Open Access
Add to BibSonomy
Abstract
We report on the design and automation of a mid-infrared, continuous wave, singly-resonant optical parametric oscillator. Hands-free controls and the implementation of a tuning algorithm allowed for hundreds of nanometers of continuous, effective-mode-hop-free tuning over the range of 2190-4000 nm. To demonstrate the applicability of this light source and algorithm to mid-IR spectroscopy, we performed a sample spectroscopy measurement in a C2H2 gas cell and compared the experimentally-measured absorption spectrum to HITRAN 2016 simulations. We found excellent agreement with simulation in both peak heights and peak centers; we also report a reduced uncertainty in peak centers compared to simulation.
© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
Mid-infrared molecular spectroscopy is a technique that has applications in a variety of fields, including: astronomy and cosmology [1], combustion [2,3], climate science [4], defense applications [5], quantum technology [6,7], and others. All of these uses are motivated by the high density of fundamental vibrational transitions in this spectral region, often referred to as the "fingerprint region". As a result, considerable effort has been made for several decades to develop a suitable mid-infrared light source for these spectroscopic studies. Most experiments benefit from (1) high spectral power density, (2) broad spectral coverage, and (3) fine spectral resolution. Available mid-IR sources are usually able to meet one or two of these requirements, but rarely all three. For example, Fourier transform infrared spectroscopy (FTIR) is broadband (hundreds of cm$^{-1}$), but is limited by low resolution (typical resolution of $\sim 10^{-2}$ cm$^{-1}$) or low signal-to-noise [8]. Quantum cascade lasers, on the other hand, have high spectral power density, but have small tuning ranges, poor beam quality, and substantial frequency noise [9]. Frequency combs offer the best combination of spectral coverage and resolution, but so far mid-infrared combs have average powers at the mW-level, or are available in limited ranges [10–13].
Continuous wave optical parametric oscillators (cw-OPOs) show promise to fulfill all three requirements simultaneously, because they have a narrow linewidth, high output power, and can be tuned many hundreds of nm by changing the phase-matching conditions in the nonlinear crystal [14,15]. In practice, reliable implementation of cw-OPOs has proven difficult, primarily because of frequent and unpredictable mode hops that are characteristic in such systems. Synchronous wavelength monitoring and automated tuning algorithms are required for these systems in order to achieve mode-hop-free tuning. A previous implementation of automated tuning achieved fully hands-free operation from a manually-tuned cw OPO, by constructing external hands-free actuators of manual tuning devices [16]. To build off of this result, we built a cw-OPO with fully-integrated, hands-free tuning actuators and developed our own automated tuning algorithm for this new device. Our algorithm, compared to previous implementations, resulted in faster, more reproducible tuning over longer ranges. We verified the algorithm functionality by performing a representative spectroscopy measurement.
2. Experimental setup
2.1 OPO design and characteristics
The OPO system (TOPTICA DLC TOPO) consisted of a distributed feedback diode laser (TOPTICA DFB pro BFY) and a fiber amplifier (FA), which produced 10 W of cw light. The output of the FA, referred to as the pump, was centered at $\lambda _P = 1064$ nm and was tunable by $\sim 4$ nm (35 cm$^{-1}$). The pump was focused into a singly-resonant OPO cavity (SRO). The design of the SRO was similar to that described in Ref. [17]. The ring cavity design included a nonlinear crystal positioned at the pump waist. The nonlinear crystal was quasi-phase matched in a fanout configuration for parametric oscillation over a range of signal and idler wavelengths, $\lambda _S$ and $\lambda _I$ respectively. These wavelengths were determined by repositioning the nonlinear crystal to change the phase matching. The three wavelengths were related by the conservation of energy relation
where all wavelengths are defined in vacuum. The signal was tunable from 1450-2070 nm, and the corresponding idler range was 2190-4000 nm. In addition to the position of the crystal, the values of $\lambda _S$ and $\lambda _I$ were determined by the settings of several other tuning parameters, described in Sec. 2.3.All cavity mirrors were coated for high transmission of the pump and idler wavelengths, which both exited the cavity after a single pass. Three of the cavity windows were coated for high reflection of the signal wavelength range, which was resonant inside the cavity. Unlike Ref. [17], one of the cavity windows was a partially-transmitting output coupler for the signal beam, enabling Watt levels of both signal and idler to be coupled out of the cavity, albeit with a higher threshold power. Typical cavity finesse was around 200, although this varied slightly as the output wavelengths were tuned. Powers in excess of 1 W were generated over most of the tuning range; a characteristic tuning curve (output power vs. wavelength) is shown in Fig. 1(a).
