1,259 research outputs found

    Dynamic gain and frequency comb formation in exceptional-point lasers

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    Exceptional points (EPs)--singularities in the parameter space of non-Hermitian systems where two nearby eigenmodes coalesce--feature unique properties with applications for microcavity lasers such as sensitivity enhancement and chiral emission. Present EP lasers operate with static populations in the gain medium. Here, we show theoretically that a laser operating sufficiently close to an EP will spontaneously induce a multi-spectral multi-modal instability that creates an oscillating population inversion and generates a frequency comb. The comb formation is enhanced by the non-orthogonality of modes via the Petermann factor. Such an "EP comb" features an ultra-compact size and a widely tunable repetition rate, without requiring external modulators or a continuous-wave pump. We develop an exact ab initio dynamic solution of the space-dependent Maxwell-Bloch equations, describing all steady-state properties of the EP comb. We illustrate this phenomenon in a realistic parity-time-symmetric 5-{\mu}m-long AlGaAs cavity and validate our prediction with finite-difference time-domain simulations. This work reveals the rich physics that connect non-Hermitian degeneracies and the nonlinear dynamics of gain media to fundamentally alter the laser behavior

    Project RISE: Recognizing Industrial Smoke Emissions

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    Industrial smoke emissions pose a significant concern to human health. Prior works have shown that using Computer Vision (CV) techniques to identify smoke as visual evidence can influence the attitude of regulators and empower citizens to pursue environmental justice. However, existing datasets are not of sufficient quality nor quantity to train the robust CV models needed to support air quality advocacy. We introduce RISE, the first large-scale video dataset for Recognizing Industrial Smoke Emissions. We adopted a citizen science approach to collaborate with local community members to annotate whether a video clip has smoke emissions. Our dataset contains 12,567 clips from 19 distinct views from cameras that monitored three industrial facilities. These daytime clips span 30 days over two years, including all four seasons. We ran experiments using deep neural networks to establish a strong performance baseline and reveal smoke recognition challenges. Our survey study discussed community feedback, and our data analysis displayed opportunities for integrating citizen scientists and crowd workers into the application of Artificial Intelligence for social good.Comment: Technical repor

    Impact of the COVID-19 Pandemic on the Field of Orthopedics

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    During the COVID-19 pandemic, countries all over the world suffered from different kinds of service disruption or reduction in the field of orthopedics with or without lockdowns. The consequences include no restriction, partial disruption, overburden of medical services and complete shutdown of clinical practices. This chapter systematically reviews the current published literature on the global impact of COVID-19 on the field of orthopedics through multiple aspects, including educational impact, service volume impact, workload impact, personal practice change, psychological impact, and impact on orthopedic research. The rates of all surgeries and elective surgeries decreased by 15.6%–49.4% and 43.5–100%, respectively. The overall impact was attributable to the staff redeployment in response to the pandemic. Therefore, it is important to maintain a flexible allocation of manpower and more sufficient and reservable staffing measures in case of emergency staff shortages. Orthopedic surgeons are suggested to prepare proper preventive strategies and set up special equipment and places for regular telemedicine for virtual consultations or virtual teaching. It can be expected that the integration of the different experiences of global countries from the impact of COVID-19 may help us to face possible similar impacts in the future

    Disordered Fe vacancies and superconductivity in potassium-intercalated iron selenide (K2-xFe4+ySe5)

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    The parent compound of an unconventional superconductor must contain unusual correlated electronic and magnetic properties of its own. In the high-Tc potassium intercalated FeSe, there has been significant debate regarding what the exact parent compound is. Our studies unambiguously show that the Fe-vacancy ordered K2Fe4Se5 is the magnetic, Mott insulating parent compound of the superconducting state. Non-superconducting K2Fe4Se5 becomes a superconductor after high temperature annealing, and the overall picture indicates that superconductivity in K2-xFe4+ySe5 originates from the Fe-vacancy order to disorder transition. Thus, the long pending question whether magnetic and superconducting state are competing or cooperating for cuprate superconductors may also apply to the Fe-chalcogenide superconductors. It is believed that the iron selenides and related compounds will provide essential information to understand the origin of superconductivity in the iron-based superconductors, and possibly to the superconducting cuprates
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