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 demonstrate the possibility of applying surface-enhanced Raman spectroscopy (SERS) combined with machine learning technology to detect and differentiate influenza type A and B viruses in a buffer environment. The SERS spectra of the influenza viruses do not possess specific peaks that allow for their straight classification and detection. Machine learning technologies (particularly, the support vector machine method) enabled the differentiation of samples containing influenza A and B viruses using SERS with an accuracy of 93% at a concentration of 200 μg/mL. The minimum detectable concentration of the virus in the sample using the proposed approach was ~0.05 μg/mL of protein (according to the Lowry protein assay), and the detection accuracy of a sample with this pathogen concentration was 84%.

We numerically quantify the performance of a photonic reservoir computer based on a semiconductor laser subject to high-pass filtered optoelectronic feedback. We assess its memory capacity, computational ability, and performance in solving a multi-step prediction task. By analyzing the complex bifurcation landscape of the corresponding delay-differential equation model, we observe that optimal performance occurs at the edge of instability, at the onset of periodic regimes, and unveil a parity asymmetry in the performance with a slight advantage for positive over negative feedback.

A compact Raman laser gas spectrometer is developed. It comprises a high-power green laser at 532.123 nm as an excitation source and a specially designed gas cell with an internal volume of less than 0.6 cm³ that can withstand gas pressures up to 100 atm. The resolution of the spectrometer is ~1 cm⁻¹. The Raman spectra of chemically pure isotopically enriched carbon dioxide (¹²CO₂, ¹³CO₂) and methane (¹²CH₄, ¹³CH₄) gases are studied. The expected limit of detection (LOD) is less than 100 ppm for the isotopologues of CO₂ and less than 25 ppm for those of CH₄ (at a gas pressure of 50 atm.), making the developed spectrometer promising for studying the sources of emissions of greenhouse gases by resolving their isotopologue composition. We also show the suitability of the spectrometer for Raman spectroscopy of human exhalation.

We analyze the modification of the computational properties of a time-delay photonic reservoir computer with a change in its feedback bandwidth. For a reservoir computing configuration based on a semiconductor laser subject to filtered optoelectronic feedback, we demonstrate that bandwidth selection can lead to a flat-topped eigenvalue spectrum for which a large number of system frequencies are weakly damped as a result of the attenuation of modulational instability by feedback filtering. This spectral configuration allows for the optimization of the reservoir in terms of its memory capacity, while its computational ability appears to be only weakly affected by the characteristics of the filter.

A laser diode subjected to optoelectronic feedback in which some light is converted to photocurrent that is fed back into the laser injection terminals can display periodic oscillations in its optical intensity. We demonstrate experimental and numerical evidence that, as the feedback level is varied, a stepwise change in the oscillation frequency manifests itself in the output optical intensity. These transitions in the dynamics can either correspond to an abrupt jump between two limit cycles, associated with a subcritical torus bifurcation of a limit cycle, or to a progressive switching mediated by an intermediate quasiperiodic state. Finally, when ramping the feedback level down, hysteresis is observed in the sequence of switching events between the limit cycles. Such devices are of interest for photonic microwave sources for wavelength-division multiplexed radio-over-fiber systems.