Fig. 1. (a) Characteristic tuning curve (power vs wavelength) for the TOPO. (b) Linewidth measurements of the pump (left), signal (center), and idler (right). Experimental measurements are shown as points, and the solid lines show a fit of the data to a Voigt lineshape. The pump (signal) linewidths were measured by beating the TOPO output with a frequency comb at 1064 nm (1566 nm). The inset shows the same signal beat over a frequency offset range of -100 to 100 kHz. The bottom right plot is a beat of two TOPO idlers to each other at 3319 nm.
We found that the TOPO was passively stable against acoustic vibrations and thermal drifts. The DFB and FA were both all-fiber, leading to a highly-stable pump beam. The OPO cavity was a monolithic aluminum block, that was kinematically coupled to the laser baseplate (also solid aluminum) [18]. Thermal drifts were managed by stabilizing both the cavity and crystal temperatures to mK accuracy using PID controllers. We measured an RMS intensity noise of 0.15%, integrated over the range of 10 Hz to 10 MHz. Pointing stability of the signal and idler were both $< 10$ $\mu$rad RMS over one hour monitoring time (after one hour of system warmup).
Linewidth measurements are shown in Fig. 1(b). We measured the signal and pump linewidths by beating the TOPO output with a 1550 nm frequency comb (TOPTICA DFC CORE+) and a 1064 nm extension (TOPTICA DFC EXT), respectively. Both the comb and the comb extension were free running during our linewidth measurements. For the pump measurement, the DFC EXT had a free-running linewidth of $<50$ kHz. Using a Voigt fit, we obtained a full width at half maximum (FWHM) beat width of $\sim$1 MHz with 25 ms acquisition time. Since this value was much larger than the linewidth of the comb, we neglected the comb’s contribution to the beat width and attributed an $\sim$1 MHz FWHM linewidth to the pump.
During the signal linewidth measurement, the DFC CORE+ had a free-running linewidth of $<30$ kHz at 1566 nm. Our measured beat note (Voigt fit) was $\sim$30 kHz FWHM with 40 ms acquisition time, implying that the TOPO signal linewidth is no broader than 30 kHz. Given the much smaller signal linewidth compared to the pump linewidth, we concluded that our resonant cavity acts as a spectral purifier, in some ways analogous to a laser pumped by incoherent light. This spectral purification is possible so long as the pump laser linewidth is within the phase-matching bandwidth of the nonlinear crystal. As a consequence of the spectral purification of the pump radiation by the resonant cavity, we expected that the excess frequency noise of the pump source would be transferred to frequency noise of the idler [19].
To measure the idler linewidth, we beat the idler outputs of two identical TOPOs at a wavelength of 3319 nm. Both pumps (signals) had been characterized previously to have FWHM linewidths of $\sim$1 MHz ($30$ kHz). A Voigt fit of the two-idler beat recovered a width of 2.5 MHz FWHM with 25 ms acquisition time. Assuming that the pump, signal, and idler linewidths of both TOPOs are identical, this suggests an idler linewidth of 1-2 MHz at 25 ms acquisition time. Therefore, we confirm that the pump frequency noise (and as such its linewidth) is transferred to the idler output of the TOPO.
2.2 Spectroscopy setup
The experimental design is shown in Fig. 2. The pump and signal outputs were attenuated and sent to a wavemeter (HighFinesse WS6-200 Vis/IR-II) with a two-channel fiber switch at its input. The wavemeter measured both wavelengths simultaneously with a sample rate of $\sim 100$ Hz, and an absolute accuracy (resolution) of 200 MHz (10 MHz). From these measurements, the idler wavelength was calculated using Eq. (1).
Fig. 2. Spectroscopy experimental setup. A distributed feedback diode laser (DFB pro BFY) was amplified using an Yb fiber amplifier (FA) and used to pump an optical parametric oscillator cavity (TOPO head). The signal and pump output of the TOPO were attenuated and directed to a wavemeter with a two-channel switch (2C-WLM). Portions of the Watt-level idler output were picked off by two CaF$_2$ windows. The remainder of the idler power was dumped onto a thermal power meter (PM) which was used for idler power monitoring. One beam pickoff passed through the C$_2$H$_2$ / CH$_4$ gas cell, and the transmitted power was monitored by photodiode PD1. The other pickoff was directed to photodiode PD2. The full system was controlled with a PC and a digital laser controller (DLC pro).
