Conference Agenda

Attosecond, atomic-scale movies remain a long-standing dream, with transformative applications from tracking resonances in metamaterials to observing phase transitions in strongly correlated materials. We propose a radical new route to this vision: HADES - Harmonic Deactivation Microscopy. By confining solid-state HHG far below the diffraction limit using an orbital-angular-momentum prepulse, we achieve selective deactivation of harmonic emission through a generalized quantum-optical framework we recently introduced and demonstrated. This mechanism interferes hidden photon pathways to enhance or suppress HHG with near-unity efficiency. HADES opens the door to all-optical, label-free super-resolution nanoscopy and control over nonlinear light–matter interactions.

In this work, we develop a simulation framework to evaluate performance of Structured Illumination Microscopy (SIM) for two-dimensional metrology. The framework is extended to multiple structured illumination microscopy (MSIM), where individual frequency components are combined in Fourier space, and to its intensity-based variant (SI-MSIM), where these components are merged in real space through intensity summation. A chirped grating is employed as the test sample. The results show that SIM, MSIM, and SI-MSIM improve resolution at all contrast thresholds compared to the wide-field method. These findings highlight the potential of SIM-based techniques for quantitative, label-free dimensional metrology.

In semiconductor manufacturing, continued miniaturization places increasing demands on overlay metrology. Accurate stacking of up to hundreds of layers requires subnanometer precision. Digital holographic microscopy is a promising method for achieving this precision with diffraction-based overlay targets. However, cross talk from surrounding structures can limit accurate extraction of the overlay signal. Here, we present a structured illumination approach that computationally improves overlay precision by identifying the contribution from surrounding structures and correcting the target signal.

Digital holography use to require a known reference beam, typically a plane wave, for phase recording. We present a reference-free interferometric framework based on the Spatial-Shifting Cepstrum (SSC) algorithm, enabling the decoupling of two arbitrary complex optical fields without prior knowledge of either beam. The method exploits controlled spatial shifts between sequential off-axis holograms and applies cepstral-domain processing to isolate each field contribution. Theoretical formulation, numerical implementation, and experimental validation in several configurations are reported. The approach achieves accurate quantitative phase imaging (QPI), increases the effective field of view, and relaxes architectural constraints.

This paper presents recent developments in hybrid computational imaging approaches for 3D motion analysis and quantitative phase imaging in automated microscopy. By integrating digital holographic microscopy with deep learning models, this work enhances the capabilities of machine microvision. High-tech fields such as micro-robotics and photonics require accurate, robust and rapid in situ measurements using complex multi-scale parameters. Unlike conventional data-driven methods, physics-based deep learning does not require training or requires minimal data, enabling real-time optical information processing. A prototype of digital holographic microscope, with a hybrid deep neural network for autofocusing and phase imaging is proposed. The main challenge is to achieve sub-micrometre-scale accuracy whilst ensuring reliability and interpretability in environments where the ‘hallucinations’ of standard AI models must be avoided.