Holography of Strongly Coupled Gauge Theories

The "periodic table" of strongly coupled gauge theories remains only sketchily understood. Holography has developed to the point where bottom up constructions can describe the spectrum of individual gauge theories (based on assumptions of their running) including quarks in different representations and higher dimension operators. I highlight the method with a "perfected" version of an AdS dual of QCD and results for composite higgs models with two representations of quarks. The method raises questions about the degree to which energy scales can be split in generic gauge theories including whether confinement and chiral symmetry breaking are linked.

Relation between parity-even and parity-odd CFT correlation functions in three dimensions

In this paper we relate the parity-odd part of two and three point correlation functions in theories with exactly conserved or weakly broken higher spin symmetries to the parity-even part which can be computed from free theories. We also comment on higher point functions.The well known connection of CFT correlation functions with de-Sitter amplitudes in one higher dimension implies a relation between parity-even and parity-odd amplitudes calculated using non-minimal interactions such as $$ {\mathcal{W}}^3 $$ W 3 and $$ {\mathcal{W}}^2\tilde{\mathcal{W}} $$ W 2 W ˜ . In the flat-space limit this implies a relation between parity-even and parity-odd parts of flat-space scattering amplitudes.

Интегральные операторы, теоремы вложения, изометрии, граничное поведение и коэффициенты Тэйлора многомерных пространств типа Неванлинны и связанные с ними проблемы

This paper contains an overview of recent results of Area-Nevanlinna classes in higher dimension. We here consider various aspects of this new interesting research area of analytic function theory in higher dimension (integral operations, embedding theorems, Taylor coefficients). Previously in one dimension all these results were known. New open interesting Problems in this new research area will be also discussed and indicated. В обзорной работе собраны воедино различные утверждения, полученные различными авторами в последнее время по аналитическим многомерным пространствам типа Неванлинны в различных многомерных областях. В статье также сформулированы и кратко обсуждаются различные новые актуальные интересные проблемы, возникающие естественным образом в указанных многомерных классах аналитических функций в различных областях в Cn. Особое внимание в работе уделяется изометриям, действию различных интегральных операторов, различным теоремам вложения, и оценкам коэффициентов Тейлора в упомянутых аналитических пространствах типа Неванлинны в различных многомерных областях. Вдобавок в данной статье вместе с ранее изученными многомерными классами функций подобного типа вводятся также новые различные шкалы многомерных пространств типа Неванлинны в различных областях в Cn.

Solution of the Kadomtsev-Petviashvili equation using an improved homotopy perturbation method

An improved homotopy perturbation method (LH) applied to find approximate solution of KP equation. The results obtained ensure that LH is capable for solving the strongly higher dimension nonlinear partial differential equation such as KP equation. The approximated solution obtained by LH is compared with exact solution.

Fluidic bacterial diodes rectify magnetotactic cell motility in porous environments

Directed motility enables swimming microbes to navigate their environment for resources via chemo-, photo-, and magneto-taxis. However, directed motility competes with fluid flow in porous microbial habitats, affecting biofilm formation and disease transmission. Despite this broad importance, a microscopic understanding of how directed motility impacts the transport of microswimmers in flows through constricted pores remains unknown. Through microfluidic experiments, we show that individual magnetotactic bacteria directed upstream through pores display three distinct regimes, whereby cells swim upstream, become trapped within a pore, or are advected downstream. These transport regimes are reminiscent of the electrical conductivity of a diode and are accurately predicted by a comprehensive Langevin model. The diode-like behavior persists at the pore scale in geometries of higher dimension, where disorder impacts conductivity at the sample scale by extending the trapping regime over a broader range of flow speeds. This work has implications for our understanding of the survival strategies of magnetotactic bacteria in sediments and for developing their use in drug delivery applications in vascular networks.

Automatic First Arrival Picking Workflow by Global Path Tracing

It can be challenging to pick high quality first arrivals on noisy seismic datasets. The stability and smoothness criteria of the picked first arrival are not satisfied for datasets with shingles and interferences from unexpected and backscattered events. To improve first arrival picking, we propose an automatic first arrival picking workflow using global path tracing to find a global solution for first arrival picking with the condition of smoothness of the traced path. The proposed methodology is composed of data preconditioning, global path tracing, and final addition of traced and piloted travel times to compute the total picked travel time. We propose several ways to precondition the dataset, including the use of amplitude and amplitude ratio with and without a pilot. 2D global path tracing is comprised of two steps, namely, accumulation of energy on the potential path and backtracking of the optimal path with a strain factor for smoothness. For higher dimensional datasets, two strategies were adopted. One was to split the higher-dimension data into sub-domains of two dimensions to which 2D global path tracing was applied. The alternative method was to smooth the preconditioned dataset in directions except for the one used to trace the path before applying 2D global path tracing. Next, we discussed the importance of choosing proper parameters in both data preconditioning and constraining global path tracing. We demonstrated the robustness and stability of the proposed automatic first arrival picking via global path tracing using synthetic and field data examples.

Optimized Polynomial Classifier for Classification of M-PSK Signals

Automatic modulation classification (AMC) is the emerging research area for military and civil applications. In this paper, M-PSK signals are classified using the optimized polynomial classifier. The distinct features i.e., higher order cumulants (HOC’s) are extracted from the noisy received signal and the dataset is generated with different number of samples, various SNR’s and on several fading channels. The proposed classifier structure classifies the overall modulation classification problem into binary sub-classifications. In each sub-classification, the extracted features are expanded using polynomial expansion into higher dimension space. In higher dimension space numerous non-linearly separable classes becomes linearly separable. The performance of the proposed classifier is evaluated on Rayleigh and Rician fading channels in the presence of additive white gaussian noise (AWGN). The polynomial classifier performance is optimized using one of the famous heuristic computational techniques i.e., Genetic Algorithm (GA). The extensive simulations have been carried with and without optimization, which shows relatively better percentage classification accuracy (PCA) as compared with the state of art existing techniques.