Evolutions of helical edge states in disordered HgTe/CdTe quantum wells

We study the evolutions of the nonmagnetic disorder-induced edge states with the disorder strength in the HgTe/CdTe quantum wells. From the supercell band structures and wave-functions, it is clearly shown that the conducting helical edge states, which are responsible for the reported quantized conductance plateau, appear above a critical disorder strength after a gap-closing phase transition. These edge states are then found to decline with the increase of disorder strength in a stepwise pattern due to the finite-width effect, where the opposite edges couple with each other through the localized states in the bulk. This is in sharp contrast with the localization of the edge states themselves if magnetic disorders are doped which breaks the time-reversal symmetry. The size-independent boundary of the topological phase is obtained by scaling analysis, and an Anderson transition to an Anderson insulator at even stronger disorder is identified, in-between of which, a metallic phase is found to separate the two topologically distinct phases.Comment: 7 pages, 5 figure

Fidelity estimation of quantum states on a silicon photonic chip

As a measure of the 'closeness' of two quantum states, fidelity plays a fundamental role in quantum information theory. Fidelity estimation protocols try to strike a balance between information gleaned from an experiment, and the efficiency of its implementation, in terms of the number of states consumed by the protocol. Here we adapt a previously reported optimal state verification protocol (Phys. Rev. Lett. 120, 170502, 2018) for fidelity estimation of two-qubit states. We demonstrate the protocol experimentally using a fully-programmable silicon photonic two-qubit chip. Our protocol outputs significantly smaller error bars of its point estimate in comparison with another widely-used estimation protocol, showing a clear step forward in the ability to estimate the fidelity of quantum states produced by a practical device

Fidelity estimation of quantum states on a silicon photonic chip

As a measure of the 'closeness' of two quantum states, fidelity plays a fundamental role in quantum information theory. Fidelity estimation protocols try to strike a balance between information gleaned from an experiment, and the efficiency of its implementation, in terms of the number of states consumed by the protocol. Here we adapt a previously reported optimal state verification protocol (Phys. Rev. Lett. 120, 170502, 2018) for fidelity estimation of two-qubit states. We demonstrate the protocol experimentally using a fully-programmable silicon photonic two-qubit chip. Our protocol outputs significantly smaller error bars of its point estimate in comparison with another widely-used estimation protocol, showing a clear step forward in the ability to estimate the fidelity of quantum states produced by a practical device

Dynamic fusion with intra-and inter-modality attention flow for visual question answering

Learning effective fusion of multi-modality features is at the heart of visual question answering. We propose a novel method of dynamically fusing multi-modal features with intra- and inter-modality information flow, which alternatively pass dynamic information between and across the visual and language modalities. It can robustly capture the high-level interactions between language and vision domains, thus significantly improves the performance of visual question answering. We also show that the proposed dynamic intra-modality attention flow conditioned on the other modality can dynamically modulate the intra-modality attention of the target modality, which is vital for multimodality feature fusion. Experimental evaluations on the VQA 2.0 dataset show that the proposed method achieves state-of-the-art VQA performance. Extensive ablation studies are carried out for the comprehensive analysis of the proposed method.Comment: CVPR 2019 ORA

Release of Staphylococcus aureus extracellular vesicles and their application as a vaccine platform

Secretion of extracellular vesicles (EVs), a process common to eukaryotes, archae, and bacteria, represents a secretory pathway that allows cell-free intercellular communication. Microbial EVs package diverse proteins and influence the host-pathogen interaction, but the mechanisms underlying EV production in Gram-positive bacteria are poorly understood. Here we show that EVs purified from community-associated methicillin-resistant Staphylococcus aureus package cytosolic, surface, and secreted proteins, including cytolysins. Staphylococcal alpha-type phenol-soluble modulins promote EV biogenesis by disrupting the cytoplasmic membrane; whereas, peptidoglycan cross-linking and autolysin activity modulate EV production by altering the permeability of the cell wall. We demonstrate that EVs purified from a S. aureus mutant that is genetically engineered to express detoxified cytolysins are immunogenic in mice, elicit cytolysin-neutralizing antibodies, and protect the animals in a lethal sepsis model. Our study reveals mechanisms underlying S. aureus EV production and highlights the usefulness of EVs as a S. aureus vaccine platform

