Author Affiliations
Abstract
1 École Polytechnique Fédérale de Lausanne, Institute of Electrical and Micro Engineering, Ecublens, Switzerland
2 Koc University, Department of Electrical and Electronics Engineering, Istanbul, Turkey
The ever-increasing demand for training and inferring with larger machine-learning models requires more efficient hardware solutions due to limitations such as power dissipation and scalability. Optics is a promising contender for providing lower power computation, since light propagation through a nonabsorbing medium is a lossless operation. However, to carry out useful and efficient computations with light, generating and controlling nonlinearity optically is a necessity that is still elusive. Multimode fibers (MMFs) have been shown that they can provide nonlinear effects with microwatts of average power while maintaining parallelism and low loss. We propose an optical neural network architecture that performs nonlinear optical computation by controlling the propagation of ultrashort pulses in MMF by wavefront shaping. With a surrogate model, optimal sets of parameters are found to program this optical computer for different tasks with minimal utilization of an electronic computer. We show a remarkable decrease of 97% in the number of model parameters, which leads to an overall 99% digital operation reduction compared to an equivalently performing digital neural network. We further demonstrate that a fully optical implementation can also be performed with competitive accuracies.
neural networks nonlinear optics fiber optics surrogate optimization neuromorphic computing wavefront shaping 
Advanced Photonics
2024, 6(1): 016002
Author Affiliations
Abstract
1 École Polytechnique Fédérale de Lausanne, Optics Laboratory, Lausanne, Switzerland
2 École Polytechnique Fédérale de Lausanne, Laboratory of Applied Photonics Devices, Lausanne, Switzerland
The performance of fiber mode-locked lasers is limited due to the high nonlinearity induced by the spatial confinement of the single-mode fiber core. To massively increase the pulse energy of the femtosecond pulses, amplification is performed outside the oscillator. Recently, spatiotemporal mode-locking has been proposed as a new path to fiber lasers. However, the beam quality was highly multimode, and the calculated threshold pulse energy (>100 nJ) for nonlinear beam self-cleaning was challenging to realize. We present an approach to reach high energy per pulse directly in the mode-locked multimode fiber oscillator with a near single-mode output beam. Our approach relies on spatial beam self-cleaning via the nonlinear Kerr effect, and we demonstrate a multimode fiber oscillator with M2 < 1.13 beam profile, up to 24 nJ energy, and sub-100 fs compressed duration. Nonlinear beam self-cleaning is verified both numerically and experimentally for the first time in a mode-locked multimode laser cavity. The reported approach is further power scalable with larger core sized fibers up to a certain level of modal dispersion and could benefit applications that require high-power ultrashort lasers with commercially available optical fibers.
fiber lasers spatiotemporally mode-locked lasers multimode nonlinear fiber optics 
Advanced Photonics
2020, 2(5): 056005

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