Science

A new benchmarking framework promises to accelerate the development of AI models capable of discovering stable and diverse inorganic crystalline materials.

Researchers have developed a new model capable of intelligently processing Earth observation data from diverse sources and resolutions, paving the way for more adaptable and insightful environmental monitoring.

A new approach using multiphoton interference significantly improves the accuracy of determining the indistinguishability of single photons, paving the way for more precise quantum sensing and computation.

Researchers have refined control protocols to enable high-fidelity iSWAP gates using dipolar interactions between neutral atom qubits, unlocking new possibilities for scalable quantum computation.

A new method uses neural networks to accurately simulate the thermal states of interacting fermions, opening doors to studying complex quantum systems.

New research explores how to verify information security in complex cyber-physical systems where both timing and energy resources are critical.

A new framework, TaskEval, offers a scalable solution to the challenge of consistently and accurately assessing the performance of large AI models across diverse tasks.

Researchers have significantly enhanced the sensitivity of quantum-based radio frequency receivers by focusing signals onto a vapor cell using a custom-designed metamaterial lens.

New simulations and machine learning techniques are refining our understanding of dark matter’s distribution within our galaxy, paving the way for more sensitive direct detection experiments.

New research explores the surprising potential for amplifying a fragile quantum property, and defines the boundaries of its enhancement under realistic constraints.