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In this paper, we investigate the possibility of generating supercontinuum in highly nonlinear fibers with improved stability characteristics through modulation of the input pulse. Specifically, we show that broadband coherent supercontinuum can be generated in the long pulse regime, provided the modulation parameters and nonlinear fiber length are carefully tuned. Based on physical arguments, we derive general guidelines for the choice of modulation frequency and fiber length. Significantly, the guidelines are valid for arbitrary long pulses. [ABSTRACT FROM AUTHOR]

The article reports on a low-dispersion photonic-crystal fibre (PCF) that could overcome the problem of ultrashort-pulse delivery, presented by J. Skibina and colleagues. It mentions that this new design of PCF does not only enlarges the band of transmitted wavelength but also reduces the dispersion and its variation with wavelength.

The noise-like pulse regime of optical fiber lasers is highly complex, and associated with multiscale emission of random sub-picosecond pulses underneath a much longer envelope. With the addition of highly nonlinear fiber in the cavity, noise-like pulse lasers can also exhibit supercontinuum broadening and the generation of output spectra spanning 100's of nm. Achieving these broadest bandwidths, however, requires careful optimization of the nonlinear polarization rotation based saturable absorber, which involves a very large potential parameter space. Here we study the spectral characteristics of a broadband noise-like pulse laser by scanning the laser operation over a random sample of 50,000 polarization settings, and we quantify that these broadest bandwidths are generated in only ∼ 0.5% of cases. We also show that a genetic algorithm can replace trial and error optimization to align the cavity for these broadband operating states. [ABSTRACT FROM AUTHOR]

We demonstrate computational spectral-domain ghost imaging by encoding complementary Fourier patterns directly onto the spectrum of a superluminescent laser diode using a programmable spectral filter. Spectral encoding before the object enables uniform spectral illumination across the beam profile, removing the need for light collection optics and yielding increased signal-to-noise ratio. In addition, the use of complementary Fourier patterns allows reduction of deleterious of parasitic light effects. As a proof-of-concept, we measure the wavelength-dependent transmission of a Michelson interferometer and a wavelength-division multiplexer. Our results open new perspectives for remote broadband spectral measurements. [ABSTRACT FROM AUTHOR]

Supercontinuum generation is a highly nonlinear process that exhibits unstable and chaotic characteristics when developing from long pump pulses injected into the anomalous dispersion regime of an optical fiber. A particular feature associated with this regime is the long-tailed "rogue wave"-like statistics of the spectral intensity on the long-wavelength edge of the supercontinuum, linked to the generation of a small number of "rogue solitons" with extreme red-shifts. Whilst the statistical properties of rogue solitons can be conveniently measured in the spectral domain using the real-time dispersive Fourier transform technique, we cannot use this technique to determine any corresponding temporal properties since it only records the spectral intensity and one loses information about the spectral phase. And direct temporal characterization using methods such as the time-lens has resolution of typically 100's of fs, precluding the measurement of solitons which possess typically much shorter durations. Here, we solve this problem by using machine learning. Specifically, we show how supervised learning can train a neural network to predict the peak power, duration, and temporal walk-off with respect to the pump pulse position of solitons at the edge of a supercontinuum spectrum from only the supercontinuum spectral intensity without phase information. Remarkably, the network accurately predicts soliton characteristics for a wide range of scenarios, from the onset of spectral broadening dominated by pure modulation instability to near octave-spanning supercontinuum with distinct rogue solitons. [ABSTRACT FROM AUTHOR]

We report the application of a neural network to correlate spectral and temporal properties for modulation instability excited by a continuous wave field with random quantum noise. Using numerical simulations to generate large ensembles of chaotic modulation instability data, a trained neural network is shown to be able to correlate unstable intensity spectra and associated temporal intensity peaks with correlation coefficients exceeding ρ = 0. 90 for dynamic ranges exceeding 40 dB. Such excellent correlation is obtained both in the initial evolving phase of modulation instability where spectra typically possess significant sideband structure, as well as in the stationary phase of the instability when distinct sideband structure is not apparent. For both cases, we also test the degree to which a neural network may be able to "forecast" temporal instability peaks based on analyzing spectral intensity at an earlier spatial reference position, but conclude that such forecasting is successful over only within a very localized distance range much less than the characteristic nonlinear length. • We report neural network spectral and temporal correlation in modulation instability. • Correlation of 0.90 is obtained for spectral dynamic range exceeding 40 dB. • Correlation is shown both in the initial and stationary phases of the instability. • Forecasting is possible over only a fraction of a nonlinear length. [ABSTRACT FROM AUTHOR]

