Pith Number

pith:ZLWQFF6C

pith:2026:ZLWQFF6CWOJ33J4USUJGELYACN

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Robustness Evaluation of Hybrid Quantum Neural Networks under Noise Models via System-Level Error Mitigation

Alberto Marchisio, Jean-Michel Dricot, Jesse Roberta Mingue Njiki, Muhammad Kashif, Muhammad Shafique, Nouhaila Innan

The effectiveness of error mitigation in hybrid quantum neural networks varies significantly depending on the type and intensity of noise present.

arxiv:2604.17515 v2 · 2026-04-19 · quant-ph

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Claims

C1strongest claim

The impact of noise and the effect of mitigation are strongly dependent on the noise model and its strength. The model maintains comparatively strong performance under phase-flip and phase-damping noise, while substantial degradation is observed under high depolarizing and amplitude-damping noise.

C2weakest assumption

That the Qiskit Aer noise models and the chosen mitigation implementations in PennyLane/Mitiq accurately capture the dominant error sources and mitigation overheads that would appear on real NISQ hardware when running the same circuits.

C3one line summary

Simulations show hybrid quantum neural networks on Iris data degrade under depolarizing and amplitude-damping noise while phase-flip and phase-damping noise are less damaging, with ZNE, DDD, LRE, and PEC providing limited mitigation that depends on noise type and strength.

Cited by

2 papers in Pith

Meta-Quantum Ensemble Framework for Robust Network Intrusion Detection

Towards Fair Benchmarking of Quantum Transfer Learning for Visual Classification

Receipt and verification

First computed	2026-07-27T01:19:59.089574Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

caed0297c2b393bda7949512622f0013493126e8c3d2d251e6e93df09979be85

Aliases

arxiv: 2604.17515 · arxiv_version: 2604.17515v2 · doi: 10.48550/arxiv.2604.17515 · pith_short_12: ZLWQFF6CWOJ3 · pith_short_16: ZLWQFF6CWOJ33J4U · pith_short_8: ZLWQFF6C

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/ZLWQFF6CWOJ33J4USUJGELYACN \
  | 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: caed0297c2b393bda7949512622f0013493126e8c3d2d251e6e93df09979be85

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "5ac3b5162e60ffd1e315340b03fde3c613ac52ef2b08107a6b14baaa3919315f",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "quant-ph",
    "submitted_at": "2026-04-19T16:16:50Z",
    "title_canon_sha256": "945ca316a67c47c7e7473a9251ede7a0a8bc5d16a309415a29cabaa923e15ea4"
  },
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  "source": {
    "id": "2604.17515",
    "kind": "arxiv",
    "version": 2
  }
}