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From the 1 of 6 linked papers with an AI index.

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6 papers

physics.ed-ph2026

From Prompt to Embodied Simulation: Using Generative AI to Create AR Physics Learning Tools

Ofek Levy, Joshua Glazer, Noah D. Finkelstein +1

Spread your thumb and index finger in the air, and a virtual lamp in the room changes color. Computer simulations have a long and well-documented record of supporting physics learn…

physics.chem-ph2026

Macroscopic Spin-Orbit Interaction through Strong-Field Pumping of Inhomogeneously Aligned Molecular Ensemble

Uriel Zanzuri, Sharly Fleischer, Tamar Seideman +3

The paper investigates how a helical bi‑chromatic strong‑field pump interacting with a radially aligned molecular ensemble generates high‑harmonic radiation that carries orbital an…

astro-ph.HE2026

Discovery of 30 Repeating Fast Radio Burst Sources and Uniform Population Statistics of 80 Repeating Sources from CHIME/FRB

Amanda M. Cook, Kaitlyn Shin, Ziggy Pleunis +44

We present 30 newly discovered repeating fast radio burst (FRB) sources from the second catalog of bursts detected by the FRB backend on the Canadian Hydrogen Intensity Mapping Exp…

physics.ed-ph2026

From Search to GenAI Queries: Global Trends in Physics Information-Seeking Across Topics and Regions

Yossi Ben-Zion, Omer Michaeli, Noah D. Finkelstein

The emergence of generative artificial intelligence (GenAI) marks a potential inflection point in the way academic information is accessed, raising fundamental questions about the…

cond-mat.mtrl-sci2025

Composition/structure directed search for new chalcogenide compounds

Alon Hever, Ohad Levy, Stefano Curtarolo +1

This work presents a simple scheme for finding new crystalline compounds by adapting structure types from neighbor atoms compounds. The approach is demonstrated for the selenide an…

physics.chem-ph2025

Black-Box Uncertainty Estimation for Deep Learning Models in Atomistic Simulations

Idan Fonea, Amir Peles, Sivan Niv +2

We analyze an ensemble-based approach for uncertainty quantification (UQ) in atomistic neural networks. This method generates an epistemic uncertainty signal without requiring chan…