Controlled photon transfer between two individual nanoemitters via shared high-Q modes of a microsphere resonator

We realize controlled cavity-mediated photon transfer between two single nanoparticles over a distance of several tens of micrometers. First, we show how a single nanoscopic emitter attached to a near-field probe can be coupled to high-Q whispering-gallery modes of a silica microsphere at will. Then we demonstrate transfer of energy between this and a second nanoparticle deposited on the sphere surface. We estimate the photon transfer efficiency to be about six orders of magnitude higher than that via free space propagation at comparable separations.Comment: accepted for publication in Nano Letter

First Detection of a Strong Magnetic Field on a Bursty Brown Dwarf: Puzzle Solved

We report the first direct detection of a strong, 5 kG magnetic field on the surface of an active brown dwarf. LSR J1835+3259 is an M8.5 dwarf exhibiting transient radio and optical emission bursts modulated by fast rotation. We have detected the surface magnetic field as circularly polarized signatures in the 819 nm sodium lines when an active emission region faced the Earth. Modeling Stokes profiles of these lines reveals the effective temperature of 2800 K and log gravity acceleration of 4.5. These parameters place LSR J1835+3259 on evolutionary tracks as a young brown dwarf with the mass of 55$\pm$4 M$_{\rm J}$ and age of 22$\pm$4 Myr. Its magnetic field is at least 5.1 kG and covers at least 11% of the visible hemisphere. The active region topology recovered using line profile inversions comprises hot plasma loops with a vertical stratification of optical and radio emission sources. These loops rotate with the dwarf in and out of view causing periodic emission bursts. The magnetic field is detected at the base of the loops. This is the first time that we can quantitatively associate brown dwarf non-thermal bursts with a strong, 5 kG surface magnetic field and solve the puzzle of their driving mechanism. This is also the coolest known dwarf with such a strong surface magnetic field. The young age of LSR J1835+3259 implies that it may still maintain a disk, which may facilitate bursts via magnetospheric accretion, like in higher-mass T Tau-type stars. Our results pave a path toward magnetic studies of brown dwarfs and hot Jupiters.Comment: ApJ, in pres

Witnessing Entanglement of EPR States With Second-Order Interference

The separability of the continuous-variable EPR state can be tested with Hanbury-Brown and Twiss type interference. The second-order visibility of such interference can provide an experimental test of entanglement. It is shown that time-resolved interference leads to the Hong, Ou and Mandel deep, that provides a signature of quantum non-separability for pure and mixed EPR states. A Hanbury-Brown and Twiss type witness operator can be constructed to test the quantum nature of the EPR entanglement.Comment: 9 pages, 5 figure

Computing evolutionary distinctiveness indices in large scale analysis

We present optimal linear time algorithms for computing the Shapley values and 'heightened evolutionary distinctiveness' (HED) scores for the set of taxa in a phylogenetic tree. We demonstrate the efficiency of these new algorithms by applying them to a set of 10,000 reasonable 5139-species mammal trees. This is the first time these indices have been computed on such a large taxon and we contrast our finding with an ad-hoc index for mammals, fair proportion (FP), used by the Zoological Society of London's EDGE programme. Our empirical results follow expectations. In particular, the Shapley values are very strongly correlated with the FP scores, but provide a higher weight to the few monotremes that comprise the sister to all other mammals. We also find that the HED score, which measures a species' unique contribution to future subsets as function of the probability that close relatives will go extinct, is very sensitive to the estimated probabilities. When they are low, HED scores are less than FP scores, and approach the simple measure of a species' age. Deviations (like the Solendon genus of the West Indies) occur when sister species are both at high risk of extinction and their clade roots deep in the tree. Conversely, when endangered species have higher probabilities of being lost, HED scores can be greater than FP scores and species like the African elephant Loxondonta africana, the two solendons and the thumbless bat Furipterus horrens can move up the rankings. We suggest that conservation attention be applied to such species that carry genetic responsibility for imperiled close relatives. We also briefly discuss extensions of Shapley values and HED scores that are possible with the algorithms presented here

Kinetic modeling and simulation of high-temperature by-product formation from urea decomposition

The Selective catalytic reduction (SCR) technique is widely applied in exhaust gas after-treatment of diesel engines. Depending on operating conditions, injected urea-water solution (UWS) can form liquid films on mixer blades and the pipe wall. Evaporation and subsequent reactions in the wall film can lead to deposits of urea and by-products, respectively. Especially deposits that are not decomposed up to high temperatures are challenging for the SCR technique. Thermogravimetric experiments are conducted for these stable urea by-products, such as ammelide, ammeline and their by-products, such as cyanamide or melamine. An analysis of the evolving gases during thermal decomposition led to a more detailed understanding of the kinetics. The postulated mechanism is able to predict the thermogravimetric analyses results and the effects of variation of the experimental conditions such as initial sample mass and heating rates. The evaluated kinetics, together with the recently developed kinetics for the urea/biuret/triuret/cyanuric acid system Tischer et al. (2019), can now be integrated into CFD simulations of SCR systems to numerically simulate all relevant physical and chemical processes in UWS equipped aftertreatment systems for a wide range of conditions

Iron as recyclable energy carrier: Feasibility study and kinetic analysis of iron oxide reduction

Carbon-free and sustainable energy storage solutions are required to mitigate climate change. One possible solution, especially for stationary applications, could be the storage of energy in metal fuels. Energy can be stored through reduction of the oxide with green hydrogen and be released by combustion. In this work a feasibility study for iron as possible metal fuel considering the complete energy cycle is conducted. On the basis of equilibrium calculations it could be shown that the power-to-power efficiency of the iron/iron oxide cycle is 27 %. As technology development requires a more detailed description of both the reduction and the oxidation, a first outlook is given on the kinetic analysis of the reduction of iron oxides with hydrogen. Thermogravimetric experiments using Fe$_2$O$_3$, Fe$_3$O$_4$ and FeO indicate a three-step process for the reduction. The maximum reduction rate can be achieved with a hydrogen content of 25 %. Based on the experimental results a reaction mechanism and accompanied kinetic data were developed for description of Fe$_2$O$_3$ reduction with H$_2$ under varying experimental conditions

Adaptive Evolutionary Clustering

In many practical applications of clustering, the objects to be clustered evolve over time, and a clustering result is desired at each time step. In such applications, evolutionary clustering typically outperforms traditional static clustering by producing clustering results that reflect long-term trends while being robust to short-term variations. Several evolutionary clustering algorithms have recently been proposed, often by adding a temporal smoothness penalty to the cost function of a static clustering method. In this paper, we introduce a different approach to evolutionary clustering by accurately tracking the time-varying proximities between objects followed by static clustering. We present an evolutionary clustering framework that adaptively estimates the optimal smoothing parameter using shrinkage estimation, a statistical approach that improves a naive estimate using additional information. The proposed framework can be used to extend a variety of static clustering algorithms, including hierarchical, k-means, and spectral clustering, into evolutionary clustering algorithms. Experiments on synthetic and real data sets indicate that the proposed framework outperforms static clustering and existing evolutionary clustering algorithms in many scenarios.Comment: To appear in Data Mining and Knowledge Discovery, MATLAB toolbox available at http://tbayes.eecs.umich.edu/xukevin/affec