The Experts below are selected from a list of 19551 Experts worldwide ranked by ideXlab platform
Emily A. Carter - One of the best experts on this subject based on the ideXlab platform.
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Kohn-Sham potentials from electron densities using a matrix representation within finite atomic orbital basis sets.
The Journal of chemical physics, 2018Co-Authors: Xing Zhang, Emily A. CarterAbstract:We revisit the static response function-based Kohn-Sham (KS) Inversion Procedure for determining the KS effective potential that corresponds to a given target electron density within finite atomic orbital basis sets. Instead of expanding the potential in an auxiliary basis set, we directly update the potential in its matrix representation. Through numerical examples, we show that the reconstructed density rapidly converges to the target density. Preliminary results are presented to illustrate the possibility of obtaining a local potential in real space from the optimized potential in its matrix representation. We have further applied this matrix-based KS Inversion approach to density functional embedding theory. A proof-of-concept study of a solvated proton transfer reaction demonstrates the method’s promise.
Siebesma A.p. - One of the best experts on this subject based on the ideXlab platform.
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Depolarization Lidar Determination of Cloud-Base Microphysical Properties
EDP Sciences, 2016Co-Authors: Donovan D.p., Klein Baltink H., Henzing J.s., S. De ,roode, Siebesma A.p.Abstract:The links between multiple-scattering induced depolarization and cloud microphysical properties (e.g. cloud particle number density, effective radius, water content) have long been recognised. Previous efforts to use depolarization information in a quantitative manner to retrieve cloud microphysical cloud properties have also been undertaken but with limited scope and, arguably, success. In this work we present a retrieval Procedure applicable to liquid stratus clouds with (quasi-)linear LWC profiles and (quasi-)constant number density profiles in the cloud-base region. This set of assumptions allows us to employ a fast and robust Inversion Procedure based on a lookup-table approach applied to extensive lidar Monte-Carlo multiple-scattering calculations. An example validation case is presented where the results of the Inversion Procedure are compared with simultaneous cloud radar observations. In non-drizzling conditions it was found, in general, that the lidar-only Inversion results can be used to predict the radar reflectivity within the radar calibration uncertainty (2-3 dBZ). Results of a comparison between ground-based aerosol number concentration and lidar-derived cloud base number considerations are also presented. The observed relationship between the two quantities is seen to be consistent with the results of previous studies based on aircraft-based in situ measurements. © 2016 Owned by the authors, published by EDP Sciences
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Depolarization Lidar Determination Of Cloud-Base Microphysical Properties
EDP Sciences, 2016Co-Authors: Donovan D.p., Klein Baltink H., Henzing J.s., De Roode S., Siebesma A.p.Abstract:The links between multiple-scattering induced depolarization and cloud microphysical properties (e.g. cloud particle number density, effective radius, water content) have long been recognised. Previous efforts to use depolarization information in a quantitative manner to retrieve cloud microphysical cloud properties have also been undertaken but with limited scope and, arguably, success. In this work we present a retrieval Procedure applicable to liquid stratus clouds with (quasi-)linear LWC profiles and (quasi-)constant number density profiles in the cloud-base region. This set of assumptions allows us to employ a fast and robust Inversion Procedure based on a lookup-table approach applied to extensive lidar Monte-Carlo multiple-scattering calculations. An example validation case is presented where the results of the Inversion Procedure are compared with simultaneous cloud radar observations. In non-drizzling conditions it was found, in general, that the lidar- only Inversion results can be used to predict the radar reflectivity within the radar calibration uncertainty (2-3 dBZ). Results of a comparison between ground-based aerosol number concentration and lidar-derived cloud base number considerations are also presented. The observed relationship between the two quantities is seen to be consistent with the results of previous studies based on aircraft-based in situ measurements
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Depolarization Lidar Determination of Cloud-Base Microphysical Properties
