activity
20062026
most citedPhoton Antibunching from a Single Quantum Dot-Microcavity System in the Strong Coupling Regime

368 citations · 4k across the 103 of their papers we have counts for

collaborators

104 papers

cond-mat.mes-hall2026

Tunable g-Factors of Hybridized Orbitals in a Quantum Dot Molecule

Michelle Lienhart, Krzysztof Gawarecki, Pavel Daskalov +10

The ability to control the -factors of orbital spin states in optically active quantum dot molecules (QDMs) is a prerequisite for the high-fidelity generation of multi-photonic…

cond-mat.mes-hall2026

Resolving High-Energy States of Interlayer Excitons in MoSe/WSe Heterostructures

Chirag Chandrakant Palekar, Paulo E. Faria Junior, Tobias Manthei +8

High-energy states of interlayer excitons (IXs) in van der Waals heterostructures remain largely unexplored despite their importance for understanding many-body interactions and no…

physics.optics2026

An integrated all-van der Waals nanobeam laser

Aris Koulas-Simos, Pietro Metuh, Athanasios Paralikis +7

Transition-metal dichalcogenides offer a promising platform for integrated coherent light sources, yet lasing has largely relied on hybrid photonic architectures without direct qua…

cond-mat.mtrl-sci2026

Anisotropic nanoscale coherent polariton transport in CrSBr

Paritosh Malik, Dogyun Ko, Vita Solovyeva +11

In a combined experimental and theoretical study, we demonstrate anisotropic polariton transport on the nanoscale in the van der Waals antiferromagnet CrSBr. While effective cavity…

cond-mat.mes-hall2026

Energy-time entanglement from a monolithically integrated quantum dot on silicon

Marcel Hohn, Imad Limame, Peter Ludewig +4

Scalable quantum photonic technologies require deterministic sources of entangled photons that are compatible with established semiconductor manufacturing platforms. While self-ass…

cs.ET2026

Power law scaling for classification accuracy in physical neural networks

Andrei V. Ermolaev, Mathilde Hary, Anas Skalli +7

Physical neural networks (PNNs) harness the intrinsic complexity of physical systems to perform neural computation, potentially at speeds and energy efficiencies inaccessible to co…