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A fully GPU-based workflow for building physics emulators of hypersonic flows

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arXiv:2606. 13742v1 Announce Type: new Abstract: The ability to resolve complex physical phenomena with high fidelity and at low computational cost is central to addressing key challenges in modern engineering.

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Authors: Fabian Paischer, Dylan Rubini, Deniz A. Bezgin, Aaron B. Buhendwa, David Hauser, Florian Sestak, Johannes Brandstetter, Sebastian Kaltenbach, Nikolaus A. Adams
Released: 2026-06-15 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because A fully GPU-based workflow for building physics emulators of hypersonic flows overlaps with clean result "The marker is a representational handle, not a behavioural one — sharing it between a villain persona and the assistant transfers no misalignment (HIGH confidence)", experiment "Follow-up to #354: cascading chunk-binding — does A→B, B→C, C→D propagate the full chain on a recipient trained only to emit A?", experiment "#351 follow-up: broader-vocab position-0 sweep at T=1.0 + position-1 suffix isolation". Matching terms: rate, full, model. Source: arxiv cs.LG (Machine Learning).
arXiv: 2606.13742

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