English
Related papers

Related papers: Inverse-design magnonic devices

200 papers

Magnons - the quanta of spin waves - propagating in magnetic materials with wavelengths at the nanometer-scale and carrying information in the form of an angular momentum, can be used as data carriers in next-generation, nano-sized low-loss…

Mesoscale and Nanoscale Physics · Physics 2017-06-07 A. V. Chumak , A. A. Serha , B. Hillebrands

The use of spin waves as a signal carrier requires developing the functional elements allowing for multiplexing and demultiplexing information coded at different wavelengths. For this purpose, we propose a system of thin ferromagnetic…

Mesoscale and Nanoscale Physics · Physics 2021-05-25 Pierre Roberjot , Krzysztof Szulc , Jarosław W. Kłos , Maciej Krawczyk

The advent of two-dimensional metamaterials in recent years has ushered in a revolutionary means to manipulate the behavior of light on the nanoscale. The effective parameters of these architected materials render unprecedented control over…

Optics · Physics 2018-11-14 Zhaocheng Liu , Dayu Zhu , Sean P. Rodrigues , Kyu-Tae Lee , Wenshan Cai

Lithium niobate-on-insulator (LNOI) is an emerging photonic platform that exhibits favorable material properties (such as low optical loss, strong nonlinearities, and stability) and enables large-scale integration with stronger optical…

Inverse design refers to the problem of optimizing the input of an objective function in order to enact a target outcome. For many real-world engineering problems, the objective function takes the form of a simulator that predicts how the…

There is growing interest in engineering unconventional computing devices that leverage the intrinsic dynamics of physical substrates to perform fast and energy-efficient computations. Granular metamaterials are one such substrate that has…

Machine Learning · Computer Science 2024-04-09 Atoosa Parsa , Corey S. O'Hern , Rebecca Kramer-Bottiglio , Josh Bongard

Multifunctional metamaterials (MMM) bear promise as next-generation material platforms supporting miniaturization and customization. Despite many proof-of-concept demonstrations and the proliferation of deep learning assisted design, grand…

Computational Engineering, Finance, and Science · Computer Science 2024-03-28 Doksoo Lee , Lu Zhang , Yue Yu , Wei Chen

Inverse microstructure design plays a central role in materials discovery, yet remains challenging due to the complexity of structure-property linkages and the scarcity of labeled training data. We propose Design-GenNO, a physics-informed…

Mathematical Physics · Physics 2025-09-11 Yaohua Zang , Phaedon-Stelios Koutsourelakis

A novel control design approach for general nonlinear systems is presented in this paper. The approach is based on the identification of a polynomial model of the system to control and on the on-line inversion of this model. An efficient…

Systems and Control · Computer Science 2014-07-07 C. Novara , M. Milanese

Understanding how nano- or micro-scale structures and material properties can be optimally configured to attain specific functionalities remains a fundamental challenge. Photonic metasurfaces, for instance, can be spectrally tuned through…

Wave-based data processing by spin waves and their quanta, magnons, is a promising technique to overcome the challenges which CMOS-based logic networks are facing nowadays. The advantage of these quasi-particles lies in their potential for…

In recent years, the development of nanophotonic devices has presented a revolutionary means to manipulate light at nanoscale. Recently, artificial neural networks (ANNs) have displayed powerful ability in the inverse design of nanophotonic…

Precise spatial manipulation of particles via optical forces is essential in many research areas, ranging from biophysics to atomic physics. Central to this effort is the challenge of designing optical systems that are optimized for…

We theoretically investigate the plasmonic properties of mid-infrared graphene-based metamaterials and apply deep learning of a neural network for the inverse design. These artificial structures have square periodic arrays of graphene…

Applied Physics · Physics 2020-02-20 Anh D. Phan , Cuong V. Nguyen , Pham T. Linh , Tran V. Huynh , Vu D. Lam , Anh-Tuan Le

Microstructural materials design is one of the most important applications of inverse modeling in materials science. Generally speaking, there are two broad modeling paradigms in scientific applications: forward and inverse. While the…

Machine Learning · Computer Science 2021-01-27 Zijiang Yang , Dipendra Jha , Arindam Paul , Wei-keng Liao , Alok Choudhary , Ankit Agrawal

System design tools are often only available as input-output blackboxes: for a given design as input they compute an output representing system behavior. Blackboxes are intended to be run in the forward direction. This paper presents a new…

Machine Learning · Computer Science 2022-04-08 Sanjai Narain , Emily Mak , Dana Chee , Brendan Englot , Kishore Pochiraju , Niraj K. Jha , Karthik Narayan

In this article, we propose a programmable plasmonic waveguide system (PPWS) to achieve several different functions based on metal coding metamaterials (MCMs) and inverse design technology. There is no need to spend much time on considering…

Optics · Physics 2021-01-05 Yihang Dan , Tian Zhang , Jian Dai , Kun Xu

Cavity magnonics is an emerging research area focusing on the coupling between magnons and photons. Despite its great potential for coherent information processing, it has been long restricted by the narrow interaction bandwidth. In this…

Mesoscale and Nanoscale Physics · Physics 2024-02-15 Jing Xu , Changchun Zhong , Shihao Zhuang , Chen Qian , Yu Jiang , Amin Pishehvar , Xu Han , Dafei Jin , Josep M. Jornet , Bo Zhen , Jiamian Hu , Liang Jiang , Xufeng Zhang

In this work, perfectly-matched metamaterials (PMMs) are described and combined with inverse design to realize broadband devices. PMMs are discretized metamaterials with anisotropic unit cells selected from a constrained design space,…

A memetic framework for optimal inverse design is proposed by combining a local gradient-based procedure and a robust global scheme. The procedure is based on method-of-moments matrices and does not demand full inversion of a system matrix.…

Optimization and Control · Mathematics 2023-10-10 Miloslav Capek , Lukas Jelinek , Petr Kadlec , Mats Gustafsson