Interactive Exploration of Cosmological Dark-Matter Simulation Data

Scherzinger, Aaron; Brix, Tobias; Drees, Dominik; Volker, Andreas; Radkov, Kiril; Santalidis, Niko; Fieguth, A.; Hinrichs, Klaus

doi:10.1109/mcg.2017.20

Cited by 9 publications

(10 citation statements)

References 5 publications

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“…Most of the current time series data visualizations are built to display halo evolution. One common technique is to use a merger tree to visualize the development of halos over time [SXL∗14, AF15, PGX∗16, SBD∗17]. Other techniques are often used along with the merger tree to enhance the effectiveness of the visualization.…”

Section: Challenges and Opportunitiesmentioning

confidence: 99%

“…Scherzinger et al . [SBD∗17] proposed a unified visualization tool based on Voreen [MSRMH09] that supports the interactive exploration of multiple data layers contained within dark matter simulations. These simulations contain only dark matter particles, in contrast to also including gas and stars.…”

Section: Data Explorationmentioning

confidence: 99%

“…Scherzinger et al . [SBD∗17] extended their framework by adding particle visualization and analysis for individual halos.…”

Section: Challenges and Opportunitiesmentioning

confidence: 99%

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Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, and Educating the Earth

Lan

Young

Anderson

et al. 2021

Computer Graphics Forum

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We present a state‐of‐the‐art report on visualization in astrophysics. We survey representative papers from both astrophysics and visualization and provide a taxonomy of existing approaches based on data analysis tasks. The approaches are classified based on five categories: data wrangling, data exploration, feature identification, object reconstruction, as well as education and outreach. Our unique contribution is to combine the diverse viewpoints from both astronomers and visualization experts to identify challenges and opportunities for visualization in astrophysics. The main goal is to provide a reference point to bring modern data analysis and visualization techniques to the rich datasets in astrophysics.

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Section: Challenges and Opportunitiesmentioning

confidence: 99%

Section: Data Explorationmentioning

confidence: 99%

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Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, and Educating the Earth

Lan

Young

Anderson

et al. 2021

Computer Graphics Forum

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“…Visual analytics tools have been used to explore simulation data that model the evolution of the Universe [HPU*15,PGX*16]. Almryde and Forbes [AF15] introduce an interactive web application to visualize “traces” of dark matter halos as they move in relation to each other over time, and Scherzinger et al [SBD*17] present an innovative application that provides 2D and 3D views to support the analysis of halo substructures and hierarchies. IGM‐Vis also provides a visual analytics dashboard comprised of integrated panels [DMF17, FBL*18, MFL*16, SCB*19], facilitating a workflow supporting IGM/CGM identification, analysis, and presentation tasks.…”

Section: Background and Related Workmentioning

confidence: 99%

IGM‐Vis: Analyzing Intergalactic and Circumgalactic Medium Absorption Using Quasar Sightlines in a Cosmic Web Context

Burchett

Abramov

Otto

et al. 2019

Computer Graphics Forum

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We introduce IGM‐Vis, a novel astrophysics visualization and data analysis application for investigating galaxies and the gas that surrounds them in context with their larger scale environment, the Cosmic Web. Environment is an important factor in the evolution of galaxies from actively forming stars to quiescent states with little, if any, discernible star formation activity. The gaseous halos of galaxies (the circumgalactic medium, or CGM) play a critical role in their evolution, because the gas necessary to fuel star formation and any gas expelled from widely observed galactic winds must encounter this interface region between galaxies and the intergalactic medium (IGM). We present a taxonomy of tasks typically employed in IGM/CGM studies informed by a survey of astrophysicists at various career levels, and demonstrate how these tasks are facilitated via the use of our visualization software. Finally, we evaluate the effectiveness of IGM‐Vis through two in‐depth use cases that depict real‐world analysis sessions that use IGM/CGM data.

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“…S CIENTIFIC visualization is an essential instrument of modern scientific computing, as it helps to discover new insights, which include the role of dark matter in the formation of galaxies [50], oceanic currents that drive the global climate [60], the neurological pathways in our brain [5], as well as the treatment of impaired blood flow in our veins [48], to name a few. Due to the increasing availability of powerful computational resources and the improvements in measurement technologies, the available data grows rapidly in all scientific disciplines.…”

Section: Introductionmentioning

confidence: 99%

Fourier Opacity Optimization for Scalable Exploration

Rojo

Groß

Günther

2020

IEEE Trans. Visual. Comput. Graphics

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Over the past decades, scientific visualization became a fundamental aspect of modern scientific data analysis. Across all data-intensive research fields, ranging from structural biology to cosmology, data sizes increase rapidly. Dealing with the growing large-scale data is one of the top research challenges of this century. For the visual exploratory data analysis, interactivity, a view-dependent visibility optimization and frame coherence are indispensable. In this work, we extend the recent decoupled opacity optimization framework to enable a navigation without occlusion of important features through large geometric data. By expressing the accumulation of importance and optical depth in Fourier basis, the computation, evaluation and rendering of optimized transparent geometry become not only order-independent, but also operate within a fixed memory bound. We study the quality of our Fourier approximation in terms of accuracy, memory requirements and efficiency for both the opacity computation, as well as the order-independent compositing. We apply the method to different point, line and surface data sets originating from various research fields, including meteorology, health science, astrophysics and organic chemistry.

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Interactive Exploration of Cosmological Dark-Matter Simulation Data

Cited by 9 publications

References 5 publications

Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, and Educating the Earth

Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, and Educating the Earth

IGM‐Vis: Analyzing Intergalactic and Circumgalactic Medium Absorption Using Quasar Sightlines in a Cosmic Web Context

Fourier Opacity Optimization for Scalable Exploration

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