Tag Archives: Graphics

Monte Carlo Physarum Machine: Characteristics of Pattern Formation in Continuous Stochastic Transport Networks [CEA]

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http://arxiv.org/abs/2204.01256


We present Monte Carlo Physarum Machine: a computational model suitable for reconstructing continuous transport networks from sparse 2D and 3D data. MCPM is a probabilistic generalization of Jones’s 2010 agent-based model for simulating the growth of Physarum polycephalum slime mold. We compare MCPM to Jones’s work on theoretical grounds, and describe a task-specific variant designed for reconstructing the large-scale distribution of gas and dark matter in the Universe known as the Cosmic web. To analyze the new model, we first explore MCPM’s self-patterning behavior, showing a wide range of continuous network-like morphologies — called “polyphorms” — that the model produces from geometrically intuitive parameters. Applying MCPM to both simulated and observational cosmological datasets, we then evaluate its ability to produce consistent 3D density maps of the Cosmic web. Finally, we examine other possible tasks where MCPM could be useful, along with several examples of fitting to domain-specific data as proofs of concept.

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O. Elek, J. Burchett, J. Prochaska, et. al.
Tue, 5 Apr 22
54/83

Comments: N/A

VIRUP : The Virtual Reality Universe Project [IMA]

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http://arxiv.org/abs/2110.04308


VIRUP is a new C++ open source software that provides an interactive virtual reality environment to navigate through large scientific astrophysical datasets obtained from both observations and simulations. It is tailored to visualize terabytes of data, rendering at 90 frames per second in order to ensure an optimal immersion experience. While VIRUP has initially been designed to work with gaming virtual reality headsets, it supports different modern immersive systems like 3D screens, 180 deg. domes or 360 deg. panorama. VIRUP is scriptable thanks to the Python language, a feature that allows to immerse visitors through pre-selected scenes or to pre-render sequences to create movies. A companion video (https://www.youtube.com/watch?v=KJJXbcf8kxA) to the last SDSS 2020 release as well as a 21 minute long documentary, The Archaeology of Light, https://go.epfl.ch/ArchaeologyofLight have been both 100% produced using VIRUP.

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F. Cabot, Y. Revaz, J. Kneib, et. al.
Tue, 12 Oct 21
18/73

Comments: 9 pages, 8 figures. Webpage:this http URL, link to “The Archaeology of Light”: this https URL

PSI: Constructing ad-hoc Simplices to Interpolate High-Dimensional Unstructured Data [IMA]

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http://arxiv.org/abs/2109.13926


Interpolating unstructured data using barycentric coordinates becomes infeasible at high dimensions due to the prohibitive memory requirements of building a Delaunay triangulation. We present a new algorithm to construct ad-hoc simplices that are empirically guaranteed to contain the target coordinates, based on a nearest neighbor heuristic and an iterative dimensionality reduction through projection. We use these simplices to interpolate the astrophysical cooling function $\Lambda$ and show that this new approach clearly outperforms our previous implementation at high dimensions.

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S. Lüders and K. Dolag
Thu, 30 Sep 21
51/82

Comments: 4 pages, 2 figures

3D Modelling and Visualisation of Observed Galaxies [IMA]

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http://arxiv.org/abs/2102.02141


Observational astronomers survey the sky in great detail to gain a better understanding of many types of astronomical phenomena. In particular, the formation and evolution of galaxies, including our own, is a wide field of research in astronomy. Three dimensional (spatial) scientific visualisation is typically limited to simulated galaxies, due to the inherently two dimensional spatial resolution of Earth-based observations. We present a novel approach to reconstruct and visualise 3D representations of galaxies based on observational data, using the scientific visualisation software Splotch to generate high quality visual representations that provide a new perspective of galaxies nearby the Milky Way.

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T. Dykes, C. Gheller, B. Koribalski, et. al.
Thu, 4 Feb 21
1/57

Comments: 16 pages, 12 figures, accepted for publication in Astronomy and Computing

papaya2: 2D Irreducible Minkowski Tensor computation [CL]

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http://arxiv.org/abs/2010.15138


A common challenge in scientific and technical domains is the quantitative description of geometries and shapes, e.g. in the analysis of microscope imagery or astronomical observation data. Frequently, it is desirable to go beyond scalar shape metrics such as porosity and surface to volume ratios because the samples are anisotropic or because direction-dependent quantities such as conductances or elasticity are of interest. Minkowski Tensors are a systematic family of versatile and robust higher-order shape descriptors that allow for shape characterization of arbitrary order and promise a path to systematic structure-function relationships for direction-dependent properties. Papaya2 is a software to calculate 2D higher-order shape metrics with a library interface, support for Irreducible Minkowski Tensors and interpolated marching squares. Extensions to Matlab, JavaScript and Python are provided as well. While the tensor of inertia is computed by many tools, we are not aware of other open-source software which provides higher-rank shape characterization in 2D.

