Search arXivSearch

arXiv · 2607.00694

Near-Field Characterisation of Guided Modes in WS2 Nanobeams and Quasi-Bulk Crystals

Abstract

The exceptionally high in-plane refractive index, low sub-bandgap absorption, and strong optical anisotropy of WS2 make it a promising material platform for next-generation integrated circuits for nanophotonics. Its layered van der Waals structure further enables heterogeneous integration with silicon photonics and emerging two-dimensional optoelectronic materials. However, despite increasing interest in the waveguiding properties of WS2, experimental studies of wavelength-dependent modal confinement and attenuation remain limited. Additionally, though the extinction coefficient of WS2 is expected to be near-negligible beneath the bandgap, reported values span orders of magnitude, leading to large uncertainty in predicted modal decay lengths and wafer-scale integration feasibility. To resolve these ambiguities we perform hyperspectral cavity-enhanced imaging, determining high-resolution upper and lower bounds on the extinction coefficient of WS2 within the visible-NIR edge. We further employ scattering-type scanning near-field optical microscopy (s-SNOM) to probe TE0, TM0, and higher-order modes in both quasi-bulk and nanobeam WS2 waveguides across the 800-1400 nm spectral range, enabling identification of mode-specific trends in wavevector dispersion and loss. This work simultaneously assesses s-SNOM as a probe of waveguide performance, and we find that while absolute loss values depend on measurement geometry, s-SNOM reliably captures relative modal trends and provides upper bounds on propagation loss, supporting its use as a diagnostic tool for anisotropic waveguides. We further identify significant artefacts in nanobeam measurements arising from transverse interference and spatial sampling effects when the structure size approaches the excitation wavelength, which can shift extracted effective indices by up to 0.25.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zara S. Taylor, Luke M. Hallacy, Xuerong Hu, Oliver T. Williams, Simone Strohmair, Fabian Felixberger, Alexander J. Knight, Timothy Chester-Parsons, Luke R. Wilson, Alexander I. Tartakovskii. 2026-07-01. Near-Field Characterisation of Guided Modes in WS2 Nanobeams and Quasi-Bulk Crystals. https://arxiv.org/abs/2607.00694

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Exoplanet Detection Using Adaptive Quantum-Optimal Measurement

Detecting terrestrial exoplanets in the habitable zones of nearby stars remains a critical challenge. Such planets can be \(10^8\) to \(10^{10}\) times fainter than their host stars and lie at diffraction-limited angular separations, where starlight strongly obscures the companion signal. Here we present an adaptive quantum measurement method for estimating the number, positions, and brightnesses of mutually incoherent point sources in the sub-Rayleigh, ultra-high-contrast regime, operating at contrasts down to \(10^{-8}\) -- five orders of magnitude beyond previous quantum imaging approaches to exoplanet detection. The method adopts a spatial-mode basis that is updated to maximize the quantum Fisher information per detected photon. Estimation is performed by maximum likelihood in log-brightness coordinates, and the source count is determined by Bayesian-information-criterion (BIC) model selection directly from photon-count statistics, without a tunable detection threshold. For point sources within sub-Rayleigh separations and with brightness ratios spanning eight orders of magnitude, the method reconstructs complete scenes with a mean success rate of \(72.5\%\). Furthermore, it is robust to misalignment, maintaining a \(71.3\%\) success rate under offsets of up to six pixels. These results demonstrate that terrestrial exoplanets can be detected below the Rayleigh limit, a regime previously inaccessible to direct imaging.

physics.optics

Research and simulation of analytical polarization control enabled by optical computing on an integrated photonics chip

Dynamic polarization controllers are key devices with broad applications in many fields. However, most on-chip polarization controllers still rely on traditional blind-search methods, whereas analytical optical-computing approaches remain insufficiently explored, particularly with respect to calibration and endless polarization control. With the accurate relative phase of Mach-Zehnder interferometer (MZI) being fully controllable on an integrated photonics chip, we present an analytical polarization control (APC) method using four phase shifters and optical computing, eliminating the need for the traditional inefficient blind-search procedure. The basic structures and operations of APC are clarified. The proposed calibration method and endless control method enable continuous APC while compensating for phase differences within the MZI structures. We simulate the influence of the endless control unit on polarization control and quantify the effect of the fourth phase difference on the output extinction ratio. With the fourth phase shifter, the phase difference encountered during Stokes vector measurement can be effectively compensated, and rotations around all three axes on the Poincaré sphere can be realized. These results establish a practical APC architecture based on optical computing for photonics chips. The proposed APC methods, combined with a FPGA-based hardware acceleration, will enable high speed on-chip polarization controllers.

physics.optics

Optical Mode Sorting with a Programmable Diffractive Neural Network

Programmable diffractive optical processors are particularly attractive for spatial light manipulation because their optical transformations can be dynamically reconfigured and adapted without modifying the physical hardware. However, their practical performance is often limited by the gap between simulation and experiment caused by optical aberrations, alignment errors, and nonideal phase responses. In this paper, we introduce a hybrid optimization framework that combines high-dimensional numerical design with low-dimensional hardware-in-the-loop calibration, enabling programmable diffractive optical networks to compensate experimentally for mismatch without retraining their underlying optical transformations. We demonstrate a programmable optical diffractive neural network (ODNN) designed by back-propagation to spatially sort six linearly polarized modes supported by a multimode fiber. The experimental distortions are represented using a truncated Zernike basis with only 19 correction coefficients per layer. These coefficients are optimized directly on the physical system using stochastic parallel gradient descent, avoiding re-optimization of the full pixelated phase masks. Experimentally, the proposed calibration yields an SNR improvement of approximately 3.26 dB, and a decrease in amplitude error of 0.04. This separation of high-dimensional optical-function design from low-dimensional physical calibration provides a scalable route towards adaptive and reconfigurable spatial-mode processors for optical router on spatial modes and wavelengths, programmable photonic computer systems and quantum information processing.

physics.optics