scholarly journals Mean-field approaches for Ξ− hypernuclei and current experimental data

2016 ◽  
Vol 94 (6) ◽  
Author(s):  
T. T. Sun ◽  
E. Hiyama ◽  
H. Sagawa ◽  
H.-J. Schulze ◽  
J. Meng
Keyword(s):  
Experimental Data ◽  
Mean Field ◽  
Current Experimental Data ◽  
Field Approaches

Potentiality of Mean-Field Approaches for Recrystallisation: Characterization of the Deformed State of Polycrystals

2004 ◽  
Vol 467-470 ◽  
pp. 33-38 ◽  
Author(s):  
Rénald Brenner ◽  
O. Castelnau ◽  
Brigitte Bacroix
Keyword(s):  
Mean Field ◽  
Mechanical State ◽  
Microstructural Parameters ◽  
Deformed State ◽  
The Mean ◽  
Field Approaches

The description of the mechanical state of a polycrystal is presented in the framework of the mean-field approaches and attention is paid to the fields heterogeneity. For nonlinear behaviours, the importance of the chosen model is emphasized with respect to relevant microstructural parameters for recrystallisation.

scholarly journals Point-coupling Models from Mesonic Hypermassive Limit and Mean-field Approaches

2012 ◽  
Vol 42 (3-4) ◽  
pp. 227-236 ◽  
Author(s):  
O. Lourenço ◽  
M. Dutra ◽  
R. L. P. G. Amaral ◽  
Antonio Delfino
Keyword(s):  
Mean Field ◽  
Field Approaches

scholarly journals On the inclusion of dissipation on top of mean-field approaches

2018 ◽  
Vol 91 (10) ◽  
Author(s):  
Phuong Mai Dinh ◽  
Lionel Lacombe ◽  
Paul-Gerhard Reinhard ◽  
Éric Suraud ◽  
Marc Vincendon
Keyword(s):  
Mean Field ◽  
Field Approaches

scholarly journals Charge radii of potassium isotopes in the RMF(BCS)* approach

2022 ◽  
Author(s):  
Rong An ◽  
Shisheng Zhang ◽  
Li-Sheng Geng ◽  
Feng-Shou 张丰收 Zhang
Keyword(s):  
Experimental Data ◽  
Density Functional Theory ◽  
Density Functional ◽  
Mean Field ◽  
Field Studies ◽  
Nuclear Density ◽  
Isotopic Chain ◽  
Functional Theory ◽  
Charge Radii ◽  
Nuclear Density Functional Theory

Abstract We apply the recently proposed RMF(BCS)* ansatz to study the charge radii of the potassium isotopic chain up to $^{52}$K. It is shown that the experimental data can be reproduced rather well, qualitatively similar to the Fayans nuclear density functional theory, but with a slightly better description of the odd-even staggerings (OES). Nonetheless, both methods fail for $^{50}$K and to a lesser extent for $^{48,52}$K. It is shown that if these nuclei are deformed with a $\beta_{20}\approx-0.2$, then one can obtain results consistent with experiments for both charge radii and spin-parities. We argue that beyond mean field studies are needed to properly describe the charge radii of these three nuclei, particularly for $^{50}$K.

scholarly journals Estimating the distribution of time to extinction of infectious diseases in mean-field approaches

2020 ◽  
Author(s):  
Maryam Aliee ◽  
Kat S. Rock ◽  
Matt J. Keeling
Keyword(s):  
Infectious Diseases ◽  
Stochastic Models ◽  
Mean Field ◽  
Practical Method ◽  
Deterministic Models ◽  
Recovery Processes ◽  
Time To Extinction ◽  
And Control ◽  
Field Approaches ◽  
Birth Death

AbstractA key challenge for many infectious diseases is to predict the time to extinction under specific interventions. In general this question requires the use of stochastic models which recognise the inherent individual-based, chance-driven nature of the dynamics; yet stochastic models are inherently computationally expensive, especially when parameter uncertainty also needs to be incorporated. Deterministic models are often used for prediction as they are more tractable, however their inability to precisely reach zero infections makes forecasting extinction times problematic. Here, we study the extinction problem in deterministic models with the help of an effective “birth-death” description of infection and recovery processes. We present a practical method to estimate the distribution, and therefore robust means and prediction intervals, of extinction times by calculating their different moments within the birth-death framework. We show these predictions agree very well with the results of stochastic models by analysing the simplified SIS dynamics as well as studying an example of more complex and realistic dynamics accounting for the infection and control of African sleeping sickness (Trypanosoma brucei gambiense).

Magnetism at Finite Temperatures

2021 ◽  
pp. 384-480
Author(s):  
Jürgen Kübler
Keyword(s):  
Experimental Data ◽  
Mean Field Theory ◽  
Mean Field ◽  
Spin Fluctuations ◽  
Alternative Theory ◽  
Dynamic Susceptibility ◽  
Technology Applications ◽  
Exchange Constants ◽  
Structure Problem ◽  
Magnetic Skyrmions

Thermal properties of magnets are dominated by low-lying excitations, perused systematically. Magnon spectra of elementary metals and compounds are obtained theoretically and compared with experimental data. Spin fluctuations are discussed in mean-field theory to obtain ab initio estimates of ordering temperatures for a multitude of magnetic systems. The free energy is connected with dynamic susceptibility which supplies a solid basis for the magnetic phase of ferromagnetic compounds. Methods derived to obtain Heisenberg exchange constants from first-principle calculations are compared with experimental data. Magnetic skyrmions enrich the field of magnetism and are of possible use for data technology applications. Several cases are discussed and classified showing theoretical and experimental data. For high temperatures the disordered local moment picture supplies an alternative theory for magnetism where the coherent-potential approximation is used to solve the electronic-structure problem in an alloy analogy. The basic theory is presented and discussed together with experimental data.

scholarly journals Evaluating Magnetocaloric Effect in Magnetocaloric Materials: A Novel Approach Based on Indirect Measurements Using Artificial Neural Networks

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1871 ◽  
Author(s):  
Angelo Maiorino ◽  
Manuel Gesù Del Duca ◽  
Jaka Tušek ◽  
Urban Tomc ◽  
Andrej Kitanovski ◽  
...  
Keyword(s):  
Experimental Data ◽  
Thermodynamic Properties ◽  
Magnetocaloric Effect ◽  
Mean Field Theory ◽  
Mean Field ◽  
Experimental Methods ◽  
Novel Approach ◽  
Magnetocaloric Materials ◽  
Artificial Neural ◽  
Time Required

The thermodynamic characterisation of magnetocaloric materials is an essential task when evaluating the performance of a cooling process based on the magnetocaloric effect and its application in a magnetic refrigeration cycle. Several methods for the characterisation of magnetocaloric materials and their thermodynamic properties are available in the literature. These can be generally divided into theoretical and experimental methods. The experimental methods can be further divided into direct and indirect methods. In this paper, a new procedure based on an artificial neural network to predict the thermodynamic properties of magnetocaloric materials is reported. The results show that the procedure provides highly accurate predictions of both the isothermal entropy and the adiabatic temperature change for two different groups of magnetocaloric materials that were used to validate the procedure. In comparison with the commonly used techniques, such as the mean field theory or the interpolation of experimental data, this procedure provides highly accurate, time-effective predictions with the input of a small amount of experimental data. Furthermore, this procedure opens up the possibility to speed up the characterisation of new magnetocaloric materials by reducing the time required for experiments.

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