The idler output was directed through two wedged CaF$_2$ windows, which each provided a Fresnel reflection of $\sim 0.5$% per surface. The remaining idler beam was dumped on a thermal power meter head to monitor the idler output power. One of the Fresnel pickoffs was guided through the gas cell and onto a photodiode (Thorlabs PDAVJ8, labeled PD1 in Fig. 2). The gas cell was a free-space absorption cell from Wavelength References, 20 cm long and filled with C$_2$H$_2$ and CH$_4$, each at 10 Torr partial pressure at room temperature ($23^{\circ }$C). The second pickoff arm was guided to a second photodiode (Thorlabs PDAVJ8, labeled PD2 in Fig. 2). This photodiode measured the reference signal. The path length in air of the two pickoff beam paths was set to be equal so that atmospheric absorptions (primarily water and CO$_2$) could be normalized out of the final measurement.
2.3 Automated tuning
The chief impediment to developing automated tuning algorithms in cw SROs is that most prior idler wavelength tuning methods included hand-adjusted screws and actuators. The TOPO design uses hands-off controls for all tuning parameters, including motorized or piezo-driven actuators for motion control. However, there are other issues that limit the effectiveness of tuning algorithms, even after all tuning "knobs" have been made hands-free: (1) cw OPOs have a large number of these tuning mechanisms, which define a high-dimensional parameter space that must be optimized or searched through, and (2) OPOs exhibit non-deterministic mode hops.
The tuning mechanisms available in the TOPO are shown in Table 1, along with their resolutions and tuning ranges. Each tuning mechanism acted on two of the three wavelengths (pump, signal, and idler) while the third was held constant. The position of the nonlinear crystal in the cavity and the rotation angle of the intracavity etalon (ICE) are referred to as "coarse" tuning mechanisms. The nonlinear crystal was mounted in an oven of our own design and translated using a commercially-obtained linear piezo stage. A commercial servo motor was used to rotate the etalon in steps of $\sim 50$ mrad. By using these two parameters in concert, the signal and idler wavelengths could be tuned across their full ranges in steps of $\sim 30$ GHz. This tuning was very consistent and repeatable due to the mechanical and thermal stability of the cavity. A given set of crystal and ICE positions produced the same signal and idler wavelengths (within a few GHz) for many months.
Table 1. Tuning methods in the TOPTICA DLC TOPO.
The other tuning methods are referred to as "fine" tuning mechanisms; they had much finer resolution but typically worked over a narrower tuning range. The nonlinear crystal temperature was monitored by an integrated thermistor in the crystal oven and maintained to mK accuracy by a PID controller in the DLC pro. The temperature of the DFB pro BFY seed laser was tuned using a similar PID controller acting on a peltier, which was attached to the DFB diode package. The seed laser current was adjusted using the integrated current controller in the DLC pro. In the OPO head, one of the four cavity mirrors was mounted on a piezoelectric stack, which allowed for fine tuning of the signal and idler by precise changes in the cavity length.
In this work, we used the DFB pro BFY seed laser temperature as our fine tuning mechanism due to its relatively high resolution and the broadest possible tuning range. The other three fine tuning parameters were fixed during the experiment. The tuning range of the seed laser temperature was $>30$ GHz, which means that it could fill in the "gaps" in wavelength coverage from the crystal position and ICE angle alone. Our DFB had a temperature tuning coefficient of 22.8 GHz/K. The DLC pro temperature controller stabilized the DFB temperature to less than 1 mK, which means the pump frequency was stable to $\sim 10$ MHz. Passive frequency stability could be improved by locking the seed laser to an external reference (such as a wavemeter or absorption line), but we did not do so in this experiment. Temperature scanning was continuous, so our scan resolution was limited by the measurement resolution of the wavemeter (also 10 MHz).
