Resonant enhancement of second harmonic generation in the mid-infrared using localized surface phonon polaritons in sub-diffractional nanostructures

We report on strong enhancement of mid-infrared second harmonic generation (SHG) from SiC nanopillars due to the resonant excitation of localized surface phonon-polaritons within the Reststrahlen band. The magnitude of the SHG peak at the monopole mode experiences a strong dependence on the resonant frequency beyond that described by the field localization degree and the dispersion of linear and nonlinear-optical SiC properties. Comparing the results for the identical nanostructures made of 4H and 6H SiC polytypes, we demonstrate the interplay of localized surface phonon polaritons with zone-folded weak phonon modes of the anisotropic crystal. Tuning the monopole mode in and out of the region where the zone-folded phonon is excited in 6H-SiC, we observe a prominent increase of the already monopole-enhanced SHG output when the two modes are coupled. Envisioning this interplay as one of the showcase features of mid-infrared nonlinear nanophononics, we discuss its prospects for the effective engineering of nonlinear-optical materials with desired properties in the infrared spectral range.Comment: 16 pages, 3 figure

Genomic mapping of RNA polymerase II reveals sites of co-transcriptional regulation in human cells

BACKGROUND: Transcription by RNA polymerase II is regulated at many steps including initiation, promoter release, elongation and termination. Accumulation of RNA polymerase II at particular locations across genes can be indicative of sites of regulation. RNA polymerase II is thought to accumulate at the promoter and at sites of co-transcriptional alternative splicing where the rate of RNA synthesis slows. RESULTS: To further understand transcriptional regulation at a global level, we determined the distribution of RNA polymerase II within regions of the human genome designated by the ENCODE project. Hypophosphorylated RNA polymerase II localizes almost exclusively to 5' ends of genes. On the other hand, localization of total RNA polymerase II reveals a variety of distinct landscapes across many genes with 74% of the observed enriched locations at exons. RNA polymerase II accumulates at many annotated constitutively spliced exons, but is biased for alternatively spliced exons. Finally, RNA polymerase II is also observed at locations not in gene regions. CONCLUSION: Localizing RNA polymerase II across many millions of base pairs in the human genome identifies novel sites of transcription and provides insights into the regulation of transcription elongation. These data indicate that RNA polymerase II accumulates most often at exons during transcription. Thus, a major factor of transcription elongation control in mammalian cells is the coordination of transcription and pre-mRNA processing to define exons

Cloud optical depth retrievals from the Aerosol Robotic Network (AERONET) cloud mode observations

Cloud optical depth is one of the most poorly observed climate variables. The new “cloud mode” capability in the Aerosol Robotic Network (AERONET) will inexpensively yet dramatically increase cloud optical depth observations in both number and accuracy. Cloud mode optical depth retrievals from AERONET were evaluated at the Atmospheric Radiation Measurement program’s Oklahoma site in sky conditions ranging from broken clouds to overcast. For overcast cases, the 1.5 min average AERONET cloud mode optical depths agreed to within 15% of those from a standard ground‐based flux method. For broken cloud cases, AERONET retrievals also captured rapid variations detected by the microwave radiometer. For 3 year climatology derived from all nonprecipitating clouds, AERONET monthly mean cloud optical depths are generally larger than cloud radar retrievals because of the current cloud mode observation strategy that is biased toward measurements of optically thick clouds. This study has demonstrated a new way to enhance the existing AERONET infrastructure to observe cloud optical properties on a global scale

The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations

Clouds present many challenges to climate modelling. To develop and verify the parameterisations needed to allow climate models to represent cloud structure and processes, there is a need for high-quality observations of cloud optical depth from locations around the world. Retrievals of cloud optical depth are obtainable from radiances measured by Aerosol Robotic Network (AERONET) radiometers in “cloud mode” using a two-wavelength retrieval method. However, the method is unable to detect cloud phase, and hence assumes that all of the cloud in a profile is liquid. This assumption has the potential to introduce errors into long-term statistics of retrieved optical depth for clouds that also contain ice. Using a set of idealised cloud profiles we find that, for optical depths above 20, the fractional error in retrieved optical depth is a linear function of the fraction of the optical depth that is due to the presence of ice cloud (“ice fraction”). Clouds that are entirely ice have positive errors with magnitudes of the order of 55 % to 70 %. We derive a simple linear equation that can be used as a correction at AERONET sites where ice fraction can be independently estimated. Using this linear equation, we estimate the magnitude of the error for a set of cloud profiles from five sites of the Atmospheric Radiation Measurement programme. The dataset contains separate retrievals of ice and liquid retrievals; hence ice fraction can be estimated. The magnitude of the error at each location was related to the relative frequencies of occurrence in thick frontal cloud at the mid-latitude sites and of deep convection at the tropical sites – that is, of deep cloud containing both ice and liquid particles. The long-term mean optical depth error at the five locations spans the range 2–4, which we show to be small enough to allow calculation of top-of-atmosphere flux to within 10 % and surface flux to about 15 %

An Analysis of AERONET Aerosol Absorption Properties and Classifications Representative of Aerosol Source Regions

Partitioning of mineral dust, pollution, smoke, and mixtures using remote sensing techniques can help improve accuracy of satellite retrievals and assessments of the aerosol radiative impact on climate. Spectral aerosol optical depth (tau) and single scattering albedo (omega (sub 0) ) from Aerosol Robotic Network (AERONET) measurements are used to form absorption [i.e., omega (sub 0) and absorption Angstrom exponent (alpha(sub abs))] and size [i.e., extinction Angstrom exponent (alpha(sub ext)) and fine mode fraction of tau] relationships to infer dominant aerosol types. Using the long-term AERONET data set (1999-2010), 19 sites are grouped by aerosol type based on known source regions to: (1) determine the average omega (sub 0) and alpha(sub abs) at each site (expanding upon previous work); (2) perform a sensitivity study on alpha(sub abs) by varying the spectral omega (sub 0); and (3) test the ability of each absorption and size relationship to distinguish aerosol types. The spectral omega (sub 0) averages indicate slightly more aerosol absorption (i.e., a 0.0 < delta omega (sub 0) <= 0.02 decrease) than in previous work and optical mixtures of pollution and smoke with dust show stronger absorption than dust alone. Frequency distributions of alpha(sub abs) show significant overlap among aerosol type categories and at least 10% of the alpha(sub abs) retrievals in each category are below 1.0. Perturbing the spectral omega (sub 0) by +/- 0.03 induces significant alpha(sub abs) changes from the unperturbed value by at least approx. +/- 0.6 for Dust, approx. +/-0.2 for Mixed, and approx. +/-0.1 for Urban/Industrial and Biomass Burning. The omega (sub 0)440nm and alpha(sub ext) 440-870nm relationship shows the best separation among aerosol type clusters, providing a simple technique for determining aerosol type from surface- and future space-based instrumentation

Connectivity of Soft Random Geometric Graphs Over Annuli

Nodes are randomly distributed within an annulus (and then a shell) to form a point pattern of communication terminals which are linked stochastically according to the Rayleigh fading of radio-frequency data signals. We then present analytic formulas for the connection probability of these spatially embedded graphs, describing the connectivity behaviour as a dense-network limit is approached. This extends recent work modelling ad hoc networks in non-convex domains.Comment: 12 pages, 6 figure