The Perceptually Accurate Visual Display of Quantitative Quantum Physics Data

Abstract

The rise of data-driven quantum physics has motivated the use of data visualization to communicate data and explore insights to users. In contrast to raw data, visual representations are more expressive and can communicate more information. The pervasive and effective uses of visualization are supposed to improve the scientific process and let users easily inspect data produced from experiments and simulations. A critical feature is perceptually accurate exploration that provides accurate interpretations of patterns in response to users’ input. This form of representation is crucial for viewers searching for patterns or answering domain questions to test domain hypotheses accurately. Due to the increasing complexity (size and density) of modern quantum physics simulation results, there is a lack of design guidelines for quantum physicists to explore complex data. In this dissertations, we design and evaluate visualization methods step by step for comprehensive understanding of quantum physics simulation results. We start with designing more accurate data representation for legibility of single point. Built from our design and experimental results, we further present a series of experiments to better support tasks involving multiple points. We finally present visualization tools by integrating design guidelines derived from our experiments and other interfaces for visual query of quantum physics data in both desktop and virtual environments. The first contribution in this dissertations work is a novel visual representation called SplitVectors that support conveying large-range magnitudes in quantum physics simulation results accurately. This is an important problem as many simulation results have large-range data. Our design dramatically improved the visual discrimination of vectors in space and achieved up to 10 times better accuracy compared to the traditional linear representation. The second contribution of this dissertations work is to advance visual guidance in bivariate glyph visualization design inspired by latest theories in vision science. Built from SplitVectors, we investigated visual encodings as well as viewers’ behaviors for visual searching of a chunk of items. Our work reveals that color and texture are the most useful to guide quantum physicists’ tasks of seeing from a large chuck of items. We also conducted an eye-tracking experiment to understand viewers’ behaviors and the use of scene guidance in the searching of multiple points. Our experiment revealed two intriguing strategies that viewers used when searching for items from hundreds of similar items. Viewers used the global distribution (gist of the scene) even without knowing the individual item and were able to restrict the eye movement to the task-relevant regions - we called them drillers. Drillers had less trial errors, and categorical colors allowed more drillers thus made a more effective display. The third contribution of this work is that we apply searching and comparison-oriented strategies and couple two-dimensional (2D) displays and 3D spatial data in a "world-inworld” environment to guide interactive queries of many tasks. Our studies yield insights that could lead to improved design for integrating 2D and 3D solutions for complex multiscale data analyses. We demonstrate the use of our concepts in both desktop and immersive virtual environment settings. These tools have been successfully delivered to quantum physicists at National Institute of Standards and Technology (NIST).