Interaction of Atmospheric Pressure Plasma Jets with Liquids

In this work, the interaction of atmospheric pressure plasmas with liquids is investigated. On the exampleof hydrogen peroxide, generation and transport mechanisms are studied from the plasma to the gas- andliquid phase. Interaction with the ambient surroundings is investigated and effects of nitrogen and oxygenspecies on the plasma dynamics a well as on the reactive species generation in the liquid phase arediscusse

Surrogate Models and Mixtures of Experts in Aerodynamic Performance Prediction for Mission Analysis

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140436/1/6.2014-2301.pd

Enhancement of Rydberg-mediated single-photon nonlinearities by electrically tuned Förster resonances

We demonstrate experimentally that Stark-tuned Förster resonances can be used to substantially increase the interaction between individual photons mediated by Rydberg interaction inside an optical medium. This technique is employed to boost the gain of a Rydberg-mediated single-photon transistor and to enhance the non-destructive detection of single Rydberg atoms. Furthermore, our all-optical detection scheme enables high-resolution spectroscopy of two-state Förster resonances, revealing the fine structure splitting of high-n Rydberg states and the non-degeneracy of Rydberg Zeeman substates in finite fields. We show that the ∣50S1/2,48S1/2⟩↔∣49P1/2,48P1/2⟩ pair state resonance in 87Rb enables simultaneously a transistor gain G>100 and all-optical detection fidelity of single Rydberg atoms F>0.8. We demonstrate for the first time the coherent operation of the Rydberg transistor with G>2 by reading out the gate photon after scattering source photons. Comparison of the observed readout efficiency to a theoretical model for the projection of the stored spin wave yields excellent agreement and thus successfully identifies the main decoherence mechanism of the Rydberg transistor

Plasma–liquid interactions: a review and roadmap

Plasma–liquid interactions represent a growing interdisciplinary area of research involving plasma science, fluid dynamics, heat and mass transfer, photolysis, multiphase chemistry and aerosol science. This review provides an assessment of the state-of-the-art of this multidisciplinary area and identifies the key research challenges. The developments in diagnostics, modeling and further extensions of cross section and reaction rate databases that are necessary to address these challenges are discussed. The review focusses on non-equilibrium plasmas

SegPGD: an effective and efficient adversarial attack for evaluating and boosting segmentation robustness

Deep neural network-based image classifications are vulnerable to adversarial perturbations. The image classifications can be easily fooled by adding artificial small and imperceptible perturbations to input images. As one of the most effective defense strategies, adversarial training was proposed to address the vulnerability of classification models, where the adversarial examples are created and injected into training data during training. The attack and defense of classification models have been intensively studied in past years. Semantic segmentation, as an extension of classifications, has also received great attention recently. Recent work shows a large number of attack iterations are required to create effective adversarial examples to fool segmentation models. The observation makes both robustness evaluation and adversarial training on segmentation models challenging. In this work, we propose an effective and efficient segmentation attack method, dubbed SegPGD. Besides, we provide a convergence analysis to show the proposed SegPGD can create more effective adversarial examples than PGD under the same number of attack iterations. Furthermore, we propose to apply our SegPGD as the underlying attack method for segmentation adversarial training. Since SegPGD can create more effective adversarial examples, the adversarial training with our SegPGD can boost the robustness of segmentation models. Our proposals are also verified with experiments on popular Segmentation model architectures and standard segmentation datasets