These three tuning mechanisms suggest an effective algorithm for automated tuning; namely, adjust the crystal and etalon to move the idler by 30 GHz per step, then tune the seed laser temperature to fill in the 30 GHz gaps continuously and with high resolution. We regulated and stabilized all other tuning methods during this scan to prevent drifts. The TOPO was stable against mode hops in a steady state, typically running several days without a single mode hop. However, mode hops were much more frequent when scanning the seed laser temperature, and so there is no guarantee that the temperature scan would fill in the gaps from motor/etalon tuning. Although our system was capable of 30 GHz mode-hop-free tuning at any starting wavelength, this was only true if the system performance (i.e., output power) was optimized at that given wavelength. In practice, this meant that we had to adjust the intracavity piezo voltage via a guess-and-check method in order to optimize the TOPO output power for a given set of crystal/ICE positions. As this piezo adjustment process was not easily automatable, avoiding or accounting for mode hops less than 30 GHz apart was necessary to avoid gaps in the output data.
These gaps in the spectroscopic data were filled one at a time: rather than avoiding mode hops altogether, our algorithm relied on the high acquisition rate and accuracy of a wavemeter to detect and respond to mode hops as quickly as possible. We refer to this as a "scan-and-stitch" method; the TOPO scanned the idler until a mode hop was detected, then "stitched" back to the wavelength just before the mode hop and continued with a new scan.
The algorithm required as input a lookup table (LUT) of idler wavelengths and their corresponding crystal positions and ICE angles. We generated a LUT with entries spaced by $\sim 30$ GHz. The algorithm started in the "stitch" phase; it loaded the LUT entry closest to the start wavelength of the scan (this start wavelength was entered by the user). When the crystal and ICE positions were loaded and stabilized, the seed laser temperature was ramped to match the idler wavelength to within 100 MHz of the set point. Once this start condition was met, the "scan" phase began. At each point in the scan, the seed laser temperature was incremented by 0.44 mK, calculated to produce a change in idler frequency of 10 MHz. The idler wavelength was measured by the wavemeter and spectroscopic data were collected. As long as the change in idler wavelength from point to point was $\sim$10 MHz, the scan continued. Larger jumps in idler wavelength ($> 1$ GHz in our experiment) indicated a mode hop of the signal. In this case, the algorithm returned to the "stitch" phase, using the last wavelength before the mode hop as the new start wavelength. This scan-and-stitch process continued until reaching the end wavelength set by the user. The total range of the scan-and-stitch tuning method is only limited by the idler tuning range of the TOPO (2190-4000 nm).
3. Results and discussion
To demonstrate the broadly-tunable, continuous, effectively mode hop-free scans possible with our system, we ran a sample scan from 2907 to 3130 nm (3195-3440 cm$^{-1}$) in 838,140 points, at a scanning speed of $\sim$6 points per second. Our average step size was $8.8 \pm 7.6$ MHz. The step size error is expected due to the resolution of the wavemeter we used in the experiment. There were 270 mode hops during the scan, and as a result we recorded 271 individual continuous scans during the measurement. Individual scans reached up to 21.2 cm$^{-1}$ in length. The stitches were successful at lining up successive scans; there were no gaps in the spectral data of more than 1 GHz, and $>99.9$% of gaps were less than $30$ MHz.
During the scan, we simultaneously measured the absorption of the $\nu _3$ asymmetric stretch mode in gaseous C$_2$H$_2$, centered around 3300 cm$^{-1}$ [20,21]. The full spectroscopy result is shown in Fig. 3. Each of the 271 individual continuous segments was referenced to the background and normalized individually. Other than normalization to the background measurement, we performed no other treatment on the data of Fig. 3.
Fig. 3. Full-range absorption (normalized) vs wavenumber for direct absorption spectroscopy measurement on the $\nu _3$ stretching mode of C$_2$H$_2$.
In Fig. 4, we show a subset of Fig. 3, from 3195.5-3216.5 cm$^{-1}$. Over this subset, we compared the experimentally-measured spectrum (blue solid line) with a simulated spectrum based off of HITRAN 2016 data [22], using a nonlinear least-squares multispectral fitting software to produce forward models [23]. The full spectrum was calculated simultaneously at experimental conditions (e.g., pressure, temperature), using Voigt lineshapes. The simulated spectrum is not shown directly, but the residual is shown on the same plot as the experimental spectrum (red dotted line, shifted by -0.1 norm. units for ease of viewing). The quantum number assignments for the reported lines can be found in Ref. [21]. We defined two groups of lines, based on the uncertainty of the line positions reported by HITRAN. The first group consisted of 14 peaks with an uncertainty of $10^{-3}$ cm$^{-1}$, and the second group consisted of 64 peaks with an uncertainty of $10^{-2}$ cm$^{-1}$.
