EDP: a program for projecting electron densities from VASP onto planes

The electron density is a fundamental concept in electronic structure calculations, as it provides a detailed description of the distribution of electrons in a material or molecule. In many electronic structure methods, the electron density is used as the basic quantity from which other properties such as the energy, potential, and forces can be derived. The electron density provides insight into chemical bonding and reactivity and understanding the electron density (and its redistribution upon chemical bond breaking or formation) is crucial for predicting and interpreting the properties of materials and molecules. The electron density is a scalar field, which means that it is a function that assigns a scalar value to each point in space. In the case of the electron density, this scalar value represents the probability density of finding an electron at that point in space. Specialized visualization tools and techniques are often required to effectively visualize scalar fields such as the electron density. These tools may include contour plots, isosurface rendering, and volume rendering, among others. Visualizing the electron density is essential for gaining insights into the electronic properties and behavior of materials and molecules. EDP is a C++-based command-line utility designed to perform the projection of the electron density scalar field onto a plane. Subsequently, this plane is rendered onto a canvas using a color map and stored as a PNG file

biaslab/RxInfer.jl: v2.10.1

RxInfer v2.10.1 Diff since v2.10.0 Merged pull requests: JOSS submission (#45) (@bvdmitri) update benchmarks with new versions of packages (#91) (@bvdmitri

biaslab/RxInfer.jl: v2.10.2

RxInfer v2.10.2 Diff since v2.10.1 Merged pull requests: Small fix to example based on John-Boik's last catch. (#89) (@wmkouw) paper: fix doi for the Julia paper (#92) (@bvdmitri) Remove PyPlot dependency in the examples (#93) (@bvdmitri

Taking a Disagreeing Perspective Improves the Accuracy of People’s Quantitative Estimates

Many decisions rest on people’s ability to make estimates of unknown quantities. In these judgments, the aggregate estimate of a crowd of individuals is often more accurate than most individual estimates. Remarkably, similar principles apply when multiple estimates from the same person are aggregated, and a key challenge is to identify strategies that improve the accuracy of people’s aggregate estimates. Here, we present the following strategy: Combine people’s first estimate with their second estimate, made from the perspective of someone they often disagree with. In five preregistered experiments (N = 6,425 adults; N = 53,086 estimates) with populations from the United States and United Kingdom, we found that such a strategy produced accurate estimates (compared with situations in which people made a second guess or when second estimates were made from the perspective of someone they often agree with). These results suggest that disagreement, often highlighted for its negative impact, is a powerful tool in producing accurate judgments

Minimisation of Spatial Models using Branching Bisimilarity - Validation code and data

This code runs the experimental validation for the paper: Title: Minimisation of Spatial Models using Branching Bisimilarity Authors: Vincenzo Ciancia, Jan Friso Groote, Diego Latella, Mieke Massink and Erik P. de Vink FORMAL METHODS 2023 See https://fm2023.isp.uni-luebeck.de This repository is obtained by using "git archive" of the main branch with tag "zenodo-FM2023" of the repository: https://github.com/VoxLogicA-Project/FM2023-Validation Please visit the repository for updates

Reaction-coordinate driven Kohn-Sham orbital characterisation for CO adsorption trajectories source code

Bachelor End Project source code. This includes files for automated DFT calculations and their visualization. The final products are videos showing the change of DOS and COHP for linear adsorption trajectories for CO