# Stochastic and Mixed Density Functional Theory within the projector augmented wave formalism for the simulation of warm dense matter Source: [Stochastic and Mixed Density Functional Theory within the projector augmented wave formalism for the simulation of warm dense matter]() Collection index: [llms.txt]() Data updated: 2025-10-25T05:15:13.516Z Authors: Vidushi Sharma, Lee A. Collins, Alexander J. White Published: 2023-01-27T23:04:17.000Z ## Abstract Stochastic and mixed stochastic-deterministic density functional theory (DFT) are promising new approaches for the calculation of the equation-of-state and transport properties in materials under extreme conditions. In the intermediate warm dense matter regime, a state between correlated condensed matter and kinetic plasma, electrons can range from being highly localized around nuclei to delocalized over the whole simulation cell. The plane-wave basis pseudo-potential approach is thus the typical tool of choice for modeling such systems at the DFT level. Unfortunately, the stochastic DFT methods scale as the square of the maximum plane-wave energy in this basis. To reduce the effect of this scaling, and improve the overall description of the electrons within the pseudo-potential approximation, we present stochastic and mixed DFT developed and implemented within the projector augmented wave formalism. We compare results between the different DFT approaches for both single-point and molecular dynamics trajectories and present calculations of self-diffusion coefficients of solid density carbon from 1 to 50 eV. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Radiology Report Generation on IU-Xray Findings generation v1.5 (Vicuna-7B)](): Radiology Report Generation; IU-Xray Findings generation v1.5 (Vicuna-7B); ROUGE-L: 26.3. - [Image Classification on VinDr-CXR (test)](): Image Classification; VinDr-CXR (test); AP (LO): 12.7. - [Radiology Report Generation on MIMIC-CXR v1.5 (Vicuna-7B)](): Radiology Report Generation; MIMIC-CXR Findings generation v1.5 (Vicuna-7B); ROUGE-L: 23.5. - [Image Classification on RSNA-Pneumonia 5,337 images (test)](): Image Classification; RSNA-Pneumonia 5,337 images (test); AP: 66.8. ## Original sources and implementation [Original paper]() [PDF]()