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R M Thorne - One of the best experts on this subject based on the ideXlab platform.
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a kalman filter technique to estimate relativistic electron Lifetimes in the outer radiation belt
Journal of Geophysical Research, 2007Co-Authors: Dmitri Kondrashov, Yuri Shprits, Michael Ghil, R M ThorneAbstract:[1] Data assimilation aims to smoothly blend incomplete and inaccurate observational data with dynamical information from a physical model, and has become an increasingly important tool in understanding and predicting meteorological, oceanographic and climate processes. As space-borne observations become more plentiful and space-physics models more sophisticated, dynamical processes in the radiation belts can be analyzed using advanced data assimilation methods. We use the Extended Kalman filter and observations from the Combined Release and Radiation Effects Satellite (CRRES) to estimate the Lifetime of relativistic electrons during magnetic storms in the Earth's outer radiation belt. The model is a linear parabolic partial differential equation governing the phase-space density. This equation contains empirical coefficients that are not well-known and that we wish to estimate, along with the phase-space density itself. The assimilation method is first verified on model-simulated data, which allows us to reliably estimate the Characteristic Lifetime of the electrons. We then apply the methodology to CRRES measurements and show it to be useful in highlighting systematic differences between the parameter estimates for storms driven by coronal mass ejections (CMEs) and by corotating interaction regions (CIRs), respectively. These differences are attributed to the complex, competing effects of acceleration and loss processes during distinct physical regimes. The technique described herein may be applied next to constrain more sophisticated radiation belt and ring current models, as well as in other areas of magnetospheric physics.
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a kalman filter technique to estimate relativistic electron Lifetimes in the outer radiation belt
Journal of Geophysical Research, 2007Co-Authors: Dmitri Kondrashov, Yuri Shprits, Michael Ghil, R M ThorneAbstract:[1] Data assimilation aims to smoothly blend incomplete and inaccurate observational data with dynamical information from a physical model, and has become an increasingly important tool in understanding and predicting meteorological, oceanographic and climate processes. As space-borne observations become more plentiful and space-physics models more sophisticated, dynamical processes in the radiation belts can be analyzed using advanced data assimilation methods. We use the Extended Kalman filter and observations from the Combined Release and Radiation Effects Satellite (CRRES) to estimate the Lifetime of relativistic electrons during magnetic storms in the Earth's outer radiation belt. The model is a linear parabolic partial differential equation governing the phase-space density. This equation contains empirical coefficients that are not well-known and that we wish to estimate, along with the phase-space density itself. The assimilation method is first verified on model-simulated data, which allows us to reliably estimate the Characteristic Lifetime of the electrons. We then apply the methodology to CRRES measurements and show it to be useful in highlighting systematic differences between the parameter estimates for storms driven by coronal mass ejections (CMEs) and by corotating interaction regions (CIRs), respectively. These differences are attributed to the complex, competing effects of acceleration and loss processes during distinct physical regimes. The technique described herein may be applied next to constrain more sophisticated radiation belt and ring current models, as well as in other areas of magnetospheric physics.
Michael Ghil - One of the best experts on this subject based on the ideXlab platform.
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a kalman filter technique to estimate relativistic electron Lifetimes in the outer radiation belt
Journal of Geophysical Research, 2007Co-Authors: Dmitri Kondrashov, Yuri Shprits, Michael Ghil, R M ThorneAbstract:[1] Data assimilation aims to smoothly blend incomplete and inaccurate observational data with dynamical information from a physical model, and has become an increasingly important tool in understanding and predicting meteorological, oceanographic and climate processes. As space-borne observations become more plentiful and space-physics models more sophisticated, dynamical processes in the radiation belts can be analyzed using advanced data assimilation methods. We use the Extended Kalman filter and observations from the Combined Release and Radiation Effects Satellite (CRRES) to estimate the Lifetime of relativistic electrons during magnetic storms in the Earth's outer radiation belt. The model is a linear parabolic partial differential equation governing the phase-space density. This equation contains empirical coefficients that are not well-known and that we wish to estimate, along with the phase-space density itself. The assimilation method is first verified on model-simulated data, which allows us to reliably estimate the Characteristic Lifetime of the electrons. We then apply the methodology to CRRES measurements and show it to be useful in highlighting systematic differences between the parameter estimates for storms driven by coronal mass ejections (CMEs) and by corotating interaction regions (CIRs), respectively. These differences are attributed to the complex, competing effects of acceleration and loss processes during distinct physical regimes. The technique described herein may be applied next to constrain more sophisticated radiation belt and ring current models, as well as in other areas of magnetospheric physics.
