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Register a new userVisual Analysis of Electronic Densities and Transitions in Molecules
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Added by
Talha Bin Masood
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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The study of electronic transitions within a molecule connected to the absorption or emission of light is a common task in the process of the design of new materials. The transitions are complex quantum mechanical processes and a detailed analysis requires a breakdown of these processes into components that can be interpreted via characteristic chemical properties. We approach these tasks by providing a detailed analysis of the electron density field. This entails methods to quantify and visualize electron localization and transfer from molecular subgroups combining spatial and abstract representations. The core of our method uses geometric segmentation of the electronic density field coupled with a graph-theoretic formulation of charge transfer between molecular subgroups. The design of the methods has been guided by the goal of providing a generic and objective analysis following fundamental concepts. We illustrate the proposed approach using several case studies involving the study of electronic transitions in different molecular systems.
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The growing use of automated decision-making in critical applications, such as crime prediction and college admission, has raised questions about fairness in machine learning. How can we decide whether different treatments are reasonable or discriminatory? In this paper, we investigate discrimination in machine learning from a visual analytics perspective and propose an interactive visualization tool, DiscriLens, to support a more comprehensive analysis. To reveal detailed information on algorithmic discrimination, DiscriLens identifies a collection of potentially discriminatory itemsets based on causal modeling and classification rules mining. By combining an extended Euler diagram with a matrix-based visualization, we develop a novel set visualization to facilitate the exploration and interpretation of discriminatory itemsets. A user study shows that users can interpret the visually encoded information in DiscriLens quickly and accurately. Use cases demonstrate that DiscriLens provides informative guidance in understanding and reducing algorithmic discrimination.
We consider an electronic bound state of the usual, non-relativistic, molecular Hamiltonian with Coulomb interactions and fixed nuclei. Away from appropriate collisions, we prove the real analyticity of all the reduced densities and density matrices, that are associated to this bound state. We provide a similar result for the associated reduced current density.
Annotations in Visual Analytics (VA) have become a common means to support the analysis by integrating additional information into the VA system. That additional information often depends on the current process step in the visual analysis. For example, the data preprocessing step has data structuring operations while the data exploration step focuses on user interaction and input. Describing suitable annotations to meet the goals of the different steps is challenging. To tackle this issue, we identify individual annotations for each step and outline their gathering and design properties for the visual analysis of heterogeneous clinical data. We integrate our annotation design into a visual analysis tool to show its applicability to data from the ophthalmic domain. In interviews and application sessions with experts we asses its usefulness for the analysis of patients with different medications.
Natural language interaction with data visualization tools often involves the use of vague subjective modifiers in utterances such as show me the sectors that are performing and where is a good neighborhood to buy a house?. Interpreting these modifiers is often difficult for these tools because their meanings lack clear semantics and are in part defined by context and personal user preferences. This paper presents a system called system that makes a first step in better understanding these vague predicates. The algorithm employs word co-occurrence and sentiment analysis to determine which data attributes and filters ranges to associate with the vague predicates. The provenance results from the algorithm are exposed to the user as interactive text that can be repaired and refined. We conduct a qualitative evaluation of the Sentifiers system that indicates the usefulness of the interface as well as opportunities for better supporting subjective utterances in visual analysis tasks through natural language.
Aims. This study was designed to examine the viability of protonated nitrogen-substituted polycyclic aromatic hydrocarbons (H+PANHs) as candidates for the carriers of the diffuse interstellar bands (DIBs). Methods. We obtained the electronic spectra of two protonated PANH cations, protonated acridine and phenanthridine, using parent ion photo-fragment spectroscopy and generated theoretical electronic spectra using ab initio calculations. Results. We show that the spectra of the two species studied here do not correspond to known DIBs. However, based on the general properties derived from the spectra of these small protonated nitrogen-substituted PAHs, we propose that larger H+PANH cations represent good candidates for DIB carriers due to the expected positions of their electronic transitions in the UV-visible and their narrow spectral bands.
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