Modified LAPW approach reaches Hartree-Fock limit total energies for solids and molecules at few μHa precision by constructing basis functions consistently with the HF Hamiltonian.
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LADeQ is an LLM-driven workflow that autonomously discovers and implements approximation algorithms for CCSD and CISD calculations, delivering speedups while respecting user-specified error tolerances.
Equilibrium quantum many-body methods are encoders from admissible states to represented variables, with exact decoders existing precisely when tasks are constant on encoder fibers.
BN doping renders the planar-to-Dewar isomerization asymmetric via a B-C stabilized metastable intermediate whose transition state resembles an S0/S1 conical intersection, and targeted substitution red-shifts S1 while boosting oscillator strength and Dewar yield.
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.
A new polarizable QM/MM method for periodic systems uses SCME for water with multipoles up to hexadecapole and anisotropic polarizabilities, achieving full QM accuracy via careful near/far-field expansions and damping.
MR-SCDFT augments standard multireference DFT by using stochastic fields to create reference configurations and a projection-selection step, yielding lower ground-state energies, smaller proton radii, and softer bands than conventional MR-CDFT for 20Ne, 24Mg, and 28Si.
AQVolt26 is a new high-temperature halide dataset that improves universal ML interatomic potentials for distorted configurations while showing that near-equilibrium relaxation data is not universally helpful.
OrbEvo uses equivariant graph transformers to learn the time evolution of TDDFT wavefunction coefficients, accurately reproducing wavefunctions, dipole moments, and absorption spectra on QM9 and MD17 molecular datasets.
Skala is a neural XC functional trained on wavefunction data that beats state-of-the-art hybrids on main-group chemistry benchmarks at semi-local computational cost.
Bulk boundary conditions plus density-matrix locality let Kohn–Sham DFT compute surface and adsorption energies on a localized surface domain that matches slab accuracy.
Using modified Hartree-Fock pseudopotentials for Cu core electrons eliminates propagated density errors, yielding accurate bandgaps and lattice constants across 50+ Cu semiconductors.
Flat bands near the Fermi level observed in noncentrosymmetric type-II Weyl semimetal TaRhTe4 by ARPES, not predicted by DFT calculations.
MALOQ introduces a scalable SO(2)-equivariant ML framework with custom kernels and edge-wise graph distribution for predicting large-scale quantum transport operators.
A Stoner-inspired preconditioner based on non-interacting susceptibility that neglects orbital variations reduces SCF iterations in magnetic KS-DFT near phase transitions.
Clifford disentanglers classified by Schmidt spectrum action reduce energy errors at fixed bond dimension in MPS simulations of molecules and improve shallow-circuit VQE calculations.
Interfacial energetics computed with machine-learned potentials explain why Mn addition switches grain-boundary precipitates in Cu-Ni-Si alloys from irregular Ni2Si to film-shaped Mn6Ni16Si7.
COO co-optimizes orbitals with TrimCI to absorb many-body correlations into the basis, cutting determinant count by orders of magnitude for iron-sulfur clusters versus localized bases or DMRG.
UniField fuses discrete atomic graphs with continuous electron density fields via RBF guidance in an SE(3)-equivariant multimodal model, reporting new SOTA results on QM9-ED, QMugs-ED, and ED5-OE benchmarks with gains up to 37%.
TSAgent automates transition state searches at DFT accuracy via an agentic loop, reaching 83% success on 100 OC20NEB examples and 70% on 10 held-out cases versus 73% for human experts.
Nanostructure geometry on suspended van der Waals membranes provides deterministic control of multiaxial strain and bandgap profiles in 2D materials like Ga2Se2, with a two-component analytical model predicting shifts to within 12% error and extendable to other materials.
Neural networks represent densities in a variational extended Thomas-Fermi model, yielding binding energies within 0.5% of prior ETF results and reproducing nuclear pasta phases.
The paper establishes an exact N-centered ensemble DFT formalism unifying neutral and charged excitations and introduces three practical strategies: weight-dependent scaling of ground-state functionals, quasi-degenerate ensemble perturbation theory, and quantum bath embedding for excited states.
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Modified LAPW approach reaches Hartree-Fock limit total energies for solids and molecules at few μHa precision by constructing basis functions consistently with the HF Hamiltonian.
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BN doping renders the planar-to-Dewar isomerization asymmetric via a B-C stabilized metastable intermediate whose transition state resembles an S0/S1 conical intersection, and targeted substitution red-shifts S1 while boosting oscillator strength and Dewar yield.
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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.
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Polarizable Embedding QM/MM for Periodic Systems
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Multireference Covariant Density Functional Theory with Stochastic Basis
MR-SCDFT augments standard multireference DFT by using stochastic fields to create reference configurations and a projection-selection step, yielding lower ground-state energies, smaller proton radii, and softer bands than conventional MR-CDFT for 20Ne, 24Mg, and 28Si.
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AQVolt26: High-Temperature r$^2$SCAN Halide Dataset for Universal ML Potentials and Solid-State Batteries
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Bulk Boundary Condition for Surface Calculations in Density Functional Theory
Bulk boundary conditions plus density-matrix locality let Kohn–Sham DFT compute surface and adsorption energies on a localized surface domain that matches slab accuracy.
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Minimizing propagated density errors of atomic core-electron for simultaneously accurate bandgaps and lattice constants in closed-shell Copper semiconductors
Using modified Hartree-Fock pseudopotentials for Cu core electrons eliminates propagated density errors, yielding accurate bandgaps and lattice constants across 50+ Cu semiconductors.
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Observation of Flat Bands in Type-II Weyl Semimetal TaRhTe$_{4}$
Flat bands near the Fermi level observed in noncentrosymmetric type-II Weyl semimetal TaRhTe4 by ARPES, not predicted by DFT calculations.
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MALOQ: Massively Accelerated Learning of Operators for Quantum Transport
MALOQ introduces a scalable SO(2)-equivariant ML framework with custom kernels and edge-wise graph distribution for predicting large-scale quantum transport operators.
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Preconditioning Magnetic Systems in Kohn-Sham Density Functional Theory
A Stoner-inspired preconditioner based on non-interacting susceptibility that neglects orbital variations reduces SCF iterations in magnetic KS-DFT near phase transitions.
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UniField fuses discrete atomic graphs with continuous electron density fields via RBF guidance in an SE(3)-equivariant multimodal model, reporting new SOTA results on QM9-ED, QMugs-ED, and ED5-OE benchmarks with gains up to 37%.
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TSAgent automates transition state searches at DFT accuracy via an agentic loop, reaching 83% success on 100 OC20NEB examples and 70% on 10 held-out cases versus 73% for human experts.
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