arXiv subjects

Hannah Niese

Publications and source records attributed to Hannah Niese.

4 recordsLinked to original sources

arXiv2026

Plasmonic Fourier Surfaces Revisited: Relating Bandgaps with Bound States in the Continuum

Periodically corrugated metal interfaces supporting surface plasmon polaritons (SPPs) belong to the earliest nanoplasmonic platforms. Even simplest reliefs described by a few harmonics - plasmonic Fourier surfaces - display markedly different far-field signatures depending on the corrugation depth and symmetry: shallow reliefs exhibit a plasmonic bandgap (PBG) between two hybridized SPP standing waves, while deeper reliefs support asymmetry-induced single sharp resonances, termed over the last decade as quasi-bound states in the continuum (qBICs). Although these spectral features have long been observed experimentally and treated empirically, the underlying eigenmode evolution connecting the shallow and deep corrugation regimes has remained largely unexplored. Here we revisit this long-standing problem by analyzing it in terms of modern eigenstate formalism. Starting from the Rayleigh hypothesis, we develop a concise first-principle analytical description that explicitly captures how one eigenmode transforms from a dark bound state into an observable qBIC, while the other turns from bright into an overcoupled, unobservable state - thus unifying the SPP manifestations featuring PBG and qBIC within the same eigenmode framework. Finally, we demonstrate the practical relevance of the theory by showing how precise eigenstate engineering can enhance the SPP refractive index sensitivity.

physics.optics↗

arXiv2026

Broadband, compact, and training-free optical processors for parallel image classification

As artificial intelligence becomes increasingly prevalent, the demand for faster and more energy-efficient computing approaches grows. While optical computing offers intrinsic advantages in bandwidth and power consumption, existing implementations remain bulky, wavelength-specific, and dependent on complex training procedures, limiting scalability and parallel operation. In this work, we demonstrate a compact, training-free optical processor based on wavy diffractive features, known as Fourier surfaces, for parallel image classification. Our device achieves classification accuracies of up to 84% for digit datasets and 66% for fashion datasets within a 40$\times$40 $\mu$m$^2$ footprint. The diffractive layer inherently separates incident wavelengths into distinct output directions, enabling broadband operation and allowing multiple colors to function as independent computation channels. As a result, this passive system supports up to 20 simultaneous computations within a single optical pass. These results highlight the potential of nanoscale diffractive systems to achieve high compute densities, paving the way for scalable, low-power optical processors for machine learning and image-recognition applications.

physics.optics↗

arXiv2026

Fourier pixels for reciprocal light control

Digital cameras and displays utilise picture elements (pixels) that perform a single function: detecting or emitting light intensity. To exploit the full information content of electromagnetic waves, more advanced elements are required. This has driven the development of multifunctional components, which for example, simultaneously detect and emit intensity or extract intensity and spectral information. However, no pixel exists that both senses and generates optical wavefronts with full control over amplitude, phase, and polarisation, limiting reciprocal control and feedback of sophisticated light fields. Here we present a route to such pixels by demonstrating a versatile platform of miniaturised diffractive elements based on Fourier optics. We exploit plasmonic surface waves, which propagate coherently and efficiently across metallic surfaces. When these plasmons are launched towards wavy microstructures designed with simple Fourier analysis, arbitrary and background-free optical wavefronts are generated. Conversely, incoming light can be sensed and its amplitude, phase, and polarisation fully characterised. By combining or superposing several such components, we create multifunctional 'Fourier pixels' that provide compact and accurate control over the optical field. Our approach, which could also use photonic waveguide modes, establishes a scalable, universal architecture for vectorially programmable pixels with applications in adaptive optics, holographic displays, optical communication, and quantum-information processing.

physics.optics↗

arXiv2025

Low Power, Scalable Nanofabrication via Photon Upconversion

Micro- and nanoscale fabrication, which enables precise construction of intricate three-dimensional structures, is of foundational importance for advancing innovation in plasmonics, nanophotonics, and biomedical applications. However, scaling fabrication to industrially relevant levels remains a significant challenge. We demonstrate that triplet-triplet annihilation upconversion (TTA-UC) offers a unique opportunity to increase fabrication speeds and scalability of micro- and nanoscale 3D structures. Due to its nonlinearity and low power requirements, TTA-UC enables localized polymerization with nanoscale resolutions while simultaneously printing millions of voxels per second through optical parallelization using off-the-shelf light-emitting diodes and digital micromirror devices. Our system design and component integration empower fabrication with a minimum lateral feature size down to 230 nm and speeds up to 112 million voxels per second at a power of 7.0 nW per voxel. This combination of high resolution and fast print speed demonstrates that TTA-UC is a significant advancement in nanofabrication technique, evidenced by the fabrication of hydrophobic nanostructures on a square-centimeter scale, paving the way for industrial nanomanufacturing.

physics.app-ph↗