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In recent years, the large electric field enhancement and tight spatial confinement supported by the so-called epsilon near-zero (ENZ) mode has attracted significant attention for the realization of efficient nonlinear optical devices. Here, we experimentally demonstrate ENZ photonic gap antennas (PGAs), which consist of a dielectric pillar within which a thin slab of indium tin oxide (ITO) material is embedded. In ENZ PGAs, hybrid dielectric-ENZ modes emerge from strong coupling between the dielectric antenna modes and the ENZ bulk plasmon resonance. These hybrid modes efficiently couple to free space and allow for large enhancements of the incident electric field over nearly an octave bandwidth, without the stringent lateral nanofabrication requirements of conventional plasmonic or dielectric nanoantennas. To understand the modal features, we probe the linear response of single ENZ PGAs with dark field scattering and interpret the results in terms of a simple coupled oscillator framework. Third harmonic generation (THG) is used to probe the ITO local fields and large enhancements are observed in the THG efficiency over a broad spectral range. Surprisingly, sharp peaks emerge on top of the nonlinear response, which were not predicted by full wave calculations. These peaks are attributed to the ENZ material's nonlocal response, which once included using a hydrodynamic model for the ITO permittivity improves the agreement of our calculations for both the linear and nonlinear response. This proof of concept demonstrates the potential of ENZ PGAs, which we have previously shown can support electric field enhancements of up to 100--200X, and the importance of including nonlocal effects when describing the response of thin ENZ layers. Importantly, inclusion of the ITO nonlocality leads to increases in the predicted field enhancement, as compared to the local calculation., Comment: arXiv admin note: substantial text overlap with arXiv:2211.05214

We introduce contextads and the Ctx construction, unifying various structures and constructions in category theory dealing with context and contextful arrows -- comonads and their Kleisli construction, actegories and their Para construction, adequate triples and their Span construction. Contextads are defined in terms of Lack--Street wreaths, suitably categorified for pseudomonads in a tricategory of spans in a 2-category with display maps. The associated wreath product provides the Ctx construction, and by its universal property we conclude trifunctoriality. This abstract approach lets us work up to structure, and thus swiftly prove that, under very mild assumptions, a contextad equipped colaxly with a 2-algebraic structure produces a similarly structured double category of contextful arrows. We also explore the role contextads might play qua dependently graded comonads in organizing contextful computation in functional programming. We show that many side-effects monads can be dually captured by dependently graded comonads, and gesture towards a general result on the `transposability' of parametric right adjoint monads to dependently graded comonads., Comment: 84 pages

We present a careful calibration of the exciton fraction of polaritons in high-$Q$ ($\sim 300,000$), long-lifetime ($\sim 300$ ps), GaAs/AlGaAs microcavities.This is a crucial parameter for many-body theories which include the polariton-polariton interactions.It is much harder to establish this number in high-$Q$ structures compared to low-$Q$ structures, because the upper polariton is nearly invisible in high-$Q$ cavities.We present a combination of photoluminescence, photoluminescence excitation, and reflectivity measurements to highly constrain the fit model, and compare the results of this model to the results from low-$Q$ structures.We present a fitted curve of exciton fraction as a function of the lower polariton energy for multiple samples which have been used in prior experiments., Comment: 16 pages, 11 figures

Social media platforms can quickly disseminate STEM content to diverse audiences, but their operation can be mysterious. We used open-source machine learning methods such as clustering, regression, and sentiment analysis to analyze over 1000 videos and metrics thereof from 6 social media STEM creators. Our data provide insights into how audiences generate interest signals(likes, bookmarks, comments, shares), on the correlation of various signals with views, and suggest that content from newer creators is disseminated differently. We also share insights on how to optimize dissemination by analyzing data available exclusively to content creators as well as via sentiment analysis of comments., Comment: 17 pages, 3 figures, 3 supplemental figures