While recent high-profile assassination attempts have once again brought nerve agents (NAs) into the spotlight, the current portfolio of NA sensors lack a sufficient combination of high performance and field-deployability. Here, we report a novel optical sensor for the detection of gaseous NAs with a potential to fill this gap. The technique is based on Fourier transform spectroscopy with a supercontinuum (SC) light source and cantilever-enhanced photoacoustic detection providing fast multi-species gas sensing with high sensitivity and selectivity in a sample volume of 7 ml, which becomes advantageous when analysing limited NA samples in the field. We study the fundamental C–H stretch bands of four known NA simulants and achieve detection limits of 64–530 ppb in one minute and recovery times of a few minutes. In the near future, the technique has significant potential to improve through the development of more powerful SC sources further in the mid-infrared region. [Display omitted] • Sub-ppm detection of nerve agent simulants. • Low gas consumption of a few milliliters. • High selectivity and possibility for multi-species detection. • Fast response and recovery times. [ABSTRACT FROM AUTHOR]

Aerosol techniques were used to synthesize spherical and monodisperse silver nanoparticles for plasmonic materials. The particles were generated with an evaporation-condensation technique followed by size selection and sintering with a differential mobility analyzer and a tube furnace, respectively. Finally, the nanoparticles were collected on a glass substrate with an electrostatic precipitator. The particle size distributions were measured with a scanning mobility particle sizer and verified with a transmission electron microscope. A spectrophotometer was used to measure the optical extinction spectra of the prepared samples, which contained particles with diameters of approximately 50, 90 and 130 nm. By controlling the particle size, the dipolar peak of the localized surface plasmon resonance was tuned between wavelengths of 398 and 448 nm. In addition, quadrupolar resonances were observed at shorter wavelengths as predicted by the simplified theoretical model used to characterize the measured spectra. [ABSTRACT FROM AUTHOR]

Multimode fibers have recently attracted significant attention due to their high-power handling capability and beam self-cleaning property that results in a single-mode profile at the fiber output. Here, we perform a detailed experimental comparison of the relative intensity noise (RIN) of all-fiber supercontinuum (SC) generated in multimode step-index (MMF) and graded-index (GRIN) fibers. We also characterize the spatial intensity profile of the SC in different wavelength bands, showing that it is near single mode across the full spectrum. Our results show that the RIN of SC generated in multimode GRIN fibers is not only lower than that generated in a step-index MMF but close to that of a SC generated in a single-mode fiber.

Supercontinuum generation in optical fiber involves complex nonlinear dynamics, making optimization challenging, and typically relying on trial-and-error or extensive numerical simulations. Machine learning and metaheuristic algorithms offer more efficient optimization approaches. We report here an experimental study of supercontinuum spectral shaping by tuning the phase of the input pulses, different optimization approaches including a genetic algorithm, particle swarm optimizer, and simulated annealing. We find that the genetic algorithm and particle swarm optimizer are more robust and perform better, with the particle swarm optimizer converging faster. Our study provides valuable insights for the systematic optimization of supercontinuum and other optical sources., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Light beams carrying orbital angular momentum (OAM) in free space or within optical fibers have a wide range of applications in optics; however, exciting these modes with both high purity and low loss generally requires demanding optimization of excitation conditions in a high dimensional space. Furthermore, mechanical drift can significantly degrade the mode purity over time, which may limit practical deployment of OAM modes in concrete applications. Here, combining an iterative wavefront matching approach and a genetic algorithm, we demonstrate rapid and automated excitation of OAM modes with optimized purity and reduced loss. Our approach allows for systematic computational realignment of the system enabling drift compensation over extended durations. Our experimental results indicate that OAM purity can be optimized and maintained over periods exceeding 24 h, paving the way for the applications of stable OAM beams in optics.

Identifying the underlying processes that locally dominate physical interactions is the key to understanding nonlinear dynamics. Machine-learning techniques have recently been shown to be highly promising in automating the search for dominant physics, adding important insights that complement analytical methods and empirical intuition. Here we apply a fully unsupervised approach to the search for dominant balance during nonlinear and dispersive propagation in an optical fiber and show that we can algorithmically identify dominant interactions in cases of optical wavebreaking, soliton fission, dispersive wave generation, and Raman soliton emergence. We discuss how dominant balance manifests both in the temporal and spectral domains.

We report the generation of a broadband supercontinuum (SC) from 790 to 2900 nm in a tellurite graded-index (GRIN) multimode fiber with a nanostructured core. We study the SC dynamics in different dispersion regimes and observe near-single-mode spatial intensity distribution at high input energy values. Numerical simulations of the (3 + 1)D generalized nonlinear Schrödinger equation are in good agreement with our experiments. Our results open a new avenue for the generation of high-power mid-infrared SC sources in soft-glass fibers.

