Revisiting Multi-Step Nonlinearity Compensation with Machine Learning

For the efficient compensation of fiber nonlinearity, one of the guiding principles appears to be: fewer steps are better and more efficient. We challenge this assumption and show that carefully designed multi-step approaches can lead to better performance-complexity trade-offs than their few-step counterparts.Comment: 4 pages, 3 figures, This is a preprint of a paper submitted to the 2019 European Conference on Optical Communicatio

Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation

In this paper, we propose a model-based machine-learning approach for dual-polarization systems by parameterizing the split-step Fourier method for the Manakov-PMD equation. The resulting method combines hardware-friendly time-domain nonlinearity mitigation via the recently proposed learned digital backpropagation (LDBP) with distributed compensation of polarization-mode dispersion (PMD). We refer to the resulting approach as LDBP-PMD. We train LDBP-PMD on multiple PMD realizations and show that it converges within 1% of its peak dB performance after 428 training iterations on average, yielding a peak effective signal-to-noise ratio of only 0.30 dB below the PMD-free case. Similar to state-of-the-art lumped PMD compensation algorithms in practical systems, our approach does not assume any knowledge about the particular PMD realization along the link, nor any knowledge about the total accumulated PMD. This is a significant improvement compared to prior work on distributed PMD compensation, where knowledge about the accumulated PMD is typically assumed. We also compare different parameterization choices in terms of performance, complexity, and convergence behavior. Lastly, we demonstrate that the learned models can be successfully retrained after an abrupt change of the PMD realization along the fiber.Comment: 10 pages, 11 figures, to appear in the IEEE/OSA Journal of Lightwave Technolog

Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation

We propose a model-based machine-learning approach for polarization-multiplexed systems by parameterizing the split-step method for the Manakov-PMD equation. This approach performs hardware-friendly DBP and distributed PMD compensation with performance close to the PMD-free case.Comment: 3 pages, 2 figure

Mesonic Contribution to the Compton Scattering Amplitude for Heavy Nuclei

The contribution of mesonic exchange currents to nuclear Compton scattering is investigated within the framework of a Fermi gas model of nuclear matter in the non-relativistic limit. The additional interaction between the nucleons is accounted for by including two- and three-body diagrams. As a test of this model, the enhancement constant $\kappa$ is calculated. The full correlators for the central and tensor part of the nucleon-nucleon interaction due to pion exchange are obtained and the energy dependence of the amplitude is investigated. The contribution of the $\Delta$-excitation to the mesonic part of the Compton amplitude is calculated explicitely using an effective Hamiltonian in the static limit.Comment: 21 pages, Latex, 12 figures available at http://www.physik2.gwdg.de/lokales/Forschungsberichte/Theorie/Meso

Meson-induced correlations of nucleons in nuclear Compton scattering

The non-resonant (seagull) contribution to the nuclear Compton amplitude at low energies is strongly influenced by nucleon correlations arising from meson exchange. We study this problem in a modified Fermi gas model, where nuclear correlation functions are obtained with the help of perturbation theory. The dependence of the mesonic seagull amplitude on the nuclear radius is investigated and the influence of a realistic nuclear density on this amplitude is dicussed. We found that different form factors appear for the static part (proportional to the enhancement constant $\kappa$) of the mesonic seagull amplitude and for the parts, which contain the contribution from electromagnetic polarizabilities.Comment: 15 pages, Latex, epsf.sty, 9 eps figures

Compton Scattering from the Deuteron and Extracted Neutron Polarizabilities

Differential cross sections for Compton scattering from the deuteron were measured at MAX-lab for incident photon energies of 55 MeV and 66 MeV at nominal laboratory angles of $45^\circ$, $125^\circ$, and $135^\circ$. Tagged photons were scattered from liquid deuterium and detected in three NaI spectrometers. By comparing the data with theoretical calculations in the framework of a one-boson-exchange potential model, the sum and difference of the isospin-averaged nucleon polarizabilities, $\alpha_N + \beta_N = 17.4 \pm 3.7$ and $\alpha_N - \beta_N = 6.4 \pm 2.4$ (in units of $10^{-4}$ fm$^3$), have been determined. By combining the latter with the global-averaged value for $\alpha_p - \beta_p$ and using the predictions of the Baldin sum rule for the sum of the nucleon polarizabilities, we have obtained values for the neutron electric and magnetic polarizabilities of $\alpha_n= 8.8 \pm 2.4$(total) $\pm 3.0$(model) and $\beta_n = 6.5 \mp 2.4$(total) $\mp 3.0$(model), respectively.Comment: 4 pages, 2 figures, revtex. The text is substantially revised. The cross sections are slightly different due to improvements in the analysi

