Search results for "Radiative Transfer"
showing 10 items of 551 documents
Tuning the collective decay of two entangled emitters by means of a nearby surface
2017
We consider the radiative properties of a system of two identical correlated atoms interacting with the electromagnetic field in its vacuum state in the presence of a generic dielectric environment. We suppose that the two emitters are prepared in a symmetric or antisymmetric superposition of one ground state and one excited state and we evaluate the transition rate to the collective ground state, showing distinctive cooperative radiative features. Using a macroscopic quantum electrodynamics approach to describe the electromagnetic field, we first obtain an analytical expression for the decay rate of the two entangled two-level atoms in terms of the Green's tensor of the generic external en…
Suppression of radiative losses of surface polaritons on nanostructured thin metal films
2005
The strong electromagnetic coupling between surface plasmon polariton modes on opposite interfaces of a finite thickness periodically nanostructured metal film has been studied. Surface polariton dispersion and associated electromagnetic field distributions have been analyzed. It was shown that at a frequency that corresponds to the crossing of film Bloch modes of different symmetries, the radiative losses of surface polaritons that are related to the polaritons' coupling to light during propagation on the structured surface are suppressed.
Optical properties and quantum yield determination in photocatalytic suspensions
2006
Knowledge of the optical properties of photocatalytic suspensions is vital for a correct comparison of their energetic efficiency. In this work, the determination of both absorption and scattering coefficients of aqueous suspensions of commercial TiO2 powders irradiated by monochromatic light was carried out by measuring only one quantity—the transmitted photon flow—as a function of the catalyst mass and by applying an asymptotic form of the Kubelka–Munk solution of the radiative transfer equation. Applying a nonlinear fitting procedure the evaluation of the actual values of absorption and scattering coefficients was carried out. The limit for optically thick media of the Kubelka–Munk equat…
Retrieval of Case 2 Water Quality Parameters with Machine Learning
2018
Water quality parameters are derived applying several machine learning regression methods on the Case2eXtreme dataset (C2X). The used data are based on Hydrolight in-water radiative transfer simulations at Sentinel-3 OLCI wavebands, and the application is done exclusively for absorbing waters with high concentrations of coloured dissolved organic matter (CDOM). The regression approaches are: regularized linear, random forest, Kernel ridge, Gaussian process and support vector regressors. The validation is made with and an independent simulation dataset. A comparison with the OLCI Neural Network Swarm (ONSS) is made as well. The best approached is applied to a sample scene and compared with t…
Active emulation of computer codes with Gaussian processes – Application to remote sensing
2020
Many fields of science and engineering rely on running simulations with complex and computationally expensive models to understand the involved processes in the system of interest. Nevertheless, the high cost involved hamper reliable and exhaustive simulations. Very often such codes incorporate heuristics that ironically make them less tractable and transparent. This paper introduces an active learning methodology for adaptively constructing surrogate models, i.e. emulators, of such costly computer codes in a multi-output setting. The proposed technique is sequential and adaptive, and is based on the optimization of a suitable acquisition function. It aims to achieve accurate approximations…
Retrieval of aboveground crop nitrogen content with a hybrid machine learning method
2020
Abstract Hyperspectral acquisitions have proven to be the most informative Earth observation data source for the estimation of nitrogen (N) content, which is the main limiting nutrient for plant growth and thus agricultural production. In the past, empirical algorithms have been widely employed to retrieve information on this biochemical plant component from canopy reflectance. However, these approaches do not seek for a cause-effect relationship based on physical laws. Moreover, most studies solely relied on the correlation of chlorophyll content with nitrogen, and thus neglected the fact that most N is bound in proteins. Our study presents a hybrid retrieval method using a physically-base…
Joint Gaussian Processes for Biophysical Parameter Retrieval
2017
Solving inverse problems is central to geosciences and remote sensing. Radiative transfer models (RTMs) represent mathematically the physical laws which govern the phenomena in remote sensing applications (forward models). The numerical inversion of the RTM equations is a challenging and computationally demanding problem, and for this reason, often the application of a nonlinear statistical regression is preferred. In general, regression models predict the biophysical parameter of interest from the corresponding received radiance. However, this approach does not employ the physical information encoded in the RTMs. An alternative strategy, which attempts to include the physical knowledge, co…
Estimating crop primary productivity with Sentinel-2 and Landsat 8 using machine learning methods trained with radiative transfer simulations
2019
Abstract Satellite remote sensing has been widely used in the last decades for agricultural applications, both for assessing vegetation condition and for subsequent yield prediction. Existing remote sensing-based methods to estimate gross primary productivity (GPP), which is an important variable to indicate crop photosynthetic function and stress, typically rely on empirical or semi-empirical approaches, which tend to over-simplify photosynthetic mechanisms. In this work, we take advantage of all parallel developments in mechanistic photosynthesis modeling and satellite data availability for an advanced monitoring of crop productivity. In particular, we combine process-based modeling with …
Observation of Photon Polarization in theb→sγTransition
2014
This Letter presents a study of the flavor-changing neutral current radiative $B^{\pm} \to K^{\pm}\pi^{\mp}\pi^{\pm}\gamma$ decays performed using data collected in proton-proton collisions with the LHCb detector at $7$ and $8\,$TeV center-of-mass energies. In this sample, corresponding to an integrated luminosity of $3\,\text{fb}^{-1}$, nearly $14\,000$ signal events are reconstructed and selected, containing all possible intermediate resonances with a $K^{\pm}\pi^{\mp}\pi^{\pm}$ final state in the $[1.1, 1.9]\,$GeV/$c^{2}$ mass range. The distribution of the angle of the photon direction with respect to the plane defined by the final-state hadrons in their rest frame is studied in interva…
Replacing radiative transfer models by surrogate approximations through machine learning
2015
Physically-based radiative transfer models (RTMs) help in understanding the processes occurring on the Earth's surface and their interactions with vegetation and atmosphere. However, advanced RTMs can take a long computational time, which makes them unfeasible in many real applications. To overcome this problem, it has been proposed to substitute RTMs through so-called emulators. Emulators are statistical models that approximate the functioning of RTMs. They are advantageous in real practice because of the computational efficiency and excellent accuracy and flexibility for extrapolation. We here present an ‘Emulator toolbox’ that enables analyzing three multi-output machine learning regress…