Ghost imaging in the time domain allows for reconstructing fast temporal objects using a slow photodetector. The technique involves correlating random or pre-programmed probing temporal intensity patterns with the integrated signal measured after modulation by the temporal object. However, the implementation of temporal ghost imaging necessitates ultrafast detectors or modulators for measuring or pre-programming the probing intensity patterns, which are not available in all spectral regions especially in the mid-infrared range. Here, we demonstrate a frequency downconversion temporal ghost imaging scheme that enables to extend the operation regime to arbitrary wavelengths regions where fast modulators and detectors are not available. The approach modulates a signal with temporal intensity patterns in the near-infrared and transfers the patterns to an idler via difference-frequency generation in a nonlinear crystal at a wavelength where the temporal object can be retrieved. As a proof-of-concept, we demonstrate computational temporal ghost imaging in the mid-infrared with operating wavelength that can be tuned from 3.2 to 4.3 μm. The scheme is flexible and can be extended to other regimes. Our results introduce new possibilities for scan-free pump-probe imaging and the study of ultrafast dynamics in spectral regions where ultrafast modulation or detection is challenging such as the mid-infrared and THz regions., (© 2024. The Author(s).)

We report the generation of a spectrally tailored supercontinuum using Fourier-domain pulse shaping of femtosecond pulses injected into a highly nonlinear fiber controlled by a genetic algorithm. User-selectable spectral enhancement is demonstrated over the 1550-2000-nm wavelength range, with the ability to both select a channel with target central wavelength and bandwidth in the range of 1-5 nm. The spectral enhancement factor relative to unshaped input pulses is typically ∼5-20 in the range 1550-1800 nm and increases for longer wavelengths, exceeding a factor of 160 around 2000 nm. We also demonstrate results where the genetic algorithm is applied to the enhancement of up to four spectral channels simultaneously.

We report real-time monitoring of coarse aerosol particle distribution in a 9 m wide full-scale industrial boiler using a broadband supercontinuum lidar. The technique utilizes the light backscattered from the aerosol to map the extinction profile using the Klett inversion method, with measured extinction values of 0.04 - 0.2 m -1 across the furnace. The technique further exploits differential absorption of water molecules in the 1.25 - 1.5 µm region to map the water vapor concentration profile in the furnace up to a distance of 3.9 m with a spatial resolution of 30 cm. We also take advantage of the strong reflection from the boiler back-wall to simultaneously measure the average water vapor temperature and concentration in the boiler in good agreement with reference readings from the boiler. Our results open novel perspectives for versatile 3D profiling of flue gas parameters and other industrial process analysis.

We analyze the dynamics of modulation instability in optical fiber (or any other nonlinear Schrödinger equation system) using the machine-learning technique of data-driven dominant balance. We aim to automate the identification of which particular physical processes drive propagation in different regimes, a task usually performed using intuition and comparison with asymptotic limits. We first apply the method to interpret known analytic results describing Akhmediev breather, Kuznetsov-Ma, and Peregrine soliton (rogue wave) structures, and show how we can automatically distinguish regions of dominant nonlinear propagation from regions where nonlinearity and dispersion combine to drive the observed spatio-temporal localization. Using numerical simulations, we then apply the technique to the more complex case of noise-driven spontaneous modulation instability, and show that we can readily isolate different regimes of dominant physical interactions, even within the dynamics of chaotic propagation., (© 2023. The Author(s).)

We report multipass broadband photoacoustic spectroscopy of trace gases in the mid-infrared. The measurement principle of the sensor relies on supercontinuum-based Fourier transform photoacoustic spectroscopy (FT-PAS), in which a scanning interferometer modulates the intensity of a mid-infrared supercontinuum light source and a cantilever microphone is employed for sensitive photoacoustic detection. With a custom-built external Herriott cell, the supercontinuum beam propagates ten times through a miniature and acoustically non-resonant gas cell. The performance of the FT-PAS system is demonstrated by measuring the fundamental C-H stretch bands of various hydrocarbons. A noise equivalent detection limit of 11 ppb is obtained for methane (40 s averaging time, 15 μW cm -1 incident power spectral density, 4 cm -1 resolution), which is an improvement by a factor of 12 compared to the best previous FT-PAS systems. High linearity and good stability of the sensor provide reliable identification of individual species from a gas mixture with strong spectral overlap, laying the foundation for sensitive and selective multi-species detection in small sample volumes.

