9,402 research outputs found

    Kinetics and Products of the Acid-Catalyzed Ring-Opening of Atmospherically Relevant Butyl Epoxy Alcohols

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    Epoxydiols are produced in the gas phase from the photo-oxidation of isoprene in the absence of significant mixing ratios of nitrogen oxides (NO_x). The reactive uptake of these compounds onto acidic aerosols has been shown to produce secondary organic aerosol (SOA). To better characterize the fate of isoprene epoxydiols in the aerosol phase, the kinetics and products of the acid-catalyzed ring-opening reactions of four hydroxy-substituted epoxides were studied by nuclear magnetic resonance (NMR) techniques. Polyols and sulfate esters are observed from the ring-opening of the epoxides in solutions of H_2SO_4/Na_2SO_4. Likewise, polyols and nitrate esters are produced in solutions of HNO_3/NaNO_3. In sulfuric acid, the rate of acid-catalyzed ring-opening is dependent on hydronium ion activity, sulfate ion, and bisulfate. The rates are much slower than the nonhydroxylated equivalent epoxides; however, the hydroxyl groups make them much more water-soluble. A model was constructed with the major channels for epoxydiol loss (i.e., aerosol-phase ring-opening, gas-phase oxidation, and deposition). In the atmosphere, SOA formation from epoxydiols will depend on a number of variables (e.g., pH and aerosol water content) with the yield of ring-opening products varying from less than 1% to greater than 50%

    Field-assisted Shockley-Read-Hall recombinations in III-Nitride quantum wells

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    The physical process driving low-current non-radiative recombinations in high-quality III-Nitride quantum wells is investigated. Lifetime measurements reveal that these recombinations scale with the overlap of the electron and hole wavefunctions and show weak temperature dependence, in contrast with common empirical expectations for Shockley-Read-Hall recombinations. A model of field-assisted multiphonon point defect recombination in quantum wells is introduced, and shown to quantitatively explain the data. This study provides insight on the high efficiency of III-Nitride light emitters

    Quantum Hamiltonian Learning Using Imperfect Quantum Resources

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    Identifying an accurate model for the dynamics of a quantum system is a vexing problem that underlies a range of problems in experimental physics and quantum information theory. Recently, a method called quantum Hamiltonian learning has been proposed by the present authors that uses quantum simulation as a resource for modeling an unknown quantum system. This approach can, under certain circumstances, allow such models to be efficiently identified. A major caveat of that work is the assumption of that all elements of the protocol are noise-free. Here, we show that quantum Hamiltonian learning can tolerate substantial amounts of depolarizing noise and show numerical evidence that it can tolerate noise drawn from other realistic models. We further provide evidence that the learning algorithm will find a model that is maximally close to the true model in cases where the hypothetical model lacks terms present in the true model. Finally, we also provide numerical evidence that the algorithm works for non-commuting models. This work illustrates that quantum Hamiltonian learning can be performed using realistic resources and suggests that even imperfect quantum resources may be valuable for characterizing quantum systems.Comment: 16 pages 11 Figure

    Invasive Wild pigs as primary nest predators for Wild turkeys

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    Depredation of wild turkey (Meleagris gallopavo) nests is a leading cause of reduced recruitment for the recovering and iconic game species. invasive wild pigs (Sus scrofa) are known to depredate nests, and have been expanding throughout the distributed range of wild turkeys in north America. We sought to gain better insight on the magnitude of wild pigs depredating wild turkey nests. We constructed simulated wild turkey nests throughout the home ranges of 20 GPS-collared wild pigs to evaluate nest depredation relative to three periods within the nesting season (i.e., early, peak, and late) and two nest densities (moderate = 12.5-25 nests/km2, high = 25-50 nests/km2) in south-central Texas, USA during March–June 2016. Overall, the estimated probability of nest depredation by wild pigs was 0.3, equivalent to native species of nest predators in the study area (e.g., gray fox [Urocyon cinereoargenteus], raccoon [Procyon lotor], and coyote [Canis latrans]). female wild pigs exhibited a constant rate of depredation regardless of nesting period or density of nests. However, male wild pigs increased their rate of depredation in areas with higher nest densities. Management efforts should remove wild pigs to reduce nest failure in wild turkey populations especially where recruitment is low

    Paradoxical popups: Why are they hard to catch?

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    Even professional baseball players occasionally find it difficult to gracefully approach seemingly routine pop-ups. This paper describes a set of towering pop-ups with trajectories that exhibit cusps and loops near the apex. For a normal fly ball, the horizontal velocity is continuously decreasing due to drag caused by air resistance. But for pop-ups, the Magnus force (the force due to the ball spinning in a moving airflow) is larger than the drag force. In these cases the horizontal velocity decreases in the beginning, like a normal fly ball, but after the apex, the Magnus force accelerates the horizontal motion. We refer to this class of pop-ups as paradoxical because they appear to misinform the typically robust optical control strategies used by fielders and lead to systematic vacillation in running paths, especially when a trajectory terminates near the fielder. In short, some of the dancing around when infielders pursue pop-ups can be well explained as a combination of bizarre trajectories and misguidance by the normally reliable optical control strategy, rather than apparent fielder error. Former major league infielders confirm that our model agrees with their experiences.Comment: 28 pages, 10 figures, sumitted to American Journal of Physic

    Behavioral modeling of integrated phase-change photonic devices for neuromorphic computing applications

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    The combination of phase-change materials and integrated photonics has led to the development of new forms of all-optical devices, including photonic memories, arithmetic and logic processors, and synaptic and neuronal mimics. Such devices can be readily fabricated into photonic integrated circuits, so potentially delivering large-scale all-optical arithmetic-logic units and neuromorphic processing chips. To facilitate in the design and optimization of such large-scale systems, and to aid in the understanding of device and system performance, fast yet accurate computer models are needed. Here, we describe the development of a behavioral modeling tool that meets such requirements, being capable of essentially instantaneous modeling of the write, erase, and readout performance of various integrated phase-change photonic devices, including those for synaptic and neuronal mimics
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