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Modeling the Lyman-$\alpha$ forest with Eulerian and SPH hydrodynamical methods

, , , , , , , , and . (2022)cite arxiv:2207.05023Comment: submitted to MNRAS.

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AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications., , , , , , , , , and 4 other author(s). SC, page 44:1-44:15. ACM, (2023)CBGIR: content-based geographic image retrieval., , , , and . GIS, page 526-527. ACM, (2010)TAC+: Drastically Optimizing Error-Bounded Lossy Compression for 3D AMR Simulations., , , , , , , and . CoRR, (2023)TAC+: Optimizing Error-Bounded Lossy Compression for 3D AMR Simulations., , , , , , , and . IEEE Trans. Parallel Distributed Syst., 35 (3): 421-438 (March 2024)Modeling the Lyman-$\alpha$ forest with Eulerian and SPH hydrodynamical methods, , , , , , , , and . (2022)cite arxiv:2207.05023Comment: submitted to MNRAS.Selection of Optimal Salient Time Steps by Non-negative Tucker Tensor Decomposition., , , , and . EuroVis (Short Papers), page 55-59. Eurographics Association, (2021)Analyzing Impact of Data Reduction Techniques on Visualization for AMR Applications Using AMReX Framework., , , , , and . SC Workshops, page 263-271. ACM, (2023)Foresight: analysis that matters for data reduction., , , , , , , , , and . SC, page 83. IEEE/ACM, (2020)Personalized In Situ Steering for Analysis and Visualization., , and . ISAV@SC, page 1-6. ACM, (2020)A topology-based approach to computing neighborhood-of-interest points using the Morse complex., , , , and . J. Vis. Commun. Image Represent., (2015)