Highly tunable hybrid metamaterials employing split-ring resonators strongly coupled to graphene surface plasmons

Metamaterials and plasmonics are powerful tools for unconventional manipulation and harnessing of light. Metamaterials can be engineered to possess intriguing properties lacking in natural materials, such as negative refractive index. Plasmonics offers capabilities to confine light in subwavelength dimensions and to enhance light-matter interactions. Recently,graphene-based plasmonics has revealed emerging technological potential as it features large tunability, higher field-confinement and lower loss compared to metal-based plasmonics. Here,we introduce hybrid structures comprising graphene plasmonic resonators efficiently coupled to conventional split-ring resonators, thus demonstrating a type of highly tunable metamaterial, where the interaction between the two resonances reaches the strong-coupling regime. Such hybrid metamaterials are employed as high-speed THz modulators, exhibiting over 60% transmission modulation and operating speed in excess of 40 MHz. This device concept also provides a platform for exploring cavity-enhanced light-matter interactions and optical processes in graphene plasmonic structures for applications including sensing, photo-detection and nonlinear frequency generation

Intermittency and Universality in Fully-Developed Inviscid and Weakly-Compressible Turbulent Flows

We performed high resolution numerical simulations of homogenous and isotropic compressible turbulence, with an average 3D Mach number close to 0.3. We study the statistical properties of intermittency for velocity, density and entropy. For the velocity field, which is the primary quantity that can be compared to the isotropic incompressible case, we find no statistical differences in its behavior in the inertial range due either to the slight compressibility or to the different dissipative mechanism. For the density field, we find evidence of ``front-like'' structures, although no shocks are produced by the simulation.Comment: Submitted to Phys. Rev. Let

Replica Cluster Variational Method: the Replica Symmetric solution for the 2D random bond Ising model

We present and solve the Replica Symmetric equations in the context of the Replica Cluster Variational Method for the 2D random bond Ising model (including the 2D Edwards-Anderson spin glass model). First we solve a linearized version of these equations to obtain the phase diagrams of the model on the square and triangular lattices. In both cases the spin-glass transition temperatures and the tricritical point estimations improve largely over the Bethe predictions. Moreover, we show that this phase diagram is consistent with the behavior of inference algorithms on single instances of the problem. Finally, we present a method to consistently find approximate solutions to the equations in the glassy phase. The method is applied to the triangular lattice down to T=0, also in the presence of an external field.Comment: 22 pages, 11 figure

Setting limits on Effective Field Theories: the case of Dark Matter

The usage of Effective Field Theories (EFT) for LHC new physics searches is receiving increasing attention. It is thus important to clarify all the aspects related with the applicability of the EFT formalism in the LHC environment, where the large available energy can produce reactions that overcome the maximal range of validity, i.e. the cutoff, of the theory. We show that this does forbid to set rigorous limits on the EFT parameter space through a modified version of the ordinary binned likelihood hypothesis test, which we design and validate. Our limit-setting strategy can be carried on in its full-fledged form by the LHC experimental collaborations, or performed externally to the collaborations, through the Simplified Likelihood approach, by relying on certain approximations. We apply it to the recent CMS mono-jet analysis and derive limits on a Dark Matter (DM) EFT model. DM is selected as a case study because the limited reach on the DM production EFT Wilson coefficient and the structure of the theory suggests that the cutoff might be dangerously low, well within the LHC reach. However our strategy can also be applied to EFT's parametrising the indirect effects of heavy new physics in the Electroweak and Higgs sectors

Ablation of SGK1 Impairs Endothelial Cell Migration and Tube Formation Leading to Decreased Neo-Angiogenesis Following Myocardial Infarction

Serum and glucocorticoid inducible kinase 1 (SGK1) plays a pivotal role in early angiogenesis during embryonic development. In this study, we sought to define the SGK1 downstream signalling pathways in the adult heart and to elucidate their role in cardiac neo-angiogenesis and wound healing after myocardial ischemia. To this end, we employed a viable SGK1 knockout mouse model generated in a 129/SvJ background. Ablation of SGK1 in these mice caused a significant decrease in phosphorylation of SGK1 target protein NDRG1, which correlated with alterations in NF-κB signalling and expression of its downstream target protein, VEGF-A. Disruption of these signalling pathways was accompanied by smaller heart and body size. Moreover, the lack of SGK1 led to defective endothelial cell (ECs) migration and tube formation in vitro, and increased scarring with decreased angiogenesis in vivo after myocardial infarct. This study underscores the importance of SGK1 signalling in cardiac neo-angiogenesis and wound healing after an ischemic insult in vivo

The first Automatic Translation Memory Cleaning Shared Task

This is an accepted manuscript of an article published by Springer in Machine Translation on 21/01/2017, available online: https://doi.org/10.1007/s10590-016-9183-x The accepted version of the publication may differ from the final published version.This paper reports on the organization and results of the rst Automatic Translation Memory Cleaning Shared Task. This shared task is aimed at nding automatic ways of cleaning translation memories (TMs) that have not been properly curated and thus include incorrect translations. As a follow up of the shared task, we also conducted two surveys, one targeting the teams participating in the shared task, and the other one targeting professional translators. While the researchers-oriented survey aimed at gathering information about the opinion of participants on the shared task, the translators-oriented survey aimed to better understand what constitutes a good TM unit and inform decisions that will be taken in future editions of the task. In this paper, we report on the process of data preparation and the evaluation of the automatic systems submitted, as well as on the results of the collected surveys

A Scalable and Extensible Approach to Benchmarking NL2Code for 18 Programming Languages

Large language models have demonstrated the ability to condition on and generate both natural language and programming language text. Such models open up the possibility of multi-language code generation: could code generation models generalize knowledge from one language to another? Although contemporary code generation models can generate semantically correct Python code, little is known about their abilities with other languages. We facilitate the exploration of this topic by proposing MultiPL-E, the first multi-language parallel benchmark for natural-language-to-code-generation. MultiPL-E extends the HumanEval benchmark (Chen et al, 2021) to support 18 more programming languages, encompassing a range of programming paradigms and popularity. We evaluate two state-of-the-art code generation models on MultiPL-E: Codex and InCoder. We find that on several languages, Codex matches and even exceeds its performance on Python. The range of programming languages represented in MultiPL-E allow us to explore the impact of language frequency and language features on model performance. Finally, the MultiPL-E approach of compiling code generation benchmarks to new programming languages is both scalable and extensible. We describe a general approach for easily adding support for new benchmarks and languages to MultiPL-E