Vorabdrucke

Quantum deep learning (QDL) explores the use of both quantum and quantum-inspired resources to determine when deep learning's core capabilities, such as expressivity, generalization, and scalability, can be enhanced based on specific resource constraints. Distinct from broader quantum machine learning, QDL emphasizes compositional depth at the pipeline level and the integration of quantum or quantum-inspired components within end-to-end workflows. [...]

Superlattice engineering in van der Waals heterostructures (e.\,g.\ by moiré engineering) provides a powerful platform for designing electronic bands and realising correlated and topological quantum phenomena. Here, we pioneer a scheme to tailor superpotentials based on intrinsic substrate electronic orders. [...]

Photoemission orbital tomography (POT) is a powerful tool for investigating the orbitals and electronic band structure of oriented layers of organic molecules. In many cases, POT allows conclusions to be drawn regarding the geometric structure, but so far it has been mainly applied to (sub)monolayers and rarely to bilayers, raising the question of whether POT can also provide structure information for thicker films. [...]

Due to their high kinetic inductance, highly disordered superconducting thin films are a potential hardware for the realization of compact, low-noise elements in cryoelectronic applications. However, high disorder typically results in structural defects that cause spatial inhomogeneity of the superconducting order parameter, thereby impairing the film's properties. [...]

Foundation models increasingly offer potential to support interactive, agentic workflows that assist researchers during analysis and interpretation of image data. Such workflows often require coupling vision to language to provide a natural-language interface. [...]

End-to-end backpropagation couples all layers through a global error signal, enabling coordinated learning but requiring long-range credit assignment. Motivated by recent progress in blockwise self-supervised learning (BWSSL), we ask whether masked video transformers can be trained without end-to-end backpropagation. [...]