DeepPolaron ML-MD simulations show rutile electrons form Ti-localized polarons hopping along [001] with 39 meV barrier and 4.4e-2 cm2/Vs mobility, while anatase holes form O-localized polarons hopping to second neighbors with 139 meV barrier and 1.4e-3 cm2/Vs mobility.
Science321(5890), 792–794 (2008),https://www.science
7 Pith papers cite this work, alongside 2,523 external citations. Polarity classification is still indexing.
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Constraint-aware neural networks clone known semilocal XC functionals more accurately in self-consistent calculations, transfer well from molecules to solids, and outperform unconstrained models across multiple tests.
Hybrid QSCI method with LCNot-UCCSD ansatz and RBM-based configuration recovery enables NISQ-era molecular simulations, demonstrated on small molecules and DMET-embedded protein-ligand systems.
ibDET allows dense Brillouin-zone sampling in EOM-CCSD, cutting finite-size errors and yielding 0.27 eV MAE to experimental band gaps on ten semiconductors and insulators.
Necessary and sufficient conditions are established for the N-representability of the universal one-electron reduced density matrix functional, guaranteeing variational upper bounds on the true energy regardless of interparticle repulsion strength.
A three-axis taxonomy (intervention level, functional role, hardware regime) organizes hybrid quantum-classical DFT approaches and points to embedding-on-NISQ as the near-term path.
Orbital-optimized DFT is surveyed as a variational, state-specific alternative to TDDFT for balanced treatment of diverse molecular electronic excitations.
citing papers explorer
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Polaron Transport in TiO$_{2}$ from Machine Learning Molecular Dynamics
DeepPolaron ML-MD simulations show rutile electrons form Ti-localized polarons hopping along [001] with 39 meV barrier and 4.4e-2 cm2/Vs mobility, while anatase holes form O-localized polarons hopping to second neighbors with 139 meV barrier and 1.4e-3 cm2/Vs mobility.
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Constraint-aware functional cloning for stable and transferable machine-learned density functional theory
Constraint-aware neural networks clone known semilocal XC functionals more accurately in self-consistent calculations, transfer well from molecules to solids, and outperform unconstrained models across multiple tests.
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Bridging the NISQ and Fault-Tolerant Regimes: Generative-ML-Assisted Quantum Selected CI for Molecular Simulations
Hybrid QSCI method with LCNot-UCCSD ansatz and RBM-based configuration recovery enables NISQ-era molecular simulations, demonstrated on small molecules and DMET-embedded protein-ligand systems.
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Resolving Finite-Size Errors in EOM-CCSD Band Gaps of Solids with Interacting-Bath Dynamical Embedding Theory
ibDET allows dense Brillouin-zone sampling in EOM-CCSD, cutting finite-size errors and yielding 0.27 eV MAE to experimental band gaps on ten semiconductors and insulators.
-
Necessary and sufficient conditions for the N-representability of functionals of the one-electron reduced density matrix
Necessary and sufficient conditions are established for the N-representability of the universal one-electron reduced density matrix functional, guaranteeing variational upper bounds on the true energy regardless of interparticle repulsion strength.
-
Hybrid Quantum-Classical Density Functional Theory: A Structured Framework
A three-axis taxonomy (intervention level, functional role, hardware regime) organizes hybrid quantum-classical DFT approaches and points to embedding-on-NISQ as the near-term path.
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Orbital-optimized density functional calculations of excited electronic states: Recent advances and perspectives
Orbital-optimized DFT is surveyed as a variational, state-specific alternative to TDDFT for balanced treatment of diverse molecular electronic excitations.