Quantum machines, new materials, and the universe at every scale.
arXiv
Verdict: NotableUnderstanding phase stability and navigating vast compositional spaces in multicomponent solids remain central challenges in solid-state chemistry.
Universal machine-learning interatomic potentials now reach held-out energy and force errors so small that they no longer predict how a model behaves in simulation.
The local effect of an interstitial hydrogen-like particle on localized f electrons was studied in PrPb 3 by means of μ + spin rotation and relaxation.
Multipartite systems of high-dimensional particles can host forms of quantum entanglement inaccessible to qubit systems.
Achieving high-fidelity and robust qubit manipulations is a crucial requirement for realizing faulttolerant quantum computation.
On-device machine learning is increasingly important in applications where extreme data rates or resource constraints make centralized processing infeasible.
The microquasar V4641 Sagittarii (V4641 Sgr) has recently been established as one of the most powerful Galactic PeV cosmic-ray accelerators (PeVatrons) through the detection of ....