Pith Number

pith:UFMLKZIL

pith:2026:UFMLKZILZGVPEH3ESEZKGTLQGI

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ML-assisted Subband Learned Digital Backpropagation for Nonlinearity Compensation in Wideband Optical Systems

Alexey Redyuk, Evgeny Shevelev, Mikhail Fedoruk, Oleg Sidelnikov, Vitaly Danilko

Subband learned digital backpropagation achieves better nonlinearity compensation at lower complexity in wideband optical systems.

arxiv:2605.14481 v1 · 2026-05-14 · physics.optics

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Numerical simulations of an 11×40 Gbaud WDM RRC-16QAM 20×100 km transmission system demonstrate that the proposed method provides a superior performance--complexity trade-off compared to conventional DBP and enhanced DBP. In the low- and medium-complexity regimes, SbL-DBP provides higher signal-to-noise ratio gains while requiring fewer propagation steps.

C2weakest assumption

That the subband decomposition plus trainable MIMO structure sufficiently captures all relevant intra- and inter-subband nonlinear interactions without significant residual modeling error when applied to real hardware or different fiber types.

C3one line summary

SbL-DBP decomposes signals into subbands for efficient dispersion handling and applies end-to-end trained MIMO filters plus sparsification to compensate nonlinear effects, delivering higher SNR gains with fewer steps than conventional DBP in 11-channel 2000 km simulations.

References

27 extracted · 27 resolved · 0 Pith anchors

[1] Five AI trends impacting telecom in 2026, 2026

[2] Roadmap on optical communications, 2024

[3] Fiber-optic trans- mission and networking: the previous 20 and the next 20 years, 2018

[4] A tutorial on fiber Kerr nonlinearity effect and its compensation in optical communication systems, 2021

[5] A Survey on Fiber Nonlinearity Compensation for 400 Gb/s and beyond Optical Communication Systems, 2017

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-17T23:39:06.546719Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

a158b5650bc9aaf21f649132a34d70320cbeaded501e5f50b85cfa2c7dd70d66

Aliases

arxiv: 2605.14481 · arxiv_version: 2605.14481v1 · doi: 10.48550/arxiv.2605.14481 · pith_short_12: UFMLKZILZGVP · pith_short_16: UFMLKZILZGVPEH3E · pith_short_8: UFMLKZIL

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/UFMLKZILZGVPEH3ESEZKGTLQGI \
  | 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: a158b5650bc9aaf21f649132a34d70320cbeaded501e5f50b85cfa2c7dd70d66

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "930ee378dd13ce37f20549e2c2d8ca6a670173ec661d78c9e8d04e8e4456f6e6",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "physics.optics",
    "submitted_at": "2026-05-14T07:22:13Z",
    "title_canon_sha256": "9b8d30426a526a2c3df288d8e981e3a41b36f0e40e4b39b1a6278dc7e10b9cf3"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.14481",
    "kind": "arxiv",
    "version": 1
  }
}