Related papers: Flexible Raman Amplifier Optimization Based on Mac…
We revisit the problem of modulation instability (MI) in optical fibers, including higher-order dispersion terms, self-steepening, and Raman response. We derive expressions for the MI gain and use them to explore the role of self-steepening…
We consider backscattering of laser pulses in strongly-magnetized plasma mediated by kinetic magnetohydrodynamic waves. Magnetized low-frequency scattering, which can occur when the external magnetic field is neither perpendicular nor…
Maximum Likelihood (ML) algorithms, for the joint estimation of synchronization impairments and channel in Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system, are investigated in this work. A system…
With the rapid development of deep learning, automatic modulation recognition (AMR), as an important task in cognitive radio, has gradually transformed from traditional feature extraction and classification to automatic classification by…
IIn this paper we demonstrate a new scheme for Raman transitions which realize a symmetric momentum-space splitting of $4 \hbar k$, deflecting the atomic wave-packets into the same internal state. Combining the advantages of Raman and Bragg…
Invariant risk minimization (IRM) aims to enable out-of-distribution (OOD) generalization in deep learning by learning invariant representations. As IRM poses an inherently challenging bi-level optimization problem, most existing approaches…
A reinforcement learning approach to design optimised graded metamaterials for mechanical energy confinement and amplification is described. Through the proximal policy optimisation algorithm, the reinforcement agent is trained to optimally…
Frequency modulation coherent anti-Stokes Raman scattering (FM CARS) is presented, using a compact as well as fast and widely tunable fiber-based light source. With this light source Raman resonances between 700 cm$^{-1}$ and 3200 cm$^{-1}$…
Throughput optimization of optical communication systems is a key challenge for current optical networks. The use of gain-flattening filters (GFFs) simplifies the problem at the cost of insertion loss, higher power consumption and…
We investigate the spatial beam dynamics inside a multimode graded-index fiber under Raman amplification by adopting a semi-analytical variational approach. The variational analysis provides us with four coupled ordinary differential…
Diffusion and flow-matching models scale because pretraining is supervised regression: a clean sample is noised analytically, and a model regresses against a closed-form target. RL post-training aligns the model with a reward. In image…
Nonlinear distortion in power amplifiers (PA) can significantly degrade performance of orthogonal frequency division multiplexed (OFDM) communication systems. This paper presents a joint maximum-likelihood channel frequency response and…
Optical systems are scalable under low-intensity illumination since their governing equations are linearly dependent of the optical signal strength. Nonetheless, in high-intensity regimes, the induced polarization becomes nonlinear,…
This paper proposes several explicit and implicit multistep frequency response optimized integrators considering first or second order derivative. A prediction-based method aiming at accelerating a novel power system transient simulation…
The gain spectrum of an Erbium-Doped Fiber Amplifier (EDFA) has a complex dependence on channel loading, pump power, and operating mode, making accurate modeling difficult to achieve. Machine Learning (ML) based modeling methods can achieve…
In this work, the spectral evolution properties in single-frequency Raman fiber amplifier (RFA) with different pump manners are analyzed theoretically for the first time based on the gain dynamics. The analysis of gain dynamics reveals that…
A tunable, multi-degree-of-freedom, parametrically excited amplifier is introduced as an apparatus capable of shifting slow, weak signals to higher frequencies, by exploiting the amplifier natural resonances via controlled parametric…
In this paper, we propose an Expectation-Maximization-based (EM) Personalized Federated Learning (PFL) framework for multi-objective optimization (MOO) in Integrated Sensing and Communication (ISAC) systems. In contrast to standard…
We consider the problem of reconstructing a signal from multi-layered (possibly) non-linear measurements. Using non-rigorous but standard methods from statistical physics we present the Multi-Layer Approximate Message Passing (ML-AMP)…
Transmission interface power flow adjustment is a critical measure to ensure the security and economy operation of power systems. However, conventional model-based adjustment schemes are limited by the increasing variations and…