First passage time distribution for a random walker on a random forcing energy landscape

We present an analytical approximation scheme for the first passage time distribution on a finite interval of a random walker on a random forcing energy landscape. The approximation scheme captures the behavior of the distribution over all timescales in the problem. The results are carefully checked against numerical simulations.Comment: 16 page

Photoionization in the time and frequency domain

Ultrafast processes in matter, such as the electron emission following light absorption, can now be studied using ultrashort light pulses of attosecond duration ($10^{-18}$s) in the extreme ultraviolet spectral range. The lack of spectral resolution due to the use of short light pulses may raise serious issues in the interpretation of the experimental results and the comparison with detailed theoretical calculations. Here, we determine photoionization time delays in neon atoms over a 40 eV energy range with an interferometric technique combining high temporal and spectral resolution. We spectrally disentangle direct ionization from ionization with shake up, where a second electron is left in an excited state, thus obtaining excellent agreement with theoretical calculations and thereby solving a puzzle raised by seven-year-old measurements. Our experimental approach does not have conceptual limits, allowing us to foresee, with the help of upcoming laser technology, ultra-high resolution time-frequency studies from the visible to the x-ray range.Comment: 5 pages, 4 figure

Folding of a donor–acceptor polyrotaxane by using noncovalent bonding interactions

Mechanically interlocked compounds, such as bistable catenanes and bistable rotaxanes, have been used to bring about actuation in nanoelectromechanical systems (NEMS) and molecular electronic devices (MEDs). The elaboration of the structural features of such rotaxanes into macromolecular materials might allow the utilization of molecular motion to impact their bulk properties. We report here the synthesis and characterization of polymers that contain π electron-donating 1,5-dioxynaphthalene (DNP) units encircled by cyclobis(paraquat-p-phenylene) (CBPQT4+), a π electron-accepting tetracationic cyclophane, synthesized by using the copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC). The polyrotaxanes adopt a well defined “folded” secondary structure by virtue of the judicious design of two DNP-containing monomers with different binding affinities for CBPQT4+. This efficient approach to the preparation of polyrotaxanes, taken alongside the initial investigations of their chemical properties, sets the stage for the preparation of a previously undescribed class of macromolecular architectures

Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods

We present a hierarchical Bayesian method for atmospheric trace gas inversions. This method is used to estimate emissions of trace gases as well as "hyper-parameters" that characterize the probability density functions (PDFs) of the a priori emissions and model-measurement covariances. By exploring the space of "uncertainties in uncertainties", we show that the hierarchical method results in a more complete estimation of emissions and their uncertainties than traditional Bayesian inversions, which rely heavily on expert judgment. We present an analysis that shows the effect of including hyper-parameters, which are themselves informed by the data, and show that this method can serve to reduce the effect of errors in assumptions made about the a priori emissions and model-measurement uncertainties. We then apply this method to the estimation of sulfur hexafluoride (SF6) emissions over 2012 for the regions surrounding four Advanced Global Atmospheric Gases Experiment (AGAGE) stations. We find that improper accounting of model representation uncertainties, in particular, can lead to the derivation of emissions and associated uncertainties that are unrealistic and show that those derived using the hierarchical method are likely to be more representative of the true uncertainties in the system. We demonstrate through this SF6 case study that this method is less sensitive to outliers in the data and to subjective assumptions about a priori emissions and model-measurement uncertainties than traditional methods

Recent and future trends in synthetic greenhouse gas radiative forcing

Atmospheric measurements show that emissions of hydrofluorocarbons (HFCs) and hydrochlorofluorocarbons are now the primary drivers of the positive growth in synthetic greenhouse gas (SGHG) radiative forcing. We infer recent SGHG emissions and examine the impact of future emissions scenarios, with a particular focus on proposals to reduce HFC use under the Montreal Protocol. If these proposals are implemented, overall SGHG radiative forcing could peak at around 355 mW m[superscript −2] in 2020, before declining by approximately 26% by 2050, despite continued growth of fully fluorinated greenhouse gas emissions. Compared to “no HFC policy” projections, this amounts to a reduction in radiative forcing of between 50 and 240 mW m[superscript −2] by 2050 or a cumulative emissions saving equivalent to 0.5 to 2.8 years of CO2 emissions at current levels. However, more complete reporting of global HFC emissions is required, as less than half of global emissions are currently accounted for.Natural Environment Research Council (Great Britain) (Advanced Research Fellowship NE/I021365/1)United States. National Aeronautics and Space Administration (Upper Atmospheric Research Program Grant NNX11AF17G)United States. National Oceanic and Atmospheric Administratio

The impact of neuron morphology on cortical network architecture

The neurons in the cerebral cortex are not randomly interconnected. This specificity in wiring can result from synapse formation mechanisms that connect neurons, depending on their electrical activity and genetically defined identity. Here, we report that the morphological properties of the neurons provide an additional prominent source by which wiring specificity emerges in cortical networks. This morphologically determined wiring specificity reflects similarities between the neurons’ axo-dendritic projections patterns, the packing density, and the cellular diversity of the neuropil. The higher these three factors are, the more recurrent is the topology of the network. Conversely, the lower these factors are, the more feedforward is the network’s topology. These principles predict the empirically observed occurrences of clusters of synapses, cell type-specific connectivity patterns, and nonrandom network motifs. Thus, we demonstrate that wiring specificity emerges in the cerebral cortex at subcellular, cellular, and network scales from the specific morphological properties of its neuronal constituents

Initial solidification dynamics of spreading droplets

When a droplet is brought in contact with an undercooled surface, it wets the substrate and solidifies at the same time. The interplay between the phase transition effects and the contact-line motion, leading to its arrest, remains poorly understood. Here we reveal the early solidification patterns and dynamics of spreading hexadecane droplets. Total internal reflection (TIR) imaging is employed to temporally and spatially resolve the early solidification behaviour. With this, we determine the conditions leading to the contact-line arrest. We quantify the overall nucleation behaviour, \textit{i.e.} the nucleation rate and the crystal growth speed, and show its sensitivity to the applied undercooling of the substrate. By combining the Johnson-Mehl-Avrami-Kolmogorov nucleation theory and scaling relations for the spreading, we can calculate the temporal evolution of the solid area fraction, which is in good agreement with our observations. We also show that for strong enough undercooling it is the rapid growth of the crystals which determines the eventual arrest of the spreading contact line.Comment: 5 pages, 5 figure