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.
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A Stoner-inspired preconditioner based on non-interacting susceptibility that neglects orbital variations reduces SCF iterations in magnetic KS-DFT near phase transitions.
Analyzes convergence rates of Tseng's splitting method and two accelerated schemes for monotone inclusion problems with sum of Hölder continuous operators.
PESCA is a self-consistent electrostatic model for semiconductors in devices whose accuracy is controlled by the small ratio κ = C_g/C_q ≈ 1%.
citing papers explorer
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LLM-Guided Test-Time Discovery of Quantum-Chemical Approximation Algorithms
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.
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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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Convergence Rates of Tseng's Splitting Method and Its Acceleration Schemes for Monotone Inclusion Problem with a Sum of H\"older Continuous Operators
Analyzes convergence rates of Tseng's splitting method and two accelerated schemes for monotone inclusion problems with sum of Hölder continuous operators.
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Electrostatics in semiconducting devices I : The Pure Electrostatics Self Consistent Approximation
PESCA is a self-consistent electrostatic model for semiconductors in devices whose accuracy is controlled by the small ratio κ = C_g/C_q ≈ 1%.