Microcavities enable the generation of highly efficient microcombs, which find applications in various domains, such as high-precision metrology, sensing, and telecommunications. Such applications generally require precise control over the spectral features of the microcombs, such as free spectral range, spectral envelope, and bandwidth. Most existing methods for customizing microcomb still rely on manual exploration of a large parameter space, often lacking practicality and versatility. In this work, we propose a smart approach that employs genetic algorithms to autonomously optimize the parameters for generating and tailoring stable microcombs. Our scheme controls optical parametric oscillation in a microring resonator to achieve broadband microcombs spanning the entire telecommunication C-band. The high flexibility of our approach allows us to obtain complex microcomb spectral envelopes corresponding to various operation regimes, with the potential to be directly adapted to different microcavity geometries and materials. Our work provides a robust and effective solution for targeted soliton crystal and multi-soliton state generation, with future potential for next-generation telecommunication applications and artificial intelligence-assisted data processing.

Mode-locking techniques have played a pivotal role in developing and advancing laser technology. Stable fiber-cavity configurations can generate trains of pulses spanning from MHz to GHz speeds, which are fundamental to various applications in micromachining, spectroscopy, and communications. However, the generation and exploitation of multiple timescales in a single laser cavity configuration remain unexplored. Our work demonstrates a fiber-cavity laser configuration designed to generate and control pulse trains from nanosecond to picosecond timescales with a broadband output and a low mode-locking threshold. Our approach exploits a frequency mode-locking mechanism that simultaneously drives the modes of an integrated microring resonator nested within an external fiber-loop cavity, guaranteeing ultra-stable operation. By selectively filtering the nested cavity modes, we can transition from nanosecond pulses to pulse burst trains in which nanosecond and picosecond components coexist. Our laser configuration produces a train of pulses with durations of 5.1 ns and 3.1 ps at repetition rates of 4.4 MHz and 48.7 GHz, with time-bandwidth products close to the transform-limited values of 0.5 and 0.46, respectively. Moreover, in the absence of frequency modulation, we demonstrate the generation of comb spectra with an adjustable central wavelength. Our findings have the potential to significantly contribute to the development of cutting-edge technologies and applications, harnessing the distinct advantages of mode-locked pulses across various scientific and engineering disciplines.

We propose a scheme for bifurcation control in micro-cavities based on the interplay between the ultrafast Kerr effect and a slow nonlinearity, such as thermo-optical, free-carriers-induced, or opto-mechanical one. We demonstrate that Hopf bifurcations can be efficiently controlled with a low energy signal via four-wave mixing. Our results show that new strategies are possible for designing efficient micro-cavity-based oscillators and sensors. Moreover, they provide new understanding of the effect of coherent wave mixing in the thermal stability regions of optical micro-cavities, fundamental for micro-resonator-based applications in communications, sensing, and metrology, including optical micro-combs.

The performance limitations of traditional computer architectures have led to the rise of brain‐inspired hardware, with optical solutions gaining popularity due to the energy efficiency, high speed, and scalability of linear operations. However, the use of optics to emulate the synaptic activity of neurons has remained a challenge since the integration of nonlinear nodes is power‐hungry and, thus, hard to scale. Neuromorphic wave computing offers a new paradigm for energy‐efficient information processing, building upon transient and passively nonlinear interactions between optical modes in a waveguide. Here, an implementation of this concept is presented using broadband frequency conversion by coherent higher‐order soliton fission in a single‐mode fiber. It is shown that phase encoding on femtosecond pulses at the input, alongside frequency selection and weighting at the system output, makes transient spectro‐temporal system states interpretable and allows for the energy‐efficient emulation of various digital neural networks. The experiments in a compact, fully fiber‐integrated setup substantiate an anticipated enhancement in computational performance with increasing system nonlinearity. The findings suggest that broadband frequency generation, accessible on‐chip and in‐fiber with off‐the‐shelf components, may challenge the traditional approach to node‐based brain‐inspired hardware design, ultimately leading to energy‐efficient, scalable, and dependable computing with minimal optical hardware requirements.

The development of integrated and programmable photonic devices has significantly affected modern communications and signal processing in both the classical and quantum domains. However, achieving the required performance for new smart applications presents challenges in terms of design, fabrication, and control over multiple parameters. Optimization methods that leverage metaheuristic algorithms, machine learning, and artificial neural networks offer efficient solutions for the complex design of photonic devices, enabling new and desired functionalities. This comprehensive review explores the use of these methods to enhance the fabrication of innovative devices for smart photonic applications in next-generation communication and signal processing. We begin by introducing the mathematical frameworks of these optimization methods. We then investigate how they enable customization, optimization, and new device functionalities. Ultimately, we present our conclusions and discuss future prospects, emphasizing the potential of optimization methods in promoting revolutionary advancements in photonics.