Vectorial near-field coupling

Abstract

The coherent exchange of optical near fields between two neighboring dipoles plays an essential role for the optical properties, quantum dynamics and thus for the function of many naturally occurring and artificial nanosystems. These interactions are inherently short-ranged, extending over a few nanometers only, and depend sensitively on relative orientation, detuning and dephasing, i.e., on the vectorial properties of the coupled dipolar near fields. This makes it challenging to analyze them experimentally. Here, we introduce plasmonic nanofocusing spectroscopy to record coherent light scattering spectra with 5-nm spatial resolution from a small dipole antenna, excited solely by evanescent fields and coupled to plasmon resonances in a single gold nanorod. We resolve mode couplings, resonance energy shifts and Purcell effects as a function of dipole distance and relative orientation, and show how they arise from different vectorial components of the interacting optical near-fields. Our results pave the way for using dipolar alignment to control the optical properties and function of nanoscale systems.

References in corpus (8)

• Room temperature coherent control of coupled single spins in solid
• Quantum-Information Processing with Semiconductor Macroatoms
• Room temperature entanglement between distant single spins in diamond
• Fano-type interpretation of red shifts and red tails in hole array transmission spectra
• Direct Observation of Controlled Coupling in an Individual Quantum Dot Molecule
• Carrier-envelope phase effects on the strong-field photoemission of electrons from metallic nanostructures
• Ultrafast nano-focusing with full optical waveform control
• Atomic-scale confinement of optical fields

Cited by in corpus (4)

• Quantifying nanoscale electromagnetic fields in near-field microscopy by Fourier demodulation analysis
• Subwavelength terahertz imaging via virtual superlensing in the radiating near field
• Excitonic Wave Function Reconstruction from Near-Field Spectra Using Machine Learning Techniques
• Brillouin Scattering Selection Rules in Polarization-Sensitive Photonic Resonators