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F. Schaller, J. Wagner and S. Kapfer
Fri, 30 Oct 20
69/74

Comments: 5 pages, 3 figures, published in the Journal of Open Source Software, code available at this https URL

Clustering-informed Cinematic Astrophysical Data Visualization with Application to the Moon-forming Terrestrial Synestia [IMA]

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http://arxiv.org/abs/2006.00084


Scientific visualization tools are currently not optimized to create cinematic, production-quality representations of numerical data for the purpose of science communication. In our pipeline \texttt{Estra}, we outline a step-by-step process from a raw simulation into a finished render as a way to teach non-experts in the field of visualization how to achieve production-quality outputs on their own. We demonstrate feasibility of using the visual effects software Houdini for cinematic astrophysical data visualization, informed by machine learning clustering algorithms. To demonstrate the capabilities of this pipeline, we used a post-impact, thermally-equilibrated Moon-forming synestia from \cite{Lock18}. Our approach aims to identify “physically interpretable” clusters, where clusters identified in an appropriate phase space (e.g. here we use a temperature-entropy phase-space) correspond to physically meaningful structures within the simulation data. Clustering results can then be used to highlight these structures by informing the color-mapping process in a simplified Houdini software shading network, where dissimilar phase-space clusters are mapped to different color values for easier visual identification. Cluster information can also be used in 3D position space, via Houdini’s Scene View, to aid in physical cluster finding, simulation prototyping, and data exploration. Our clustering-based renders are compared to those created by the Advanced Visualization Lab (AVL) team for the full dome show “Imagine the Moon” as proof of concept. With \texttt{Estra}, scientists have a tool to create their own production-quality, data-driven visualizations.

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P. Aleo, S. Lock, D. Cox, et. al.
Tue, 2 Jun 20
25/90

Comments: 19 pages, 16 figures, submitted to MNRAS

Optimally Fast Soft Shadows on Curved Terrain with Dynamic Programming and Maximum Mipmaps [CL]

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http://arxiv.org/abs/2005.06671


We present a simple, novel method of efficiently rendering ray cast soft shadows on curved terrain by using dynamic programming and maximum mipmaps to rapidly find a global minimum shadow cost in constant runtime complexity. Additionally, we apply a new method of reducing view ray computation times that pre-displaces the terrain mesh to bootstrap ray starting positions. Combining these two methods, our ray casting engine runs in real-time with more than 200% speed up over uniform ray stepping with comparable image quality and without hardware ray tracing acceleration. To add support for accurate planetary ephemerides and interactive features, we integrated the engine into celestia.Sci, a general space simulation software. We demonstrate the ability of our engine to accurately handle a large range of distance scales by using it to generate videos of lunar landing trajectories. The numerical error when compared with real lunar mission imagery is small, demonstrating the accuracy and efficiency of our approach.

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D. Jung, F. Schrempp and S. Son
Fri, 15 May 20
40/65

Comments: 16 pages, 17 figures

Robust Statistics for Image Deconvolution [IMA]

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http://arxiv.org/abs/1711.02793


We present a blind multiframe image-deconvolution method based on robust statistics. The usual shortcomings of iterative optimization of the likelihood function are alleviated by minimizing the M-scale of the residuals, which achieves more uniform convergence across the image. We focus on the deconvolution of astronomical images, which are among the most challenging due to their huge dynamic ranges and the frequent presence of large noise-dominated regions in the images. We show that high-quality image reconstruction is possible even in super-resolution and without the use of traditional regularization terms. Using a robust \r{ho}-function is straightforward to implement in a streaming setting and, hence our method is applicable to the large volumes of astronomy images. The power of our method is demonstrated on observations from the Sloan Digital Sky Survey (Stripe 82) and we briefly discuss the feasibility of a pipeline based on Graphical Processing Units for the next generation of telescope surveys.

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M. Lee, T. Budavari, R. White, et. al.
Thu, 9 Nov 17
23/54

Comments: N/A

3D visualization of astronomy data cubes using immersive displays [IMA]

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http://arxiv.org/abs/1607.08874


We report on an exploratory project aimed at performing immersive 3D visualization of astronomical data, starting with spectral-line radio data cubes from galaxies. This work is done as a collaboration between the Department of Physics and Astronomy and the Department of Computer Science at the University of Manitoba. We are building our prototype using the 3D engine Unity, because of its ease of use for integration with advanced displays such as a CAVE environment, a zSpace tabletop, or virtual reality headsets. We address general issues regarding 3D visualization, such as: load and convert astronomy data, perform volume rendering on the GPU, and produce physically meaningful visualizations using principles of visual literacy. We discuss some challenges to be met when designing a user interface that allows us to take advantage of this new way of exploring data. We hope to lay the foundations for an innovative framework useful for all astronomers who use spectral line data cubes, and encourage interested parties to join our efforts. This pilot project addresses the challenges presented by frontier astronomy experiments, such as the Square Kilometre Array and its precursors.

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G. Ferrand, J. English and P. Irani
Mon, 1 Aug 16
36/54

Comments: presentation given at CASCA conference on 2016/06/01

Visualising Large Datasets in TOPCAT v4 [IMA]

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http://arxiv.org/abs/1410.6725


TOPCAT is a widely used desktop application for manipulation of astronomical catalogues and other tables, which has long provided fast interactive visualisation features including 1, 2 and 3-d plots, multiple datasets, linked views, color coding, transparency and more. In Version 4 a new plotting library has been written from scratch to deliver new and enhanced visualisation capabilities. This paper describes some of the considerations in the design and implementation, particularly in regard to providing comprehensible interactive visualisation for multi-million point datasets.

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M. Taylor
Mon, 27 Oct 14
25/58

Comments: 4 pages, 2 figures, conference paper submitted to arXiv a year after acceptance

The physics of volume rendering [IMA]

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http://arxiv.org/abs/1410.6022


Radiation transfer is an important topic in several physical disciplines, probably most prominently in astrophysics. Computer scientists use radiation transfer, among other things, for the visualisation of complex data sets with direct volume rendering. In this note, I point out the connection between physical radiation transfer and volume rendering, and I describe an implementation of direct volume rendering in the astrophysical radiation transfer code RADMC-3D. I show examples for the use of this module on analytical models and simulation data.

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T. Peters
Thu, 23 Oct 14
48/60

Comments: N/A