Tunable dual-comb spectrometer for mid-infrared trace gas analysis from 3 to 4.7 µm

High-sensitivity dual-comb and cross-comb spectroscopy across the infrared using a widely tunable and free-running optical parametric oscillator

Dual-comb spectroscopy (DCS) enables high-resolution measurements at high speeds without the trade-off between resolution and update rate inherent to mechanical delay scanning. However, high complexity and limited sensitivity remain significant challenges for DCS systems. We address these via a wavelength-tunable dual-comb optical parametric oscillator (OPO) combined with an up-conversion detection method. The OPO is tunable from 1300-1670 nm (signal) and 2700-5000 nm (idler). Spatial multiplexing in both the laser and OPO cavities creates a near-common path arrangement, enabling comb-line-resolved measurements in free-running operation. The narrow instantaneous bandwidth results in high power per comb-line up to 160 μW in the mid-infrared. Through intra-cavity up-conversion based on cross-comb spectroscopy, we leverage these power levels while overcoming the sensitivity limitations of direct mid-infrared detection. This approach yields a high signal-to-noise ratio (50.2 dB Hz1/2) and high dual-comb figure of merit (3.5 × 108 Hz1/2). This scheme enabled detecting ambient methane over a 3-meter path length in millisecond time scale.

Theory and experiment of transient two-wave mixing in Yb-doped single-frequency fiber amplifiers induced by frequency modulation

This paper presents a theoretical and experimental characterization of an instability phenomenon observed in single-frequency fiber amplifiers when the frequency of the seed laser is modulated. The instability manifests itself as fluctuating elastic back-reflections that occur only when the frequency is decreasing with time. The theory is a generalization of a coupled-mode model developed for a single-frequency fiber amplifier back-seeded with a constant frequency shift relative to the main signal. It can explain most observed features of the experiments in a qualitative and semi-quantitative way. Open questions and directions for further developments are also discussed.

Quartz-enhanced multiheterodyne resonant photoacoustic spectroscopy

The extension of dual-comb spectroscopy (DCS) to all wavelengths of light along with its ability to provide ultra-large dynamic range and ultra-high spectral resolution, renders it extremely useful for a diverse array of applications in physics, chemistry, atmospheric science, space science, as well as medical applications. In this work, we report on an innovative technique of quartz-enhanced multiheterodyne resonant photoacoustic spectroscopy (QEMR-PAS), in which the beat frequency response from a dual comb is frequency down-converted into the audio frequency domain. In this way, gas molecules act as an optical-acoustic converter through the photoacoustic effect, generating heterodyne sound waves. Unlike conventional DCS, where the light wave is detected by a wavelength-dependent photoreceiver, QEMR-PAS employs a quartz tuning fork (QTF) as a high-Q sound transducer and works in conjunction with a phase-sensitive detector to extract the resonant sound component from the multiple heterodyne acoustic tones, resulting in a straightforward and low-cost hardware configuration. This novel QEMR-PAS technique enables wavelength-independent DCS detection for gas sensing, providing an unprecedented dynamic range of 63 dB, a remarkable spectral resolution of 43 MHz (or ~0.3 pm), and a prominent noise equivalent absorption of 5.99 × 10-6 cm-1·Hz-1/2.

Electro-optic frequency comb based IPDA lidar: assessment of speckle issues

We present a theoretical, numerical and experimental assessment of the impact of speckle on a dual electro-optic frequency comb (EOFC) based system for integrated path differential absorption (IPDA) measurements. The principle of gas concentration measurements in a dual EOFC configuration in the absence of speckle is first briefly reviewed and experimentally illustrated using a C₂H₂ gas cell. A numerical simulation of the system performance in the presence of speckle is then outlined. The speckle-related error in the concentration estimate is found to be an increasing function of the product between the roughness of the backscattering surface and the EOFC line-spacing. As this product increases, the speckle-induced power fluctuations in the comb lines are no longer correlated to each other. To confirm this, concentration measurements are conducted using backscattered light from two different surfaces. Experiment results are in very good agreement with numerical simulations. Though detrimental for IPDA measurements, it is finally shown that decorrelation of speckle noise can be advantageously exploited for surface characterization in a dual EOFC configuration.

Rapid Quantitative Analysis of IR Absorption Spectra for Trace Gas Detection by Artificial Neural Networks Trained with Synthetic Data

Infrared absorption spectroscopy is a widely used tool to quantify and monitor compositions of gases. The concentration information is often retrieved by fitting absorption profiles to the acquired spectra, utilizing spectroscopic databases. In complex gas matrices an expanded parameter space leads to long computation times of the fitting routines due to the increased number of spectral features that need to be computed for each iteration during the fit. This hinders the capability of real-time analysis of the gas matrix. Here, an artificial neural network (ANN) is employed for rapid prediction of gas concentrations in complex infrared absorption spectra composed of mixtures of CO and N₂O. Experimental data is acquired with a mid-infrared dual frequency comb spectrometer. To circumvent the experimental collection of huge amounts of training data, the network is trained on synthetically generated spectra. The spectra are based on simulated absorption profiles making use of the HITRAN database. In addition, the spectrometer’s influence on the measured spectra is characterized and included in the synthetic training data generation. The ANN was tested on measured spectra and compared to a non-linear least squares fitting algorithm. An average evaluation time of 303 µs for a single measured spectrum was achieved. Coefficients of determination were 0.99997 for the predictions of N₂O concentrations and 0.99987 for the predictions of CO concentrations, with uncertainties on the predicted concentrations between 0.04 and 0.18 ppm for 0 to 100 ppm N₂O and between 0.05 and 0.18 ppm for 0 to 60 ppm CO.