Results 61 to 70 of about 123,227 (279)
This study demonstrates coherent control of 15N nuclear spins coupled to VB−${\text{V}}_{\text{B}}^{-}$ centers in isotope‐enriched hexagonal boron nitride. Selective addressing via spin‐state mixing enables Rabi driving, quantum gates, and coherence times exceeding 10 μs$\umu{\rm s}$.
Adalbert Tibiássy +6 more
wiley +1 more source
Imaging of Biphoton States: Fundamentals and Applications
Quantum states of two photons exhibit a rich polarization and spatial structure, which provides a fundamental resource of strongly correlated and entangled states. This review analyzes the physics of these intriguing properties and explores the various techniques and technologies available to measure them, including the state of the art of their ...
Alessio D'Errico, Ebrahim Karimi
wiley +1 more source
Electric‐Current‐Assisted Nucleation of Zero‐Field Hopfion Rings
This work reports a novel and efficient nucleation protocol for 3D localized topological magnetic solitons‐hopfion rings in chiral magnets using pulsed electric currents. By using Lorentz transmission electron microscopy and topological analysis, we report characteristic features and extraordinary stability of hopfion rings in zero or inverted external
Xiaowen Chen +12 more
wiley +1 more source
Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain
A new approach uses simple neural networks to create digital twins of brain activity, capturing how different patterns unfold over time. The method generates and recovers key dynamics even from noisy data. When applied to fMRI, it predicts brain signals and reveals distinctive activity patterns across regions and individuals, opening possibilities for ...
Gabriele Di Antonio +3 more
wiley +1 more source
Solid Harmonic Wavelet Bispectrum for Image Analysis
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown +3 more
wiley +1 more source
Rapid Proteome‐Wide Discovery of Protein–Protein Interactions With ppIRIS
ppIRIS is a lightweight deep learning framework for proteome‐wide protein–protein interaction prediction directly from sequence. By fusing evolutionary and structural embeddings with a regularized Siamese architecture, ppIRIS achieves state‐of‐the‐art accuracy across species, enables minute‐scale screening, and reveals biologically validated bacterial ...
Luiz Felipe Piochi +4 more
wiley +1 more source
A probabilistic framework based on random time‐space coding metasurfaces enables control of the spatial distribution of electromagnetic fields temporal statistics. By tailoring the marginal and joint distributions of random codes, electromagnetic fields with desired mean and variance patterns are realized, enabling simultaneous transmission and jamming.
Jia Cheng Li +3 more
wiley +1 more source
Beyond the Non‐Hermitian Skin Effect: Scaling‐Controlled Topology from Exceptional‐Bound Bands
ABSTRACT We establish a novel mechanism for topological transitions in non‐Hermitian systems that are controlled by the system size. Based on a new paradigm known as exceptional‐bound (EB) band engineering, its mechanism hinges on the unique critical scaling behavior near an exceptional point, totally unrelated to the well‐known non‐Hermitian skin ...
Mengjie Yang, Ching Hua Lee
wiley +1 more source
Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization
Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed +4 more
wiley +1 more source
Considering spatiotemporal evolutionary information in dynamic multi‐objective optimisation
Abstract Preserving population diversity and providing knowledge, which are two core tasks in the dynamic multi‐objective optimisation (DMO), are challenging since the sampling space is time‐ and space‐varying. Therefore, the spatiotemporal property of evolutionary information needs to be considered in the DMO.
Qinqin Fan +3 more
wiley +1 more source

