The new field of spin cavitronics focuses on the interaction between the magnon excitation of a magnetic element and the electromagnetic wave in a microwave cavity. In the strong interaction regime, such an interaction usually gives rise to the level anticrossing for the magnonic and the electromagnetic mode. Recently, the attractive level crossing has been observed, and it is explained by a non-Hermitian model Hamiltonian. However, the mechanism of such attractive coupling is still unclear. We reveal the secret by using a simple model with two harmonic oscillators coupled to a third oscillator with large dissipation. We further identify this dissipative third party as the invisible cavity mode with large leakage in cavity-magnon experiments. This understanding enables one to design dissipative coupling in all sorts of coupled systems.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1103/PhysRevLett.123.227201 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Ideal mentolabial sulcus depth in long-face, short-face, and normal-face in female individuals.
Oral Maxillofac Surg
January 2025
Department of Restorative, School of Dentistry, Dental Research Center, Hamadan University of Medical Sciences, Pajouhesh Square, Hamadan, 6517838736, Iran.
Purpose: The harmony between the lips and the chin is an essential parameter in facial esthetics, and the mentolabial sulcus (MLS) represents the level of this harmony. This study aimed to assess the effect of MLS depth on facial profile attractiveness in long-face, short-face, and normal-face Iranian female individuals.
Methods: An observational study with a questionnaire was conducted, and a profile photograph of an Iranian female with class I occlusion was altered to create long-face, normal-face and short-face profiles with MLS depth ranging from 1 to 12 mm.
Isolation of Quick-Response High-Affinity Aptamers for Continuous and Reagentless Detection of Thrombin.
Anal Chem
January 2025
Department of Chemistry, Capital Normal University, Xisanhuan North Road. 105, Beijing 100048, China.
Continuous and reagentless biomolecular detection technologies are bringing an evolutionary influence on disease diagnostics and treatment. Aptamers are attractive as specific recognition probes because they are capable of regeneration without washing. Unfortunately, the affinity and dissociation kinetics of the aptamers developed to date show an inverse relationship, preventing continuous and reagentless detection of protein targets due to their low dissociation rates.
View Article and Find Full Text PDFDonor-Acceptor Type Carbon Nitride Photocatalysts in Photocatalysis: Current Understanding, Applications and Challenges.
Small
January 2025
College of Resources, Hunan Agricultural University, Changsha, 410128, China.
The exploration of photocatalytic materials with efficient charge separation has always been a prominent area of research in photocatalysis. In the preceding years, the strategy of constructing donor-acceptor (D-A) structured materials has gradually been developed in photocatalytic systems, becoming a new research crossroads and attracting extensive interdisciplinary focus. Polymeric carbon nitride (PCN) has gradually been recognized as the primary photocatalytic material for constructing D-A structures due to its attractive exceptional physicochemical stability, electronic band structure, and cost-effectiveness.
View Article and Find Full Text PDFPotential drug targets for asthma identified through mendelian randomization analysis.
Respir Res
January 2025
Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Background: The emergence of new molecular targeted drugs marks a breakthrough in asthma treatment, particularly for severe cases. Yet, options for moderate-to-severe asthma treatment remain limited, highlighting the urgent need for novel therapeutic drug targets. In this study, we aimed to identify new treatment targets for asthma using the Mendelian randomization method and large-scale genome-wide association data (GWAS).
View Article and Find Full Text PDFStructural analysis of physical gel networks using graph neural networks.
Eur Phys J E Soft Matter
January 2025
Institut für Theoretische Physik 1, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, 91058, Bavaria, Germany.
We employ graph neural networks (GNN) to analyse and classify physical gel networks obtained from Brownian dynamics simulations of particles with competing attractive and repulsive interactions. Conventionally such gels are characterized by their position in a state diagram spanned by the packing fraction and the strength of the attraction. Gel networks at different regions of such a state diagram are qualitatively different although structural differences are subtile while dynamical properties are more pronounced.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!