'EDP Sciences', 2016Co-Authors: Donovan D.p., Klein Baltink H., Henzing J. S., De Roode, Siebesma A.p.Abstract:The links between multiple-scattering induced depolarization and cloud microphysical properties (e.g. cloud particle number density, effective radius, water content) have long been recognised. Previous efforts to use depolarization information in a quantitative manner to retrieve cloud microphysical cloud properties have also been undertaken but with limited scope and, arguably, success. In this work we present a retrieval Procedure applicable to liquid stratus clouds with (quasi-)linear LWC profiles and (quasi-)constant number density profiles in the cloud-base region. This set of assumptions allows us to employ a fast and robust Inversion Procedure based on a lookup-table approach applied to extensive lidar Monte-Carlo multiple-scattering calculations. An example validation case is presented where the results of the Inversion Procedure are compared with simultaneous cloud radar observations. In non-drizzling conditions it was found, in general, that the lidar-only Inversion results can be used to predict the radar reflectivity within the radar calibration uncertainty (2-3 dBZ). Results of a comparison between ground-based aerosol number concentration and lidar-derived cloud base number considerations are also presented. The observed relationship between the two quantities is seen to be consistent with the results of previous studies based on aircraft-based in situ measurements.Atmospheric Remote SensingAtmospheric Physic
Sandra M Richwalski - One of the best experts on this subject based on the ideXlab platform.
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joint Inversion of h v ratios and dispersion curves from seismic noise estimating the s wave velocity of bedrock
Geophysical Research Letters, 2005Co-Authors: Matteo Picozzi, Stefano Parolai, Sandra M RichwalskiAbstract:[1] A joint Inversion of phase velocity and H/V ratio curves, both obtained from seismic-noise recordings, permits the retrieval of the shear-wave velocity structure of local sedimentary cover. Our Inversion scheme uses a genetic algorithm and considers the influence of higher modes on the data sets. Encouraged by the results published previously on joint Inversion (Parolai et al., 2005) we went one step further. We found, using a synthetic data set, that the impedance contrast at the sediment-bedrock interface has a strong influence on the shape of the H/V ratio curve, which therefore allows the bedrock S-wave velocity to be well constrained in the joint-Inversion Procedure. Our observations were further confirmed using a real data set.
Xing Zhang - One of the best experts on this subject based on the ideXlab platform.
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Kohn-Sham potentials from electron densities using a matrix representation within finite atomic orbital basis sets.
The Journal of chemical physics, 2018Co-Authors: Xing Zhang, Emily A. CarterAbstract:We revisit the static response function-based Kohn-Sham (KS) Inversion Procedure for determining the KS effective potential that corresponds to a given target electron density within finite atomic orbital basis sets. Instead of expanding the potential in an auxiliary basis set, we directly update the potential in its matrix representation. Through numerical examples, we show that the reconstructed density rapidly converges to the target density. Preliminary results are presented to illustrate the possibility of obtaining a local potential in real space from the optimized potential in its matrix representation. We have further applied this matrix-based KS Inversion approach to density functional embedding theory. A proof-of-concept study of a solvated proton transfer reaction demonstrates the method’s promise.
Jan Thoen - One of the best experts on this subject based on the ideXlab platform.
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photoacoustic investigation of the thermal properties of layered materials calculation of the forward signal and numerical Inversion Procedure
Journal of Applied Physics, 1993Co-Authors: Christ Glorieux, Jan Fivez, Jan ThoenAbstract:The structure of layered materials or substances with depth‐dependent properties is often difficult to investigate with conventional optical or acoustical methods. Since the photoacoustic technique is based on thermal waves, which have other transmission and reflection properties than optical or acoustical waves, it can provide information on samples for which other methods fail. In this work, a straightforward numerical calculation of the photoacoustical signal for samples with a one‐dimensional layered optical and thermal structure is described. An Inversion Procedure, based on the nonlinear least‐squares fit routine minuit is shown to be very effective for obtaining depth information from the frequency dependence of the photoacoustic signal.
