Trending Research
Crystal Structure Generation with Autoregressive Large Language Modeling
Quickly generating and predicting inorganic crystal structures is important for the discovery of new materials, which can target applications such as energy or electronic devices.
Materials Science
Digital Discovery of a Scientific Concept at the Core of Experimental Quantum Optics
Second, our manuscript demonstrates how artificial intelligence can act as a source of inspiration for the scientific discoveries of new actionable concepts in physics.
Quantum Physics
ViSNet: an equivariant geometry-enhanced graph neural network with vector-scalar interactive message passing for molecules
microsoft/AI2BMD
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Geometric deep learning has been revolutionizing the molecular modeling field.
Chemical Physics Biomolecules Quantum Physics
PyPSA: Python for Power System Analysis
In this paper the basic functionality of PyPSA is described, including the formulation of the full power flow equations and the multi-period optimisation of operation and investment with linear power flow equations.
Physics and Society
doped: Python toolkit for robust and repeatable charged defect supercell calculations
Defects are a universal feature of crystalline solids, dictating the key properties and performance of many functional materials.
Materials Science Chemical Physics Computational Physics
Urban Mobility
In this chapter, we discuss urban mobility from a complexity science perspective.
Physics and Society Computers and Society
HepLean: Digitalising high energy physics
We introduce HepLean, an open-source project to digitalise definitions, theorems, proofs, and calculations in high energy physics using the interactive theorem prover Lean 4.
High Energy Physics - Phenomenology Logic in Computer Science High Energy Physics - Theory
Discovery of highly anisotropic dielectric crystals with equivariant graph neural networks
Anisotropy in crystals plays a pivotal role in many technological applications.
Materials Science
Hybrid quantum programming with PennyLane Lightning on HPC platforms
We introduce PennyLane's Lightning suite, a collection of high-performance state-vector simulators targeting CPU, GPU, and HPC-native architectures and workloads.
Quantum Physics Distributed, Parallel, and Cluster Computing Emerging Technologies Computational Physics
Towards an exact electronic quantum many-body treatment of Kondo correlation in magnetic impurities
The Kondo effect is a prototypical quantum phenomenon arising from the interaction between localized electrons in a magnetic impurity and itinerant electrons in a metallic host.
Strongly Correlated Electrons Materials Science Chemical Physics Computational Physics