Fig. 4. (Top) Inset of Fig. 3 over the range 3195.5 - 3216.5 cm$^{-1}$. The blue solid line is the experimental measurement. The red dotted line is the residual of experimental data with HITRAN-based simulation (shifted by -0.1 norm. units). (Bottom) Peak offset $\Delta \nu _j$ vs wavenumber for all the peaks identified in HITRAN. The open orange circles are peaks that HITRAN reports with an uncertainty of 0.001 cm$^{-1}$. The filled black squares are the peaks that HITRAN reports with an uncertainty of 0.01 cm$^{-1}$. The gray bar across the center extends $\pm$0.002 cm$^{-1}$; it is meant to show the HITRAN $2\sigma$ uncertainty window for the orange-colored peak centers.
In order to compare better with HITRAN, we recalibrated our frequency axis using the low-uncertainty HITRAN points. We applied a shift to our experimental spectrum (expected to be within the accuracy of our wavemeter), determined as follows: we first labeled these peaks with the index $j$, then defined the peak offset $\Delta \nu _j$ to be
where $\nu _j$ is the experimentally-measured center frequency of the $j$th peak and $\nu _j^H$ is the simulated center frequency of that same peak. We then applied a shift to $\nu _j$ that was the average peak offset of these low-uncertainty peaks; in other words, we shifted $\nu _j$ so that The necessary shift was calculated to be 0.0019 cm$^{-1}$ (57 MHz). A shift of this magnitude is expected in our experiment, because our wavemeter had an absolute accuracy of 0.0067 cm$^{-1}$. We do not expect a significant dependence of the shift on wavelength over the range we investigated, so we applied a uniform shift to the entire experimental spectrum.After the shift was applied, we plotted the peak offset $\Delta \nu _j$ vs wavenumber for the low-uncertainty peaks. These are shown as the open orange circles in the bottom plot of Fig. 4. We find that the standard deviation of peak offsets here is $1.35 \times 10^{-3}$ cm$^{-1}$, in good agreement with the reported HITRAN uncertainty of $10^{-3}$ cm$^{-1}$. Twelve of the fourteen peaks lie within the HITRAN $\pm 2\sigma$ uncertainty window, shown as the gray bar across the bottom plot of Fig. 4.
We also show the peak offset of the second group of peaks on the same figure. These 64 high-uncertainty peaks are shown as the solid black squares in Fig. 4. For this group, the HITRAN $\pm 2\sigma$ uncertainty window is larger than our plot range. In contrast, our experimentally-measured peaks were much more closely centered around zero offset. As a result of our measurement, we suggest a lowered uncertainty of $2 \times 10^{-3}$ cm$^{-1}$ in the reported HITRAN peak centers for this subset of peaks.
4. Conclusions and outlook
We have demonstrated a new automated tuning algorithm for a cw-OPO, enabled by our rigid and hands-free OPO design. By leveraging the control of all tuning parameters via a PC and laser controller, we have shown that we can perform scans of hundreds of nanometers, in a way that is robust against unexpected mode hops. These continuous scans were limited in resolution only by the resolution of our wavemeter. This new technique offers great promise for substantially increasing the applicability of cw-OPOs to molecular spectroscopy experiments. By performing a sample measurement and comparing with HITRAN, we find that the TOPO and algorithm are already useful for verifying the HITRAN database and improving upon listed uncertainties.
There are several future improvements that we have in mind. We plan to improve the absolute accuracy of our measurement by stabilizing the TOPO to a frequency reference. With the pump, signal, and idler beat measurements already demonstrated here, there is a clear path forward towards locking any of the TOPO outputs given the availability of tuning parameters and locking solutions. In particular, locking the TOPO to a frequency comb can create a phase-coherent bridge to spectral ranges where direct frequency or phase measurement is unavailable or difficult [24]. The TOPO can be seeded with a narrow-linewidth pump source, which will result in a narrow-linewidth idler. This can improve the frequency resolution of a measurement, as well as simplify locking in some cases. We also plan to generate sidebands in our seed laser, which can transfer to the idler output to enable frequency modulation (FM) spectroscopy. Furthermore, we are investigating methods to up-convert the TOPO to the visible and ultraviolet spectral ranges using second/fourth/eighth harmonic generation, by leveraging existing technologies (TOPTICA SHG pro) [25,26]. The wavelength range covered by up-converted TOPO light would be much broader than the range from a single frequency-doubled or -quadrupled diode laser.
