Muonic knight shift for simple metals in a linear-response model

1981 ◽  
Vol 61 (2) ◽  
pp. 353-360 ◽  
Author(s):  
R. De Renzi ◽  
V. Dallacasa
Keyword(s):  
Linear Response ◽  
Knight Shift ◽  
Response Model

Unveiling Solvents Effect on Excited-State Polarizabilities with the Corrected Linear-Response Model

2014 ◽  
Vol 118 (30) ◽  
pp. 5652-5656 ◽  
Author(s):  
Šimon Budzák ◽  
Miroslav Medved′ ◽  
Benedetta Mennucci ◽  
Denis Jacquemin
Keyword(s):  
Excited State ◽  
Linear Response ◽  
Response Model

scholarly journals (U) A Linear Response Model Predicts Reactivity From a Density Profile

2021 ◽  
Author(s):  
Jennifer Disterhaupt ◽  
Erik Skau ◽  
Dean Sanzo ◽  
Marc Klasky
Keyword(s):  
Density Profile ◽  
Linear Response ◽  
Response Model

scholarly journals Possible biases in scaling-based estimates of glacier change: a case study in the Himalaya

2020 ◽  
Vol 14 (9) ◽  
pp. 3235-3247
Author(s):  
Argha Banerjee ◽  
Disha Patil ◽  
Ajinkya Jadhav
Keyword(s):  
Response Time ◽  
Climate Sensitivity ◽  
Linear Response ◽  
Model Simulation ◽  
Change Scenario ◽  
Response Model ◽  
Future Evolution ◽  
Scaling Model ◽  
Mountain Glaciers

Abstract. Approximate glacier models are routinely used to compute the future evolution of mountain glaciers under any given climate-change scenario. A majority of these models are based on statistical scaling relations between glacier volume, area, and/or length. In this paper, long-term predictions from scaling-based models are compared with those from a two-dimensional shallow-ice approximation (SIA) model. We derive expressions for climate sensitivity and response time of glaciers assuming a time-independent volume–area scaling. These expressions are validated using a scaling-model simulation of the response of 703 synthetic glaciers from the central Himalaya to a step change in climate. The same experiment repeated with the SIA model yields about 2 times larger climate sensitivity and response time than those predicted by the scaling model. In addition, the SIA model obtains area response time that is about 1.5 times larger than the corresponding volume response time, whereas scaling models implicitly assume the two response times to be equal to each other. These results indicate the possibility of a low bias in the scaling model estimates of the long-term loss of glacier area and volume. The SIA model outputs are used to obtain parameterisations, climate sensitivity, and response time of glaciers as functions of ablation rate near the terminus, mass-balance gradient, and mean thickness. Using a linear-response model based on these parameterisations, we find that the linear-response model outperforms the scaling model in reproducing the glacier response simulated by the SIA model. This linear-response model may be useful for predicting the evolution of mountain glaciers on a global scale.

scholarly journals The Born model can accurately describe electrostatic ion solvation

2020 ◽  
Vol 22 (43) ◽  
pp. 25126-25135
Author(s):  
Timothy T. Duignan ◽  
X. S. Zhao
Keyword(s):  
Oxygen Atom ◽  
Linear Response ◽  
Ion Solvation ◽  
Response Model ◽  
Free Energies ◽  
Born Model ◽  
Repulsion Force ◽  
Solvation Free Energies

The solvation free energies of ions in water are consistent with the Born linear response model if the centre on which the ion–water repulsion force acts is moved from the oxygen atom towards the hydrogens.

Open-shell linear response model and the systematics of octupole states in Ge and Se isotopes

1984 ◽  
Vol 10 (6) ◽  
pp. 785-789
Author(s):  
J Bar-Touv ◽  
S Mordechai
Keyword(s):  
Linear Response ◽  
Open Shell ◽  
Response Model

806 Linear Response Model for an Axle Weighing System in Consideration of Moving Loads

2007 ◽  
Vol 2007 (0) ◽  
pp. _806-1_-_806-6_
Author(s):  
Kengo FUKUDA ◽  
Koji YOSHIDA ◽  
Tetsuya KINUGASA ◽  
Kazuhito KANAZAWA ◽  
Toshiro ONO
Keyword(s):  
Linear Response ◽  
Response Model ◽  
Moving Loads
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