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a kalman filter technique to estimate relativistic electron Lifetimes in the outer radiation belt
Journal of Geophysical Research, 2007Co-Authors: Dmitri Kondrashov, Yuri Shprits, Michael Ghil, R M ThorneAbstract:[1] Data assimilation aims to smoothly blend incomplete and inaccurate observational data with dynamical information from a physical model, and has become an increasingly important tool in understanding and predicting meteorological, oceanographic and climate processes. As space-borne observations become more plentiful and space-physics models more sophisticated, dynamical processes in the radiation belts can be analyzed using advanced data assimilation methods. We use the Extended Kalman filter and observations from the Combined Release and Radiation Effects Satellite (CRRES) to estimate the Lifetime of relativistic electrons during magnetic storms in the Earth's outer radiation belt. The model is a linear parabolic partial differential equation governing the phase-space density. This equation contains empirical coefficients that are not well-known and that we wish to estimate, along with the phase-space density itself. The assimilation method is first verified on model-simulated data, which allows us to reliably estimate the Characteristic Lifetime of the electrons. We then apply the methodology to CRRES measurements and show it to be useful in highlighting systematic differences between the parameter estimates for storms driven by coronal mass ejections (CMEs) and by corotating interaction regions (CIRs), respectively. These differences are attributed to the complex, competing effects of acceleration and loss processes during distinct physical regimes. The technique described herein may be applied next to constrain more sophisticated radiation belt and ring current models, as well as in other areas of magnetospheric physics.
Dmitri Kondrashov - One of the best experts on this subject based on the ideXlab platform.
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a kalman filter technique to estimate relativistic electron Lifetimes in the outer radiation belt
Journal of Geophysical Research, 2007Co-Authors: Dmitri Kondrashov, Yuri Shprits, Michael Ghil, R M ThorneAbstract:[1] Data assimilation aims to smoothly blend incomplete and inaccurate observational data with dynamical information from a physical model, and has become an increasingly important tool in understanding and predicting meteorological, oceanographic and climate processes. As space-borne observations become more plentiful and space-physics models more sophisticated, dynamical processes in the radiation belts can be analyzed using advanced data assimilation methods. We use the Extended Kalman filter and observations from the Combined Release and Radiation Effects Satellite (CRRES) to estimate the Lifetime of relativistic electrons during magnetic storms in the Earth's outer radiation belt. The model is a linear parabolic partial differential equation governing the phase-space density. This equation contains empirical coefficients that are not well-known and that we wish to estimate, along with the phase-space density itself. The assimilation method is first verified on model-simulated data, which allows us to reliably estimate the Characteristic Lifetime of the electrons. We then apply the methodology to CRRES measurements and show it to be useful in highlighting systematic differences between the parameter estimates for storms driven by coronal mass ejections (CMEs) and by corotating interaction regions (CIRs), respectively. These differences are attributed to the complex, competing effects of acceleration and loss processes during distinct physical regimes. The technique described herein may be applied next to constrain more sophisticated radiation belt and ring current models, as well as in other areas of magnetospheric physics.
