Personne
Peng Chen
Cette personne n’est plus à l’EPFL
Publications associées (12)
Berry curvature dipole generation and helicity-to-spin conversion at symmetry-mismatched heterointerfaces
The Berry curvature dipole (BCD) is a key parameter that describes the geometric nature of energy bands in solids. It defines the dipole-like distribution of Berry curvature in the band structure and plays a key role in emergent nonlinear phenomena. The th ...
NATURE PORTFOLIO2023Reconfigurable nonreciprocal excitation of propagating exchange spin waves in perpendicularly magnetized yttrium iron garnet thin films
Jean-Philippe Ansermet, Haiming Yu, Yu Zhang, Peng Chen, Jilei Chen, Tao Liu, Jinlong Wang, Rundong Yuan
We report the nonreciprocal excitation of propagating forward volume exchange spin waves in yttrium iron garnet (YIG) thin film with perpendicular anisotropy by bringing the in-plane magnetization of Co20Fe60B20 (CoFeB) nanowires to resonance. All-electric ...
College Pk2023Long-distance coherent propagation of magnon polarons in a ferroelectric-ferromagnetic heterostructure
Jean-Philippe Ansermet, Haiming Yu, Peng Chen, Jilei Chen, Jianyu Zhang, Yao Zhang, Song Liu, Jinlong Wang
We experimentally demonstrate the coherent propagation of magnon polarons, the hybridized excitations formed by the coupling of spin waves and Rayleigh/Love surface acoustic waves, in a heterostructure consisting of ferroelectric BaTiO3 and ferromagnetic L ...
College Pk2023Multilevel and weighted reduced basis method for stochastic optimal control problems constrained by Stokes equations
Alfio Quarteroni, Gianluigi Rozza, Peng Chen
In this paper we develop and analyze a multilevel weighted reduced basis method for solving stochastic optimal control problems constrained by Stokes equations. We prove the analytic regularity of the optimal solution in the probability space under certain ...
Springer Heidelberg2016A new algorithm for high-dimensional uncertainty quantification based on dimension-adaptive sparse grid approximation and reduced basis methods
In this work we develop an adaptive and reduced computational algorithm based on dimension-adaptive sparse grid approximation and reduced basis methods for solving highdimensional uncertainty quantification (UQ) problems. In order to tackle the computation ...
Elsevier2015MATHICSE Technical Report : Reduced order methods for uncertainty quantification problems
Alfio Quarteroni, Gianluigi Rozza, Peng Chen
This work provides a review on reduced order methods in solving uncertainty quantification problems. A quick introduction of the reduced order methods, including proper orthogonal decomposition and greedy reduced basis methods, are presented along with the ...
MATHICSE2015Comparison between reduced basis and stochastic collocation methods for elliptic problems
Alfio Quarteroni, Gianluigi Rozza, Peng Chen
The stochastic collocation method has recently been applied to stochastic problems that can be transformed into parametric systems. Meanwhile, the reduced basis method, primarily developed for solving parametric systems, has been recently used to deal with ...
Springer Verlag2014A weighted empirical interpolation method: a priori convergence analysis and applications
Alfio Quarteroni, Gianluigi Rozza, Peng Chen
We extend the classical empirical interpolation method to a weighted empirical interpolation method in order to approximate nonlinear parametric functions with weighted parameters, e.g. random variables obeying various probability distributions. A priori c ...
EDP Sciences2014Accurate and efficient evaluation of failure probability for partial different equations with random input data
Several computational challenges arise when evaluating the failure probability of a given system in the context of risk prediction or reliability analysis. When the dimension of the uncertainties becomes high, well established direct numerical methods can ...
Elsevier Science Sa2013A Weighted Reduced Basis Method For Elliptic Partial Differential Equations With Random Input Data
Alfio Quarteroni, Gianluigi Rozza, Peng Chen
In this work we propose and analyze a weighted reduced basis method to solve elliptic partial differential equations (PDEs) with random input data. The PDEs are first transformed into a weighted parametric elliptic problem depending on a finite number of p ...
Siam Publications2013