1,148 research outputs found

    Trapped modes in finite quantum waveguides

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    The Laplace operator in infinite quantum waveguides (e.g., a bent strip or a twisted tube) often has a point-like eigenvalue below the essential spectrum that corresponds to a trapped eigenmode of finite L2 norm. We revisit this statement for resonators with long but finite branches that we call "finite waveguides". Although now there is no essential spectrum and all eigenfunctions have finite L2 norm, the trapping can be understood as an exponential decay of the eigenfunction inside the branches. We describe a general variational formalism for detecting trapped modes in such resonators. For finite waveguides with general cylindrical branches, we obtain a sufficient condition which determines the minimal length of branches for getting a trapped eigenmode. Varying the branch lengths may switch certain eigenmodes from non-trapped to trapped states. These concepts are illustrated for several typical waveguides (L-shape, bent strip, crossing of two stripes, etc.). We conclude that the well-established theory of trapping in infinite waveguides may be incomplete and require further development for being applied to microscopic quantum devices

    1-D Convolutional Graph Convolutional Networks for Fault Detection in Distributed Energy Systems

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    This paper presents a 1-D convolutional graph neural network for fault detection in microgrids. The combination of 1-D convolutional neural networks (1D-CNN) and graph convolutional networks (GCN) helps extract both spatial-temporal correlations from the voltage measurements in microgrids. The fault detection scheme includes fault event detection, fault type and phase classification, and fault location. There are five neural network model training to handle these tasks. Transfer learning and fine-tuning are applied to reduce training efforts. The combined recurrent graph convolutional neural networks (1D-CGCN) is compared with the traditional ANN structure on the Potsdam 13-bus microgrid dataset. The achievable accuracy of 99.27%, 98.1%, 98.75%, and 95.6% for fault detection, fault type classification, fault phase identification, and fault location respectively.Comment: arXiv admin note: text overlap with arXiv:2210.1517

    Direct measurements of DOCO isomers in the kinetics of OD+CO

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    Quantitative and mechanistically-detailed kinetics of the reaction of hydroxyl radical (OH) with carbon monoxide (CO) have been a longstanding goal of contemporary chemical kinetics. This fundamental prototype reaction plays an important role in atmospheric and combustion chemistry, motivating studies for accurate determination of the reaction rate coefficient and its pressure and temperature dependence at thermal reaction conditions. This intricate dependence can be traced directly to details of the underlying dynamics (formation, isomerization, and dissociation) involving the reactive intermediates cis- and trans-HOCO, which can only be observed transiently. Using time-resolved frequency comb spectroscopy, comprehensive mechanistic elucidation of the kinetics of the isotopic analogue deuteroxyl radical (OD) with CO has been realized. By monitoring the concentrations of reactants, intermediates, and products in real-time, the branching and isomerization kinetics and absolute yields of all species in the OD+CO reaction are quantified as a function of pressure and collision partner.Comment: 19 pages, 4 figure

    When can we reconstruct the ancestral state? Beyond Brownian motion

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    Reconstructing the ancestral state of a group of species helps answer many important questions in evolutionary biology. Therefore, it is crucial to understand when we can estimate the ancestral state accurately. Previous works provide a necessary and sufficient condition, called the big bang condition, for the existence of an accurate reconstruction method under discrete trait evolution models and the Brownian motion model. In this paper, we extend this result to a wide range of continuous trait evolution models. In particular, we consider a general setting where continuous traits evolve along the tree according to stochastic processes that satisfy some regularity conditions. We verify these conditions for popular continuous trait evolution models including Ornstein-Uhlenbeck, reflected Brownian Motion, and Cox-Ingersoll-Ross

    Detection of lithium in nearby young late-M dwarfs

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    Late M-type dwarfs in the solar neighborhood include a mixture of very low-mass stars and brown dwarfs which is difficult to disentangle due to the lack of constraints on their age such as trigonometric parallax, lithium detection and space velocity. We search for young brown dwarf candidates among a sample of 28 nearby late-M dwarfs with spectral types between M5.0 and M9.0, and we also search for debris disks around three of them. Based on theoretical models, we used the color I−JI-J, the JJ-band absolute magnitude and the detection of the Li I 6708 A˚\AA doublet line as a strong constraint to estimate masses and ages of our targets. For the search of debris disks, we observed three targets at submillimeter wavelength of 850 μ\mum. We report here the first clear detections of lithium absorption in four targets and a marginal detection in one target. Our mass estimates indicate that two of them are young brown dwarfs, two are young brown dwarf candidates and one is a young very low-mass star. The closest young field brown dwarf in our sample at only ∼\sim15 pc is an excellent benchmark for further studying physical properties of brown dwarfs in the range 100−-150 Myr. We did not detect any debris disks around three late-M dwarfs, and we estimated upper limits to the dust mass of debris disks around them.Comment: 10 pages, 5 figures, accepted for publication in Astronomy and Astrophysic
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