Pith Number

pith:PFXNN7DH

pith:2026:PFXNN7DH3Q7WTDUIGWNF2PRT56

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Quantum Feature Pyramid Gating for Seismic Image Segmentation

Jyotsna Sharma, Taha Gharaibeh

A 4-qubit quantum circuit at Feature Pyramid merge points raises mean IoU from 0.8404 to 0.9389 on seismic salt segmentation.

arxiv:2605.15370 v1 · 2026-05-14 · quant-ph · cs.LG

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Claims

C1strongest claim

In a controlled EfficientNetV2-L ablation at 256 x 256 resolution, replacing the three Quantum FPN Gates with element-wise addition while holding the encoder, loss schedule, splits, and threshold search fixed reduces mean IoU from 0.9389 to 0.8404, a 9.85 percentage-point gap.

C2weakest assumption

The performance gap is attributable to the quantum circuit rather than to the introduction of 72 additional trainable parameters or to the specific gating topology; the paper compares against element-wise addition but does not report a classical parametric gate with matched parameter count.

C3one line summary

A 4-qubit quantum feature pyramid gating architecture raises mean IoU from 0.8404 to 0.9389 over classical addition in controlled ablations on the TGS salt segmentation dataset.

References

33 extracted · 33 resolved · 3 Pith anchors

[1] Parameterized quantum circuits as machine learning models, 2019

[2] Quantum machine learning for image classification, 2024

[3] Transfer learning in hybrid classical-quantum neural networks, 2020

[4] Quanvolutional neural networks: Powering image recognition with quantum circuits, 2020

[5] Effect of data encoding on the expressive power of variational quantum machine-learning models, 2021

Formal links

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Receipt and verification

First computed	2026-05-20T00:00:54.980004Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

796ed6fc67dc3f698e88359a5d3e33ef8dfeda218a8f4fe8b2445a56c831152f

Aliases

arxiv: 2605.15370 · arxiv_version: 2605.15370v1 · doi: 10.48550/arxiv.2605.15370 · pith_short_12: PFXNN7DH3Q7W · pith_short_16: PFXNN7DH3Q7WTDUI · pith_short_8: PFXNN7DH

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/PFXNN7DH3Q7WTDUIGWNF2PRT56 \
  | 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: 796ed6fc67dc3f698e88359a5d3e33ef8dfeda218a8f4fe8b2445a56c831152f

Canonical record JSON

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    "abstract_canon_sha256": "7ed8f0ba2e1e3af5c241733fe9d56527427db76bf1a3b5ead1c1bc1cf4d2b097",
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      "cs.LG"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "quant-ph",
    "submitted_at": "2026-05-14T19:50:01Z",
    "title_canon_sha256": "47b70801ed718bd36454a0c4d91cb67d372b33d5381b10d134a76e9d7727abb6"
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  "source": {
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    "kind": "arxiv",
    "version": 1
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