We show using numerical simulations that data driven discovery using sparse regression can be used to extract the governing differential equation model of ideal four-wave mixing in a nonlinear Schrödinger equation optical fibre system. Specifically, we consider the evolution of a strong single frequency pump interacting with two frequency detuned sidebands where the dynamics are governed by a reduced Hamiltonian system describing pump-sideband coupling. Based only on generated dynamical data from this system, sparse regression successfully recovers the underlying physical model, fully capturing the dynamical landscape on both sides of the system separatrix. We also discuss how analysing an ensemble over different initial conditions allows us to reliably identify the governing model in the presence of noise. These results extend the use of data driven discovery to ideal four-wave mixing in nonlinear Schrödinger equation systems., (© 2022. The Author(s).)

Neural networks have been recently shown to be highly effective in predicting time-domain properties of optical fiber instabilities based only on analyzing spectral intensity profiles. Specifically, from only spectral intensity data, a suitably trained neural network can predict temporal soliton characteristics in supercontinuum generation, as well as the presence of temporal peaks in modulation instability satisfying rogue wave criteria. Here, we extend these previous studies of machine learning prediction for single-pass fiber propagation instabilities to the more complex case of noise-like pulse dynamics in a dissipative soliton laser. Using numerical simulations of highly chaotic behaviour in a noise-like pulse laser operating around 1550 nm, we generate large ensembles of spectral and temporal data for different regimes of operation, from relatively narrowband laser spectra of 70 nm bandwidth at the -20 dB level, to broadband supercontinuum spectra spanning 200 nm at the -20 dB level and with dispersive wave and long wavelength Raman extension spanning from 1150-1700 nm. Using supervised learning techniques, a trained neural network is shown to be able to accurately correlate spectral intensity profiles with time-domain intensity peaks and to reproduce the associated temporal intensity probability distributions.

The generation of a two-octave supercontinuum from the visible to mid-infrared (700-2800 nm) in a non-silica graded-index multimode fiber is reported. The fiber design is based on a nanostructured core comprised of two types of drawn lead-bismuth-gallate glass rods with different refractive indices. This yields an effective parabolic index profile and ten times increased nonlinearity when compared to silica fibers. Using femtosecond pulse pumping at wavelengths in both normal and anomalous dispersion regimes, a detailed study is carried out into the supercontinuum generating mechanisms and instabilities seeded by periodic self-imaging. Significantly, suitable injection conditions in the high power regime are found to result in the output beam profile showing clear signatures of beam self-cleaning from nonlinear mode mixing. Experimental observations are interpreted using spatio-temporal 3+1D numerical simulations of the generalized nonlinear Schrödinger equation, and simulated spectra are in excellent agreement with experiment over the full two-octave spectral bandwidth. Experimental comparison with the generation of supercontinuum in a silica graded-index multimode fiber shows that the enhanced nonlinear refractive index of the lead-bismuth-gallate fiber yields a spectrum with a significantly larger bandwidth. These results demonstrate a new pathway towards the generation of bright, ultrabroadband light sources in the mid-infrared., (© 2022. The Author(s).)

We present an erratum to our Letter [Opt. Lett.47, 802 (2022)10.1364/OL.448571]. This erratum corrects an error in the sign of one of the higher-order dispersion coefficient used in the simulations of Figs. 2 and 4, as well as in Figs. S1 and S3. The simulations in the original Letter were performed using the correct value, and therefore this correction does not affect any of the results and conclusions of the original Letter.

We investigate the noise transfer mechanism from the light source intensity fluctuations to the acoustic signal in Fourier transform photoacoustic spectroscopy (FT-PAS). This noise coupling is expected to be reduced in FT-PAS compared with conventional Fourier transform spectroscopy, as only the specific spectral components that are absorbed by the probed sample contribute to the noise level. We employ an incoherent supercontinuum (SC) light source in our experiments and observe a linear relation between the sample gas concentration and the detected noise level, which significantly reduces the influence of the SC noise on the detection limit. Based on our experimental results, we derive a model for the noise level, which establishes the foundation for practical sensitive implementation of FT-PAS.

Understanding dynamical complexity is one of the most important challenges in science. Significant progress has recently been made in optics through the study of dissipative soliton laser systems, where dynamics are governed by a complex balance between nonlinearity, dispersion, and energy exchange. A particularly complex regime of such systems is associated with noise-like pulse multiscale instabilities, where sub-picosecond pulses with random characteristics evolve chaotically underneath a much longer envelope. However, although observed for decades in experiments, the physics of this regime remains poorly understood, especially for highly-nonlinear cavities generating broadband spectra. Here, we address this question directly with a combined numerical and experimental study that reveals the physical origin of instability as nonlinear soliton dynamics and supercontinuum turbulence. Real-time characterisation reveals intracavity extreme events satisfying statistical rogue wave criteria, and both real-time and time-averaged measurements are in quantitative agreement with modelling., (© 2021. The Author(s).)