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Visualizing Cosmological Time

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Part of the book series: The Springer International Series in Engineering and Computer Science ((SECS,volume 713))

Abstract

Time is a critical aspect of visualization systems that invoke dynamic simulations and animation. Dealing with time at the scales required to conceptualize astrophysical and cosmological data, however, introduces specialized problems that require unique approaches. In this paper, we extend our previous investigations on interactive visualization across extremely large scale ranges of space to incorporate dynamical processes with very large scale ranges of time. We focus on several issues: time scales that are too short or too long to animate in real time, those needing complex adjustment relative to the scale of space, time simulations that involve the constant finite velocity of light (special relativity) in an essential way, and those that depend upon the dynamics of the coordinate system of the universe itself (general relativity). We conclude that a basic strategy for time scaling should ordinarily track the scaling of space chosen for a particular problem; e.g., if we are adjusting the interactive space scale, we scale time in a similar way. At cosmological scales, this has the interesting consequence that the time scale adjusts to the size of each era of the universe. If we make a single tick of the viewer’s clock correspond to an enormous time when viewing an enormous space, we see motions in viewer’s time of increasingly larger, and usually appropriate, scales. Adding interactive time-scale controls then permits the user to switch the focus of attention among animations with distinctly different time features within a single spatial scale. Objects may have an entire time hierarchy of alternate icons, with different representations for different time-step scales, exactly analogous to the choice of spatial level-of-detail models.

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Hanson, A.J., Fu, CW., Wernert, E.A. (2003). Visualizing Cosmological Time. In: Post, F.H., Nielson, G.M., Bonneau, GP. (eds) Data Visualization. The Springer International Series in Engineering and Computer Science, vol 713. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1177-9_29

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  • DOI: https://doi.org/10.1007/978-1-4615-1177-9_29

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-5430-7

  • Online ISBN: 978-1-4615-1177-9

  • eBook Packages: Springer Book Archive

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