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a kalman filter technique to estimate relativistic electron Lifetimes in the outer radiation belt
Journal of Geophysical Research, 2007Co-Authors: Dmitri Kondrashov, Yuri Shprits, Michael Ghil, R M ThorneAbstract:[1] Data assimilation aims to smoothly blend incomplete and inaccurate observational data with dynamical information from a physical model, and has become an increasingly important tool in understanding and predicting meteorological, oceanographic and climate processes. As space-borne observations become more plentiful and space-physics models more sophisticated, dynamical processes in the radiation belts can be analyzed using advanced data assimilation methods. We use the Extended Kalman filter and observations from the Combined Release and Radiation Effects Satellite (CRRES) to estimate the Lifetime of relativistic electrons during magnetic storms in the Earth's outer radiation belt. The model is a linear parabolic partial differential equation governing the phase-space density. This equation contains empirical coefficients that are not well-known and that we wish to estimate, along with the phase-space density itself. The assimilation method is first verified on model-simulated data, which allows us to reliably estimate the Characteristic Lifetime of the electrons. We then apply the methodology to CRRES measurements and show it to be useful in highlighting systematic differences between the parameter estimates for storms driven by coronal mass ejections (CMEs) and by corotating interaction regions (CIRs), respectively. These differences are attributed to the complex, competing effects of acceleration and loss processes during distinct physical regimes. The technique described herein may be applied next to constrain more sophisticated radiation belt and ring current models, as well as in other areas of magnetospheric physics.
Vuk Milisic - One of the best experts on this subject based on the ideXlab platform.
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from delayed and constrained minimizing movements to the harmonic map heat equation
Journal of Functional Analysis, 2020Co-Authors: Vuk MilisicAbstract:Abstract In the context of cell motility modelling and more particularly related to the Filament Based Lamelipodium Model [18] , [9] , [10] , this work deals with a rigorous mathematical proof of convergence between solutions of two problems: we start from a microscopic description of adhesions using a delayed and constrained vector valued equation with spacial diffusion and show the convergence towards the corresponding friction limit. The convergence is performed with respect to the bond Characteristic Lifetime e whose inverse is also proportional to the stiffness of the bonds. The originality of this work is the extension of gradient flow techniques to our setting. Namely, the discrete finite difference term in the gradient flow energy is here replaced by a delay term which complicates greatly the mathematical analysis. Contrarily to the standard approach [2] , [16] , compactness in time is not provided by the energy minimization process : a series of past times are taken into account in our discrete energy. A supplementary equation on the time derivative is obtained requiring uniform estimate with respect to e of the Lagrange multiplier and provides compactness. Due to the non-linearity induced by the constraint, a specific stability estimate useful in our previous works, is not at hand here. Numerical simulations even showed that this estimate does not hold. Nevertheless, transposing our delay operator, we succeed in proving convergence under slightly weaker hypotheses. The result relies on a careful initial layer analysis, extending [11] to the space dependent setting.
Nilgun Gedik - One of the best experts on this subject based on the ideXlab platform.
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Fluctuating charge-density waves in a cuprate superconductor
Nature Materials, 2013Co-Authors: D. H. Torchinsky, A. T. Bollinger, Ivan Bozovic, Fahad Mahmood, Nilgun GedikAbstract:Cuprate materials hosting high-temperature superconductivity (HTS) also exhibit various forms of charge and spin ordering whose significance is not fully understood. So far, static charge-density waves (CDWs) have been detected by diffraction probes only at particular doping levels or in an applied external field . However, dynamic CDWs may also be present more broadly and their detection, characterization and relationship with HTS remain open problems. Here we present a method based on ultrafast spectroscopy to detect the presence and measure the Lifetimes of CDW fluctuations in cuprates. In an underdoped La(1.9)Sr(0.1)CuO4 film (T(c) = 26 K), we observe collective excitations of CDW that persist up to 100 K. This dynamic CDW fluctuates with a Characteristic Lifetime of 2 ps at T = 5 K that decreases to 0.5 ps at T = 100 K. In contrast, in an optimally doped La(1.84)Sr(0.16)CuO4 film (T(c) = 38.5 K), we detect no signatures of fluctuating CDWs at any temperature, favouring the competition scenario. This work forges a path for studying fluctuating order parameters in various superconductors and other materials.