Electromagnetic Polarizabilities of Nucleons bound in 40^{40}Ca, 16^{16}O and 4^4He

Differential cross sections for elastic scattering of photons have been measured for $^{40}$Ca at energies of 58 and 74 MeV and for $^{16}$O and $^4$He at 61 MeV, in the angular range from 45$^o$ to 150$^o$. Evidence is obtained that there are no significant in-medium modifications of the electromagnetic polarizabilities except for those originating from meson exchange currents.Comment: 20 pages including 5 Figure

Revisiting Efficient Multi-Step Nonlinearity Compensation with Machine Learning: An Experimental Demonstration

Efficient nonlinearity compensation in fiber-optic communication systems is considered a key element to go beyond the "capacity crunch''. One guiding principle for previous work on the design of practical nonlinearity compensation schemes is that fewer steps lead to better systems. In this paper, we challenge this assumption and show how to carefully design multi-step approaches that provide better performance--complexity trade-offs than their few-step counterparts. We consider the recently proposed learned digital backpropagation (LDBP) approach, where the linear steps in the split-step method are re-interpreted as general linear functions, similar to the weight matrices in a deep neural network. Our main contribution lies in an experimental demonstration of this approach for a 25 Gbaud single-channel optical transmission system. It is shown how LDBP can be integrated into a coherent receiver DSP chain and successfully trained in the presence of various hardware impairments. Our results show that LDBP with limited complexity can achieve better performance than standard DBP by using very short, but jointly optimized, finite-impulse response filters in each step. This paper also provides an overview of recently proposed extensions of LDBP and we comment on potentially interesting avenues for future work.Comment: 10 pages, 5 figures. Author version of a paper published in the Journal of Lightwave Technology. OSA/IEEE copyright may appl

The Role of Dietary Fiber in Rheumatoid Arthritis Patients: A Feasibility Study

Short-chain fatty acids are microbial metabolites that have been shown to be key regulators of the gut–joint axis in animal models. In humans, microbial dysbiosis was observed in rheumatoid arthritis (RA) patients as well as in those at-risk to develop RA, and is thought to be an environmental trigger for the development of clinical disease. At the same time, diet has a proven impact on maintaining intestinal microbial homeostasis. Given this association, we performed a feasibility study in RA patients using high-fiber dietary supplementation with the objective to restore microbial homeostasis and promote the secretion of beneficial immunomodulatory microbial metabolites. RA patients (n = 36) under routine care received daily high-fiber bars or cereals for 28 days. Clinical assessments and laboratory analysis of immune parameters in blood and stool samples from RA patients were done before and after the high-fiber dietary supplementation. We observed an increase in circulating regulatory T cell numbers, favorable Th1/Th17 ratios, as well as decreased markers of bone erosion in RA patients after 28 days of dietary intervention. Furthermore, patient-related outcomes of RA improved. Based on these results, we conclude that controlled clinical studies of high-fiber dietary interventions could be a viable approach to supplement or complement current pharmacological treatment strategies

Functional polymorphisms within the inflammatory pathway regulate expression of extracellular matrix components in a genetic risk dependent model for anterior cruciate ligament injuries

Objectives: To investigate the functional effect of genetic polymorphisms of the inflammatory pathway on structural extracellular matrix components (ECM) and the susceptibility to an anterior cruciate ligament (ACL) injury. Design: Laboratory study, case–control study. Methods: Eight healthy participants were genotyped for interleukin (IL)1B rs16944 C > T and IL6 rs1800795 G > C and