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cs.IT updates on arXiv.org

Theoretical Limits of Language Model Alignment $f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models When Can Voting Help, Hurt, or Change Course? Exact Structure of Binary Test-Time Aggregation When Semantic Communication Meets Queueing: Cross-Layer Latency and Task Fidelity Optimization Convexity in Disguise: A Theoretical Framework for Nonconvex Low-Rank Matrix Estimation Conditional Diffusion Under Linear Constraints: Langevin Mixing and Information-Theoretic Guarantees Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval Expert Routing for Communication-Efficient MoE via Finite Expert Banks Contextual Memory-Enhanced Source Coding for Low-SNR Communications Realizable Bayes-Consistency for General Metric Losses Leveraging Code Automorphisms for Improved Syndrome-Based Neural Decoding A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy Optimization of CV-QKD Under Practical Constraints Benchmarking Wireless Representations: High-Dimensional vs. Compressed Embeddings for Efficiency and Robustness Real-Time Text Transmission via LLM-Based Entropy Coding over Fixed-Rate Channels SwiftChannel: Algorithm-Hardware Co-Design for Deep Learning-Based 5G Channel Estimation Evolving Token Communication with Parametric Memory Network Remote Action Generation: Remote Control with Minimal Communication The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions Stabilizing Private LASSO under Heterogeneous Covariates via Anisotropic Objective Perturbation Linear-Readout Floors and Threshold Recovery in Computation in Superposition Soft Graph Diffusion Transformer for MIMO Detection Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design Exponential families from a single KL identity MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness Diffusion-OAMP for Joint Image Compression and Wireless Transmission Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
Mitigation of relative intensity noise of Quantum Dash mo...
Vidak Vujicic, Aravind P. Anthur, Arsalan Saljoghei, Vivek Panap · 2016-11-29 · via cs.IT updates on arXiv.org

Quantum Dash (Q-Dash) Passively Mode-Locked Lasers (PMLLs) exhibit significant low frequency Relative Intensity Noise (RIN), due to the high Mode Partition Noise (MPN), which prevents the implementation of multilevel amplitude modulation formats such as PAM4. The authors demonstrate low frequency RIN mitigation by employing 8B/10B and Manchester encoding with PAM4 modulation format. These encoding techniques reduce the overlap between the modulation spectral content and the low-frequency RIN of the Q-Dash devices, at the expense of increased overhead. The RIN of the 33.6 GHz free spectral range Q-Dash PMLL was characterized, and the results obtained show very high levels of RIN from DC to 4 GHz, but low levels for higher frequencies. The performance improvement for 28 GBaud 8B/10B and Manchester encoded PAM4 signal has been demonstrated compared to the case when no encoding is used. Finally, the effect of RIN on the system performance was demonstrated by comparing the Bit Error Rate (BER) performance of the PAM4 signaling obtained with an External Cavity Laser (ECL) to those obtained with Q-Dash PMLL.