pith:3AF3DBYV
ML-based Fast Simulation of FARICH Responses
A conditional GAN can generate realistic photon hits for the FARICH detector much faster than Monte Carlo methods.
arxiv:2605.17635 v1 · 2026-05-17 · hep-ex · cs.LG
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\pithnumber{3AF3DBYVWXRL4QBLHTHOS37FQM}
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Record completeness
Claims
The cGAN produces realistic samples and provides a significant speed-up over Monte-Carlo simulation.
That the chosen metrics on probability maps and reconstructed velocity distributions are adequate proxies for the realism needed in downstream physics analyses, without direct comparison to real experimental data.
A cGAN generates realistic photon hit samples for the FARICH detector conditioned on particle parameters and outperforms a linear statistical baseline in realism while providing speed-up over Monte Carlo.
References
Formal links
Receipt and verification
| First computed | 2026-05-20T00:04:49.748970Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
d80bb18715b5e2be402b3ccee96fe5831b597c7826366dd4dccf7e3a8df6452d
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/3AF3DBYVWXRL4QBLHTHOS37FQM \
| 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())"
# expect: d80bb18715b5e2be402b3ccee96fe5831b597c7826366dd4dccf7e3a8df6452d
Canonical record JSON
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"license": "http://creativecommons.org/licenses/by/4.0/",
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