elementary excitations
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2022 ◽  
Vol 974 ◽  
pp. 115626
Author(s):  
Pei Sun ◽  
Jintao Yang ◽  
Yi Qiao ◽  
Junpeng Cao ◽  
Wen-Li Yang

2021 ◽  
Vol 103 (12) ◽  
Author(s):  
Jintae Kim ◽  
Minsoo Kim ◽  
Pramod Padmanabhan ◽  
Jung Hoon Han ◽  
Hyun-Yong Lee

2021 ◽  
Vol 103 (10) ◽  
Author(s):  
H. Godfrin ◽  
K. Beauvois ◽  
A. Sultan ◽  
E. Krotscheck ◽  
J. Dawidowski ◽  
...  

2021 ◽  
Vol 264 ◽  
pp. 114933
Author(s):  
Stevo K. Jaćimovski ◽  
Jelena S. Lamovec ◽  
Jovan P. Šetrajčić ◽  
Dušan I. Ilić

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Qi Wang ◽  
Jun Ding ◽  
Longfei Zhang ◽  
Evgeny Podryabinkin ◽  
Alexander Shapeev ◽  
...  

AbstractThe elementary excitations in metallic glasses (MGs), i.e., β processes that involve hopping between nearby sub-basins, underlie many unusual properties of the amorphous alloys. A high-efficacy prediction of the propensity for those activated processes from solely the atomic positions, however, has remained a daunting challenge. Recently, employing well-designed site environment descriptors and machine learning (ML), notable progress has been made in predicting the propensity for stress-activated β processes (i.e., shear transformations) from the static structure. However, the complex tensorial stress field and direction-dependent activation could induce non-trivial noises in the data, limiting the accuracy of the structure-property mapping learned. Here, we focus on the thermally activated elementary excitations and generate high-quality data in several Cu-Zr MGs, allowing quantitative mapping of the potential energy landscape. After fingerprinting the atomic environment with short- and medium-range interstice distribution, ML can identify the atoms with strong resistance or high compliance to thermal activation, at a high accuracy over ML models for stress-driven activation events. Interestingly, a quantitative “between-task” transferring test reveals that our learnt model can also generalize to predict the propensity of shear transformation. Our dataset is potentially useful for benchmarking future ML models on structure-property relationships in MGs.


2020 ◽  
Vol 2020 (12) ◽  
Author(s):  
Zhirong Xin ◽  
Yusong Cao ◽  
Xiaotian Xu ◽  
Tao Yang ◽  
Junpeng Cao ◽  
...  

Abstract Based on its off-diagonal Bethe ansatz solution, we study the thermodynamic limit of the spin-$$ \frac{1}{2} $$ 1 2 XYZ spin chain with the antiperiodic boundary condition. The key point of our method is that there exist some degenerate points of the crossing parameter ηm,l, at which the associated inhomogeneous T − Q relation becomes a homogeneous one. This makes extrapolating the formulae deriving from the homogeneous one to an arbitrary η with O(N−2) corrections for a large N possible. The ground state energy and elementary excitations of the system are obtained. By taking the trigonometric limit, we also give the results of antiperiodic XXZ spin chain within the gapless region in the thermodynamic limit, which does not have any degenerate points.


Optica ◽  
2020 ◽  
Vol 7 (9) ◽  
pp. 1045 ◽  
Author(s):  
Petr Zapletal ◽  
Bogdan Galilo ◽  
Andreas Nunnenkamp

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