arXiv (All)
open access
PEACE: Covariant learning of nonadiabatic manifolds with parity-resolved Hamiltonians
Nonadiabatic molecular dynamics provides mechanistic insight into light-driven processes and informs the design of molecules and materials for solar energy conversion, photocatalysis and photo switching. Accurately describing these processes requires a representation that respects electronic symmetr
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Robustness and reliability of different CASPT2 flavors for nonadiabatic molecular dynamics#1218971
- Cartesian and Curvilinear Anharmonic Frequencies and Intensities: Perturb-then-Diagonalize Polyad Transport and Adiabatic Discrete-Variable Representation#1355408
- Enhancing molecular dynamics with equivariant machine-learned densities#138927
- Data-Driven Free-Energy Learning from Trajectories via Structure-Preserving Exponential Time Differencing#1249211
- Functional Morphology of Moral Patiency: A Continuous-Time Measure-Theoretic Framework for Synthetic Sentience#725814
Record · ID 1233615
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive