The paper proposes a three-axis framework to organize hybrid quantum-classical DFT approaches and shows embedding methods suit current noisy hardware better than linear algebra speedups.
Reviews of Modern Physics 87(3), 897–923 (2015)
6 Pith papers cite this work. Polarity classification is still indexing.
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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.
Hybrid QM/ML forcefield framework couples DFT with MLIPs to enable scalable, chemically accurate simulations of solute-dislocation interactions, demonstrated on Sn/Fe segregation in Zr and magnetic effects in steel.
Exact force fields are variationally induced from DFT by pulling back the energy functional, density, and response function from external potential space to nuclear positions.
SALMON 2.3 implements divide-and-conquer DFT ground-state initialization with orbital reconstruction, achieving linear scaling and enabling real-time TDDFT on systems up to 4134 atoms.
Phase-space kinetic modeling with distribution function f(r,p,t) is applied to solid-state plasmas in nano-objects, adding quantum, spin, relativistic and dissipative features for linear and nonlinear response examples.
citing papers explorer
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Hybrid Quantum-Classical Density Functional Theory: A Structured Framework
The paper proposes a three-axis framework to organize hybrid quantum-classical DFT approaches and shows embedding methods suit current noisy hardware better than linear algebra speedups.
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TSAgent: An Agentic Workflow for Autonomous Transition State Search
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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A Hybrid Quantum Mechanics Machine Learning Forcefield (QM/ML) Framework for Accurate Solute-Dislocation Interaction Simulations
Hybrid QM/ML forcefield framework couples DFT with MLIPs to enable scalable, chemically accurate simulations of solute-dislocation interactions, demonstrated on Sn/Fe segregation in Zr and magnetic effects in steel.
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A density-functional perspective on force fields
Exact force fields are variationally induced from DFT by pulling back the energy functional, density, and response function from external potential space to nuclear positions.
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SALMON 2.3: Implementation of divide-and-conquer ground-state initialization for large-scale real-time TDDFT
SALMON 2.3 implements divide-and-conquer DFT ground-state initialization with orbital reconstruction, achieving linear scaling and enabling real-time TDDFT on systems up to 4134 atoms.
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Phase-space modelling of solid-state plasmas
Phase-space kinetic modeling with distribution function f(r,p,t) is applied to solid-state plasmas in nano-objects, adding quantum, spin, relativistic and dissipative features for linear and nonlinear response examples.