arXiv subjects

Idan Cohen

Publications and source records attributed to Idan Cohen.

3 recordsLinked to original sources

arXiv2026

Localized Exciton Emission with Spontaneous Circular Polarization in NiPS3/WSe2 Heterostructures

Two-dimensional (2D) van der Waals (vdW) heterostructures (HSs) provide a versatile platform for tailoring electronic, optical, and magnetic properties via proximity effects at their interfaces. In this work, we explore the optical response of few-layer NiPS3/WSe2 HSs using low-temperature micro-photoluminescence ({\mu}-PL) and magneto-PL spectroscopy. The HSs exhibit multiple sharp excitonic peaks that do not appear in the individual constituent materials, indicating the emergence of localized intralayer WSe2 excitons confined by interface-induced potentials. Notably, these excitons exhibit spontaneous circular polarization even in the absence of an external magnetic field, suggesting a magnetic proximity effect induced by uncompensated spins at the NiPS3 interface. Magneto-PL measurements further reveal nonlinear Zeeman splitting, consistent with the presence of an interfacial exchange field that alters the valley exciton dynamics. Density functional theory (DFT) calculations confirm the intralayer origin of the PL and reveal interfacial hybridization and spin texture modifications, supporting the experimental findings. These results highlight how combining a 2D semiconductor with a layered antiferromagnet enables control over valley polarization and spin degrees of freedom, offering new opportunities for chiral light sources and magnetically tunable optoelectronic devices.

cond-mat.mtrl-sci↗

arXiv2024

Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction

Classical methods for acoustic scene mapping require the estimation of time difference of arrival (TDOA) between microphones. Unfortunately, TDOA estimation is very sensitive to reverberation and additive noise. We introduce an unsupervised data-driven approach that exploits the natural structure of the data. Our method builds upon local conformal autoencoders (LOCA) - an offline deep learning scheme for learning standardized data coordinates from measurements. Our experimental setup includes a microphone array that measures the transmitted sound source at multiple locations across the acoustic enclosure. We demonstrate that LOCA learns a representation that is isometric to the spatial locations of the microphones. The performance of our method is evaluated using a series of realistic simulations and compared with other dimensionality-reduction schemes. We further assess the influence of reverberation on the results of LOCA and show that it demonstrates considerable robustness.

eess.AS↗

arXiv2015

Forecasting the Israeli 2015 elections using a smartphone application

We developed a smartphone application, Ha'Midgam, to poll and forecast the results of the 2015 Israeli elections. The application was downloaded by over 7,500 people. We present the method used to control bias in our sample and our forecasts. We discuss limitations of our approach and suggest possible solutions to control bias in similar applications.

stat.AP↗