pith:XGHCOIKR
SFUMATO#: A GPU-accelerated code for self-gravitational radiation hydrodynamics simulation with adaptive mesh refinement
SFUMATO# provides a GPU-accelerated implementation for self-gravitational radiation hydrodynamics simulations on adaptive meshes.
arxiv:2604.21438 v2 · 2026-04-23 · astro-ph.GA · astro-ph.IM · astro-ph.SR
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Claims
We present a new implementation of the SFUMATO code, called SFUMATO#, for solving self-gravitational radiation hydrodynamics problems using adaptive mesh refinement (AMR) with the CUDA/HIP programming frameworks.
The linearized implicit method for non-equilibrium chemistry and thermal evolution preserves accuracy when the pseudo dust heat capacity is increased by up to three orders of magnitude, as demonstrated only on the specific test problems described.
SFUMATO# is a multi-GPU AMR code for self-gravitational radiation hydrodynamics featuring new linearized implicit solvers for non-equilibrium chemistry and thermal evolution, validated on test problems with measured scaling performance.
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| First computed | 2026-05-22T01:04:03.004583Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b98e272151ea489927c0b0bd3a8f4e092e0382e0c144359ced6572bf8a0d2fd7
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/XGHCOIKR5JEJSJ6AWC6TVD2OBE \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
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Canonical record JSON
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