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Traditionally, gravitational waves are detected with techniques such as matched filtering or unmodeled searches based on wavelets. However, in the case of generic black hole binaries with non-aligned spins, if one wants to explore the whole…

General Relativity and Quantum Cosmology · Physics 2023-07-26 Paraskevi Nousi , Alexandra E. Koloniari , Nikolaos Passalis , Panagiotis Iosif , Nikolaos Stergioulas , Anastasios Tefas

Recurrence networks are powerful tools used effectively in the nonlinear analysis of time series data. The analysis in this context is done mostly with unweighted and undirected complex networks constructed with specific criteria from the…

Chaotic Dynamics · Physics 2017-09-18 Rinku Jacob , K. P. Harikrishnan , R. Misra , G. Ambika

A modeling approach is proposed based on transmission line theory for the characterization of the periodic rectangular waveguide grating (RWG) structure. Using an equivalent circuit (EC) model the dispersion equation of the structure is…

Applied Physics · Physics 2018-03-16 Ye Chen , Yaogen Ding

The optimal allocation of channels and power resources plays a crucial role in ensuring minimal interference, maximal data rates, and efficient energy utilisation. As a successful approach for tackling resource management problems in…

Networking and Internet Architecture · Computer Science 2024-08-09 Lili Chen , Jingge Zhu , Jamie Evans

We present a discrete model of resonant scattering of waves by an open periodic waveguide. The model elucidates a phenomenon common in electromagnetics, in which the interaction of plane waves with embedded guided modes of the waveguide…

Mathematical Physics · Physics 2011-01-04 Natalia Ptitsyna , Stephen P. Shipman

Diffusion-driven instability is a fundamental mechanism underlying pattern formation in spatially extended systems. In almost all existing works, diffusion across the links of the underlying network is modeled through scalar weights,…

Statistical Mechanics · Physics 2026-02-16 Anna Gallo , Wilfried Segnou , Timoteo Carletti

The modified rigorous coupled-wave analysis technique is developed to describe the optical characteristics of the plasmonic structures with the grating-gated delta-thin conductive channel in the far- and near-field zones of electromagnetic…

Mesoscale and Nanoscale Physics · Physics 2021-01-14 Yurii M. Lyaschuk , Serhii M. Kukhtaruk , Vytautas Janonis , Vadym V. Korotyeyev

Optical resonators are structures that utilize wave interference and feedback to confine light in all three dimensions. Depending on the feedback mechanism, resonators can support either standing- or traveling-wave modes. Over the years,…

Optics · Physics 2022-08-30 Qi Zhong , Haoqi Zhao , Liang Feng , Kurt Busch , Sahin K. Ozdemir , Ramy El-Ganainy

We study long range propagation of electromagnetic waves in random waveguides with rectangular cross-section and perfectly conducting boundaries. The waveguide is filled with an isotropic linear dielectric material, with randomly…

Mathematical Physics · Physics 2013-10-21 Ricardo Alonso , Liliana Borcea

We show that anisotropic planar anti-guiding waveguide structures with two radiation channels towards the surrounding cladding materials can support unidirectional guided resonances (UGRs), where radiation is cancelled in one of the…

Routing quantum information between non-local computational nodes is a foundation for extensible networks of quantum processors. Quantum information transfer between arbitrary nodes is generally mediated either by photons that propagate…

A core technology that has emerged from the artificial intelligence revolution is the recurrent neural network (RNN). Its unique sequence-based architecture provides a tractable likelihood estimate with stable training paradigms, a…

Disordered Systems and Neural Networks · Physics 2020-07-01 Mohamed Hibat-Allah , Martin Ganahl , Lauren E. Hayward , Roger G. Melko , Juan Carrasquilla

Gravitational waves at kilohertz and higher frequencies offer a unique probe of the early Universe at temperatures well beyond the reach of the cosmic microwave background, corresponding to energy scales $\gtrsim 10^9$GeV. Existing detector…

General Relativity and Quantum Cosmology · Physics 2026-02-17 Jan Heisig

Geographically Weighted Regression (GWR) is a widely recognized technique for modeling spatial heterogeneity. However, it is commonly assumed that the relationships between dependent and independent variables are linear. To overcome this…

Machine Learning · Computer Science 2025-04-08 Jianfei Cao , Dongchao Wang

Deep residual networks were shown to be able to scale up to thousands of layers and still have improving performance. However, each fraction of a percent of improved accuracy costs nearly doubling the number of layers, and so training very…

Computer Vision and Pattern Recognition · Computer Science 2017-06-15 Sergey Zagoruyko , Nikos Komodakis

Graphene nanoribbons (GNRs) are one-dimensional nanostructures predicted to display a rich variety of electronic behaviors. Depending on their structure, GNRs realize metallic and semiconducting electronic structures with band gaps that can…

Mesoscale and Nanoscale Physics · Physics 2013-10-16 Oleg V. Yazyev

Photonic crystal waveguides (PCWs) play a critical role in precisely controlling light propagation, enabling high-performance functions in applications such as optical communication and integrated photonics. The design of PCWs traditionally…

Optics · Physics 2024-10-10 Lucian Feng

We consider the waveguiding by thin patterned slabs embedded in a homogeneous medium. In the longwave limit, the wave spectra of slabs are found to be well described by a single frequency-independent parameter, which we call the "guiding…

Optics · Physics 2007-09-28 Serge Luryi , Arsen V. Subashiev

The high-quality-factor mechanical resonator in electromechanical systems has facilitated dynamic control of phonons via parametric nonlinear processes and paved the development of mechanical logic-elements. However the resonating element…

Mesoscale and Nanoscale Physics · Physics 2019-02-28 Daiki Hatanaka , Tom Darras , Imran Mahboob , Koji Onomitsu , Hiroshi Yamaguchi

Graph Convolutional Networks (GCNs) have gained significant developments in representation learning on graphs. However, current GCNs suffer from two common challenges: 1) GCNs are only effective with shallow structures; stacking multiple…

Machine Learning · Computer Science 2019-12-13 Menghan Wang , Kun Zhang , Gulin Li , Keping Yang , Luo Si