Large Hadron Collider (LHC) in the Randall-Sundrum (RS) Model. We present in detail the complete next-to-leading order (NLO) QCD corrections to the inclusive total cross sections. The NLO QCD corrections enhance significantly the total cross sections and decrease efficiently the dependence of the total cross sections on the factorization and renormalization scales. We also examine the uncertainty of the total cross sections due to the parton distribution function (PDF) uncertainties. For the differential cross sections on the transverse momentum ($q_T$) of the graviton, within the CSS resummation formalism, we resum the logarithmically-enhanced terms at small $q_T$ to all orders up to NLO logatithmic accuracy. Combined with the fixed order calculations, we give consistent predictions for both small $q_T$ and large $q_T$.Comment: 26 pages, 13 figures; minor changes and misprints corrected; version to appear in PR

Thrust distribution in Higgs decays at the next-to-leading order and beyond

We present predictions for the thrust distribution in hadronic decays of the Higgs boson at the next-to-leading order and the approximate next-to-next-to-leading order. The approximate NNLO corrections are derived from a factorization formula in the soft/collinear phase-space regions. We find large corrections, especially for the gluon channel. The scale variations at the lowest orders tend to underestimate the genuine higher order contributions. The results of this paper is therefore necessary to control the perturbative uncertainties of the theoretical predictions. We also discuss on possible improvements to our results, such as a soft-gluon resummation for the 2-jets limit, and an exact next-to-next-to-leading order calculation for the multi-jets region

What-and-Where to Match: Deep Spatially Multiplicative Integration Networks for Person Re-identification

Matching pedestrians across disjoint camera views, known as person re-identification (re-id), is a challenging problem that is of importance to visual recognition and surveillance. Most existing methods exploit local regions within spatial manipulation to perform matching in local correspondence. However, they essentially extract \emph{fixed} representations from pre-divided regions for each image and perform matching based on the extracted representation subsequently. For models in this pipeline, local finer patterns that are crucial to distinguish positive pairs from negative ones cannot be captured, and thus making them underperformed. In this paper, we propose a novel deep multiplicative integration gating function, which answers the question of \emph{what-and-where to match} for effective person re-id. To address \emph{what} to match, our deep network emphasizes common local patterns by learning joint representations in a multiplicative way. The network comprises two Convolutional Neural Networks (CNNs) to extract convolutional activations, and generates relevant descriptors for pedestrian matching. This thus, leads to flexible representations for pair-wise images. To address \emph{where} to match, we combat the spatial misalignment by performing spatially recurrent pooling via a four-directional recurrent neural network to impose spatial dependency over all positions with respect to the entire image. The proposed network is designed to be end-to-end trainable to characterize local pairwise feature interactions in a spatially aligned manner. To demonstrate the superiority of our method, extensive experiments are conducted over three benchmark data sets: VIPeR, CUHK03 and Market-1501.Comment: Published at Pattern Recognition, Elsevie