Contents
Abstract xi
Acknowledgments xiii
Author’s contribution xvii
Paper published in scientific journals . . . xvii
Paper in preparation . . . xvii
Conference papers . . . xvii
Contents xix List of Figures xxiii List of Tables xxv List of Acronyms xxvii Nomenclature xxxi 1 Introduction 1 1.1 What is a computer? . . . 1
1.2 From digital Turing/Von Neumann-related computers to analog bio-inspired pro-cessors . . . 2
1.3 Why photonics? . . . 4
1.4 Thesis outline . . . 6
2 Reservoir computing paradigm 7 2.1 Artificial neural networks: a brief overview . . . 8
2.1.1 General description. . . 8
2.1.2 Classifying neural network models . . . 9
2.2 Reservoir computing genesis . . . 12
2.3 Building and running a reservoir computer . . . 12
2.4 Benchmark tasks . . . 15
2.4.1 Memory capacities . . . 15
2.4.2 NARMA10 . . . 16
2.4.3 Nonlinear channel equalization. . . 16
2.4.4 Isolated spoken digits recognition . . . 17
2.4.5 Radar task . . . 17
3 Optical cavities as processing units 19 3.1 Introduction . . . 20
CONTENTS
3.2 Linear coherently driven passive cavities . . . 20
3.2.1 Ring interferometers theory . . . 20
3.2.2 Polarization eigenmodes of the cavity . . . 23
3.3 Using optical cavities as reservoirs . . . 24
3.4 Phase stabilization . . . 26
3.4.1 Principle . . . 26
3.4.2 Avoiding stimulated Brillouin back-scattering . . . 29
3.4.3 PID regulator design . . . 31
3.4.4 Phonic, thermal and vibration insulation . . . 32
4 Linear photonic reservoir with a quadratic non-linearity in the output layer 35 4.1 Introduction . . . 36
4.2 Operation principle . . . 36
4.3 Experimental implementation . . . 38
4.3.1 Description . . . 38
4.3.2 Technical specifications of the hardware components . . . 40
4.4 Simulation . . . 41
4.5 Results . . . 41
4.5.1 Memory capacity evaluation . . . 41
4.5.2 NARMA10 . . . 43
4.5.3 Nonlinear channel equalization. . . 44
4.5.4 Isolated spoken digits recognition . . . 46
4.5.5 Radar task . . . 47
4.6 Discussion . . . 48
5 Autonomous linear photonic reservoir with a quadratic non-linearity in the output layer 51 5.1 Introduction . . . 52
5.2 Operation principle . . . 53
5.3 Numerical investigation . . . 54
5.3.1 Description of the simulated setup . . . 54
5.3.2 Simulated features . . . 55
5.3.3 Technical specifications of the simulated hardware components . . . 56
5.4 Simulation results . . . 56
5.4.1 NARMA10 . . . 57
5.4.2 Nonlinear channel equalization. . . 57
5.4.3 Radar task . . . 58
5.5 Discussion . . . 59
6 Autonomous photonic reservoir computer with sine non-linearity in the input layer and optical output 61 6.1 Introduction . . . 62
6.2 Operation principle . . . 62
6.3 Physical implementation . . . 63
6.4 Numerical investigation . . . 65
6.4.1 Description of the simulated components . . . 65
6.4.2 Simulated features . . . 67
6.4.3 Simulation results for the nonlinear channel equalization task . . . 67
6.5 Experiment. . . 68
6.5.1 Technical specifications of the hardware components . . . 70
6.5.2 Experimental results . . . 73
6.5.2.1 Nonlinear channel equalization . . . 73
6.5.2.2 Radar task . . . 74
6.6 Discussion . . . 75
Contents
7 Conclusion and perspectives 77
Appendix 79
Appendix Numerical implementation of the PID regulator 81
Bibliography 89