Provenance documentation to enable explainable and trustworthy AI: A literature review

ABSTRACTRecently artificial intelligence (AI) and machine learning (ML) models have demonstrated remarkable progress with applications developed in various domains. It is also increasingly discussed that AI and ML models and applications should be transparent, explainable, and trustworthy. Accordingly, the field of Explainable AI (XAI) is expanding rapidly. XAI holds substantial promise for improving trust and transparency in AI-based systems by explaining how complex models such as the deep neural network (DNN) produces their outcomes. Moreover, many researchers and practitioners consider that using provenance to explain these complex models will help improve transparency in AI-based systems. In this paper, we conduct a systematic literature review of provenance, XAI, and trustworthy AI (TAI) to explain the fundamental concepts and illustrate the potential of using provenance as a medium to help accomplish explainability in AI-based systems. Moreover, we also discuss the patterns of recent developments in this area and offer a vision for research in the near future. We hope this literature review will serve as a starting point for scholars and practitioners interested in learning about essential components of provenance, XAI, and TAI

Convolution surfaces with varying radius: Formulae for skeletons made of arcs of circles and line segments

International audienceWe develop closed form formulae for the computation of the defining fields of convolutions surfaces. The formulae are obtained for power inverse kernels with skeletons made of line segments or arcs of circle. To obtain the formulae we use Creative Telescoping and describe how this technique can be used for other families of kernels and skeleton primitives. We apply the new formulae to obtain convolution surfaces around $\mathcal{G}^1$ skeletons, some of them closed curves. We showcase how the use of arcs of circles greatly improves the visualization of the surface around a general curve compared with a segment based approach

Optical Coherence Tomography Angiography of Optic Disc Perfusion in Glaucoma

Purpose To compare optic disc perfusion between normal subjects and subjects with glaucoma using optical coherence tomography (OCT) angiography and to detect optic disc perfusion changes in glaucoma. Design Observational, cross-sectional study. Participants Twenty-four normal subjects and 11 patients with glaucoma were included. Methods One eye of each subject was scanned by a high-speed 1050-nm–wavelength swept-source OCT instrument. The split-spectrum amplitude-decorrelation angiography (SSADA) algorithm was used to compute 3-dimensional optic disc angiography. A disc flow index was computed from 4 registered scans. Confocal scanning laser ophthalmoscopy (cSLO) was used to measure disc rim area, and stereo photography was used to evaluate cup/disc (C/D) ratios. Wide-field OCT scans over the discs were used to measure retinal nerve fiber layer (NFL) thickness. Main Outcome Measures Variability was assessed by coefficient of variation (CV). Diagnostic accuracy was assessed by sensitivity and specificity. Comparisons between glaucoma and normal groups were analyzed by Wilcoxon rank-sum test. Correlations among disc flow index, structural assessments, and visual field (VF) parameters were assessed by linear regression. Results In normal discs, a dense microvascular network was visible on OCT angiography. This network was visibly attenuated in subjects with glaucoma. The intra-visit repeatability, inter-visit reproducibility, and normal population variability of the optic disc flow index were 1.2%, 4.2%, and 5.0% CV, respectively. The disc flow index was reduced by 25% in the glaucoma group (P = 0.003). Sensitivity and specificity were both 100% using an optimized cutoff. The flow index was highly correlated with VF pattern standard deviation (R[superscript 2] = 0.752, P = 0.001). These correlations were significant even after accounting for age, C/D area ratio, NFL, and rim area. Conclusions Optical coherence tomography angiography, generated by the new SSADA, repeatably measures optic disc perfusion and may be useful in the evaluation of glaucoma and glaucoma progression.National Institutes of Health (U.S.) (Grant 1R01 EY023285-01)Rosenbaum's P30EY010572National Institutes of Health (U.S.). Clinical and Translational Science Awards (CTSA) Program (Grant UL1TR000128)Research to Prevent Blindness, Inc. (United States) (Grant R01-EY11289-26)United States. Air Force Office of Scientific Research (FA9550-10-1-0551)German Research Foundation (DFG-HO-1791/11-1)German Research Foundation (DFG-GSC80-SAOT)German Research Foundation (Training Group 1773