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pith:3ORNYHBJ

pith:2025:3ORNYHBJFIDU45CUBJ2UXHDEFH
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Learning holographic QCD with unflavoured meson spectra

Mathew Thomas Arun, Ritik Pal

A neural network reconstructs the five-dimensional holographic geometry and potentials of QCD from unflavored meson mass spectra.

arxiv:2512.16450 v2 · 2025-12-18 · hep-ph · cond-mat.dis-nn · hep-th

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4 Citations open
5 Replications open
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Claims

C1strongest claim

Using the masses of the unflavored mesons ρ, a1, a2, and f0 and their excitations as training data, the model learns confining effective potentials and computes a dilaton profile that satisfies the null energy condition. The network predicts that the dilaton's IR behavior will be much steeper than its quadratic form. The symmetry-breaking bulk potential V(X)=k1 X^3 + k2 X^4 was computed with k1 ∼ -4 and k2 ∼ 9. The deep-learned parameters, metric, and dilaton profile were then used to predict the pion mass and its spectrum with good accuracy.

C2weakest assumption

The discretized Schrödinger-like equation with Dirichlet boundary conditions on a linear moose accurately represents the holographic QCD dynamics, and the chosen set of meson masses is sufficient to determine the geometry and potentials uniquely without significant overfitting or degeneracy.

C3one line summary

Neural network learns confining potentials and dilaton profile in holographic QCD from meson spectra, predicting steeper IR dilaton and pion masses with good accuracy.

References

51 extracted · 51 resolved · 23 Pith anchors

[1] The Large N Limit of Superconformal Field Theories and Supergravity 1998 · arXiv:hep-th/9711200
[2] Gauge Theory Correlators from Non-Critical String Theory 1998 · arXiv:hep-th/9802109
[3] Anti De Sitter Space And Holography 1998 · arXiv:hep-th/9802150
[4] Low energy hadron physics in holographic QCD 2005 · arXiv:hep-th/0412141
[5] More on a holographic dual of QCD 2005 · arXiv:hep-th/0507073

Formal links

2 machine-checked theorem links

Receipt and verification
First computed 2026-05-18T02:44:32.111843Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

dba2dc1c292a074e74540a754b9c6429d6502e54fd36dc769eaaa146408ba112

Aliases

arxiv: 2512.16450 · arxiv_version: 2512.16450v2 · doi: 10.48550/arxiv.2512.16450 · pith_short_12: 3ORNYHBJFIDU · pith_short_16: 3ORNYHBJFIDU45CU · pith_short_8: 3ORNYHBJ
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/3ORNYHBJFIDU45CUBJ2UXHDEFH \
  | 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: dba2dc1c292a074e74540a754b9c6429d6502e54fd36dc769eaaa146408ba112
Canonical record JSON
{
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    "abstract_canon_sha256": "4705099805d11449ed95197989409e4436f80136e5aacc845b76899bb328fa40",
    "cross_cats_sorted": [
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      "hep-th"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "hep-ph",
    "submitted_at": "2025-12-18T12:11:16Z",
    "title_canon_sha256": "72b19dd041276e2ce1c6c4838c76db849b830a1e6d54c49a4edfb6384ba756f3"
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