Emergent coherent modes in nonlinear magnonic waveguides detected at ultrahigh frequency resolution

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

The terahertz (THz) frequency region (0.1-10 THz) between microwaves and infrared, holds significant potential across various fields such as communication, sensing, and spectroscopy. Conventional THz systems for broadband emission and detection remain bulk ...

Microwave superconducting resonators are extensively studied in fields such as quantum computing and electron spin resonance (ESR) spectroscopy. However, the integration of superconducting resonators with feedback mechanisms to create ultra-low noise oscil ...

With recent innovations in artificial intelligence (AI), machines can now recognize architectural patterns and generate new forms in ways that far exceed human capacity. The integration of machines in the design process has ushered in a substantial shift i ...

Learning manipulation from demonstration is a key way for humans to teach complex tasks. However, this domain mainly focuses on kinetic teaching, and does not consider imitation of interaction forces which is essential for more contact rich tasks. We propo ...

The increasing implementation of programs supported by machine learning in medical contexts will affect psychiatry. It is crucial to accompany this development with careful ethical considerations informed by empirical research involving experts from the fi ...

The use of machine learning for predicting ecotoxicological outcomes is promising, but underutilized. The curation of data with informative features requires both expertise in machine learning as well as a strong biological and ecotoxicological background, ...

While road obstacle detection techniques have become increasingly effective, they typically ignore the fact that, in practice, the apparent size of the obstacles decreases as their distance to the vehicle increases. In this letter, we account for this by c ...

The prospect of massive parallelism of optics enabling fast and low energy cost operations is attracting interest for novel photonic circuits where 3-dimensional (3D) implementations have a high potential for scalability. Since the technology for data inpu ...

Abstractive summarization has seen big improvements in recent years, mostly due to advances in neural language modeling, language model pretraining, and scaling models and datasets. While large language models generate summaries that are fluent, coherent, ...

Microcavity polaritons are strongly interacting hybrid light-matter quasiparticles, which are promising for the development of novel light sources and active photonic devices. Here, we report polariton lasing in the UV spectral range in microring resonator ...

Information is the resolution of uncertainty and manifests itself as patterns. Although complex, most observable phenomena are not random and instead are associated with deterministic, chaotic systems. The underlying patterns and symmetries expressed from ...

Multimode fibers (MMF) were initially developed to transmit digital information encoded in the time domain. There were few attempts in the late 60s and 70s to transmit analog images through MMF. With the availability of digital spatial modulators, practica ...

Optical microresonators with high quality (Q) factors are essential to a wide range of integrated photonic devices. Steady efforts have been directed towards increasing microresonator Q factors across a variety of platforms. With success in reducing microf ...

We present a discriminative clustering approach in which the feature representation can be learned from data and moreover leverage labeled data. Representation learning can give a similarity-based clustering method the ability to automatically adapt to an ...

Phonon-assisted luminescence is a key property of defect centers in semiconductors, and can be measured to perform the readout of the information stored in a quantum bit, or to detect temperature variations. The investigation of phonon-assisted luminescenc ...

Purpose: We have introduced an artificial intelligence framework, 31P-SPAWNN, in order to fully analyze phosphorus-31 (P-31) magnetic resonance spectra. The flexibility and speed of the technique rival traditional least-square fitting methods, with the per ...

Emergent coherent modes in nonlinear magnonic waveguides detected at ultrahigh frequency resolution

Chat with Graph Search

Single-Chip for Terahertz Emission and Detection on Thin-Film Lithium Niobate Platform

Superconducting microwave oscillators as detectors for ESR spectroscopy

Deep Architectural Form

Learning Motion Reconstruction from Demonstration via Multi-Modal Soft Tactile Sensing

Explainability as fig leaf? An exploration of experts’ ethical expectations towards machine learning in psychiatry

A benchmark dataset for machine learning in ecotoxicology

Perspective Aware Road Obstacle Detection

From 3D to 2D and back again

Interpretable Representation Learning and Evaluation for Abstractive Summarization

Polariton lasing in AlGaN microring with GaN/AlGaN quantum wells

Measurement in the Age of Information

Learning to image and compute with multimode optical fibers

Probing material absorption and optical nonlinearity of integrated photonic materials

Discriminative clustering with representation learning with any ratio of labeled to unlabeled data

Phonon-Assisted Luminescence in Defect Centers from Many-Body Perturbation Theory

In vivo magnetic resonance P-31-Spectral Analysis With Neural Networks: 31P-SPAWNN