Search results for "linear"
showing 10 items of 7165 documents
Germanium Dicarbide: Evidence for a T-Shaped Ground State Structure
2017
The equilibrium structure of germanium dicarbide GeC2 has been an open question since the late 1950s. Although most high-level quantum calculations predict an L-shaped geometry, a T-shaped or even a linear geometry cannot be ruled out because of the very flat potential energy surface. By recording the rotational spectrum of this dicarbide using sensitive microwave and millimeter techniques, we unambiguously establish that GeC2 adopts a vibrationally averaged T-shaped structure in its ground state. From analysis of 14 isotopologues, a precise r0 structure has been derived, yielding a Ge–C bond length of 1.952(1) A and an apex angle of 38.7(2)°.
Nonlinear response theory for Markov processes II: Fifth-order response functions
2017
The nonlinear response of stochastic models obeying a master equation is calculated up to fifth-order in the external field thus extending the third-order results obtained earlier (G. Diezemann, Phys. Rev. E{\bf 85}, 051502 (2012)). For sinusoidal fields the $5\om$-component of the susceptibility is computed for the model of dipole reorientations in an asymmetric double well potential and for a trap model with a Gaussian density of states. For most realizations of the models a hump is found in the higher-order susceptibilities. In particular, for the asymmetric double well potential model there are two characteristic temperature regimes showing the occurence of such a hump as compared to a …
Harmonic morphisms in nonlinear potential theory
1992
This article concerns the following problem: given a family of partial differential operators with similar structure and given a continuous mapping f from an open set Ω in Rn into Rn, then when does f pull back the solutions of one equation in the family to solutions of another equation in that family? This problem is typical in the theory of differential equations when one wants to use a coordinate change to study solutions in a different environment.
Effective characterization of the phase and intensity profiles of asymmetrically distorted light pulses in optical fiber systems
2009
International audience; We address the problem of characterization of light pulses that propagate in long-haul high-bit-rate optical communication systems under strongly perturbed conditions. We show that the conventional technique for characterization of the phase and intensity profile of such pulses becomes qualitatively inconsistent when the pulse's profile is asymmetrically distorted with respect to its center of mass. We resolve these inconsistencies by partially reformulating the conventional technique by means of appropriate pulse parameters, which we call upgraded parameters, that allow a fair characterization of the intensity and phase of all types of light pulses, including those …
A spin-crossover complex based on a 2,6-bis(pyrazol-1-yl)pyridine (1-bpp) ligand functionalized with a carboxylate group
2014
Combining Fe(ii) with the carboxylate-functionalized 2,6-bis(pyrazol-1-yl)pyridine (bppCOOH) ligand results in the spin-crossover compound [Fe(bppCOOH)2](ClO4)2 which shows an abrupt spin transition with a T1/2 of ca. 380 K and a TLIESST of 60 K due to the presence of a hydrogen-bonded linear network of complexes.
Dimensionless Stage-Discharge Relationship for a Non-Linear Water Reservoir: Theory and Experiments
2020
In the field of hydrology, stage&ndash
Estimating the macroscopic capillary length from Beerkan infiltration experiments and its impact on saturated soil hydraulic conductivity predictions
2020
International audience; The macroscopic capillary length, λc, is a fundamental soil parameter expressing the relative importance of the capillary over gravity forces during water movement in unsaturated soil. In this investigation, we propose a simple field method for estimating λc using only a single-ring infiltration experiment of the Beerkan type and measurements of initial and saturated soil water contents. We assumed that the intercept of the linear regression fitted to the steady-state portion of the experimental infiltration curve could be used as a reliable predictor of λc. This hypothesis was validated by assessing the proposed calculation approach using both analytical and field d…
Exposure to mercury among 9-year-old Spanish children: Associated factors and trend throughout childhood
2019
Mercury is considered a neurotoxicant and human exposure occurs mainly from the consumption of marine species. We aimed to describe total mercury concentrations (THg) and associated factors in 9-year old children, as well as to explore the trend in THg from 4 to 9 years of age. The study population consisted of 9-year-old children participating in the INMA (Environment and Childhood) birth cohort study in Valencia, Spain (n = 405, 2013–2014). THg in hair samples was measured by atomic absorption spectrometry at the age of 4 and 9 years. Sociodemographic and dietary data was obtained through questionnaires. Multiple linear regression was used to explore the association between THg and covari…
Joint Gaussian processes for inverse modeling
2017
Solving inverse problems is central in geosciences and remote sensing. Very often a mechanistic physical model of the system exists that solves the forward problem. Inverting the implied radiative transfer model (RTM) equations numerically implies, however, challenging and computationally demanding problems. Statistical models tackle the inverse problem and predict the biophysical parameter of interest from radiance data, exploiting either in situ data or simulated data from an RTM. We introduce a novel nonlinear and nonparametric statistical inversion model which incorporates both real observations and RTM-simulated data. The proposed Joint Gaussian Process (JGP) provides a solid framework…
Statistical retrieval of atmospheric profiles with deep convolutional neural networks
2019
Abstract Infrared atmospheric sounders, such as IASI, provide an unprecedented source of information for atmosphere monitoring and weather forecasting. Sensors provide rich spectral information that allows retrieval of temperature and moisture profiles. From a statistical point of view, the challenge is immense: on the one hand, “underdetermination” is common place as regression needs to work on high dimensional input and output spaces; on the other hand, redundancy is present in all dimensions (spatial, spectral and temporal). On top of this, several noise sources are encountered in the data. In this paper, we present for the first time the use of convolutional neural networks for the retr…