Quantum-Aware Noise Modeling for Coherent ZR/ZR+ Optical Links Using QuTiP and OptiSystem: A Giant Step Toward Optical Digital Twins

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Authors: Praveen Kumar Pal
Cited by: 0
References: 17

Abstract

Coherent pluggable transceivers such as 400ZR, 800ZR, and ZR+ have emerged as essential enablers for modern data-center interconnects (DCI), offering high-capacity transmission over metro and regional distances. Traditional simulation methods rely predominantly on classical stochastic models for fiber impairments, amplified spontaneous emission (ASE), phase noise, and Digital Signal Processor (DSP) distortions. However, as symbol rates exceed 100 Gbaud and OSNR margins continue to shrink, several noise processes begin exhibiting distinct quantum mechanical characteristics that classical approximations cannot accurately capture. This paper introduces a Quantum-Aware Noise Modeling Framework that integrates QuTiP (Quantum Toolbox in Python) with OptiSystem to simulate coherent ZR/ZR+(ZR Standards) optical links under low-Optical Signal to Noise Ratio (OSNR) and high-order modulation regimes. The hybrid simulation approach incorporates density-matrix evolution, quantum-limited amplification, operator-based phase diffusion, vacuum fluctuations, and photon-number uncertainty into a classical coherent transmission workflow. Experimental analysis demonstrates that quantum-aware modeling yields significantly improved accuracy in Bit Error Rate (BER), Quality(Q)-factor, and constellation behavior prediction-especially in quantumdominant noise regimes. The proposed methodology provides a foundation for next-generation transceiver co-design and quantum-enhanced coherent DSP algorithms. This approach is the first giant step towards creating the next generation ultrahigh-speed digital twins for faster Optical product development.

Fields of Study & Subjects

Optical Network Technologies Semiconductor Lasers and Optical Devices Advanced Optical Network Technologies

Publication details

Journal / source
2026 IEEE International Conference for Convergence in Computing Technology (I3CTCON)
Publisher
IEEE
Pages
1–8
Publication date
14 March 2026