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
References
1. F. Cataldo, D. A. García-Hernández, and A. Manchado, “Far- and mid-infrared spectroscopy of complex organic matter of astrochemical interest: coal, heavy petroleum fractions and asphaltenes,” Mon. Not. R. Astron. Soc. 429(4), 3025–3039 (2013). [CrossRef]
2. C. S. Goldenstein, R. Spearrin, J. B. Jeffries, and R. K. Hanson, “Infrared laser-absorption sensing for combustion gases,” Prog. Energy Combust. Sci. 60, 132–176 (2017). [CrossRef]
3. W. Ren, A. Farooq, D. F. Davidson, and R. K. Hanson, “CO concentration and temeprature sensor for combustion gases using quantum-cascade laser absorption near 4.7 um,” Appl. Phys. B 107(3), 849–860 (2012). [CrossRef]
4. A. L. Gomez, J. Park, M. L. Walser, A. Lin, and S. A. Nizkorodov, “UV Photodissociation Spectroscopy of Oxidized Undecylenic Acid Films,” J. Phys. Chem. A 110(10), 3584–3592 (2006). [CrossRef]
5. M. W. Todd, R. A. Provencal, T. G. Owano, B. A. Paldus, A. Kachanov, K. L. Vodopyanov, M. Hunter, S. L. Coy, J. I. Steinfeld, and J. T. Arnold, “Application of mid-infrared cavity-ringdown spectroscopy to trace explosives vapor detection using a broadly-tunable (6-8 um) optical parametric oscillator,” Appl. Phys. B 75(2-3), 367–376 (2002). [CrossRef]
6. J. Ye, L.-S. Ma, and J. L. Hall, “Ultrasensitive detections in atomic and molecular physics: demonstration in molecular overtone spectroscopy,” J. Opt. Soc. Am. B 15(1), 6–15 (1998). [CrossRef]
7. D. DeMille, “Quantum Computation with Trapped Polar Molecules,” Phys. Rev. Lett. 88(6), 067901 (2002). [CrossRef]
8. H. Wang, X. Ma, Y. Wang, D. Chen, W. Chen, and Q. Li, “Enhancing the signal-to-noise ratio of FTIR spectrometers by a digital J-Stop,” Opt. Express 25(16), 19077–19082 (2017). [CrossRef]
9. S. Borri, S. Bartalini, P. C. Pastor, I. Galli, G. Giusfredi, D. Mazzotti, M. Yamanishi, and P. De Natale, “Frequency-Noise Dynamics of Mid-Infrared Quantum Cascade Lasers,” IEEE J. Quantum Electron. 47(7), 984–988 (2011). [CrossRef]
10. E. Baumann, F. R. Giorgetta, W. C. Swann, A. M. Zolot, I. Coddington, and N. R. Newbury, “Spectroscopy of the methane ${\nu }_3$ band with an accurate midinfrared coherent dual-comb spectrometer,” Phys. Rev. A 84(6), 062513 (2011). [CrossRef]
11. H. Timmers, A. Kowligy, A. Lind, F. C. Cruz, N. Nader, M. Silfies, G. Ycas, T. K. Allison, P. G. Schunemann, S. B. Papp, and S. A. Diddams, “Molecular fingerprinting with bright, broadband infrared frequency combs,” Optica 5(6), 727–732 (2018). [CrossRef]
12. S. Vasilyev, I. S. Moskalev, V. O. Smolski, J. M. Peppers, M. Mirov, A. V. Muraviev, K. Zawilski, P. G. Schunemann, S. B. Mirov, K. L. Vodopyanov, and V. P. Gapontsev, “Super-octave longwave mid-infrared coherent transients produced by optical rectification of few-cycle 2.5-µm pulses,” Optica 6(1), 111–114 (2019). [CrossRef]
13. A. S. Kowligy, H. Timmers, A. J. Lind, U. Elu, F. C. Cruz, P. G. Schunemann, J. Biegert, and S. A. Diddams, “Infrared electric field sampled frequency comb spectroscopy,” Sci. Adv. 5(6), eaaw8794 (2019). [CrossRef]
14. M. Vainio and L. Halonen, “Mid-infrared optical parametric oscillators and frequency combs for molecular spectroscopy,” Phys. Chem. Chem. Phys. 18(6), 4266–4294 (2016). [CrossRef]
15. M. Vainio, J. Peltola, S. Persijn, F. J. M. Harren, and L. Halonen, “Singly resonant cw OPO with simple wavelength tuning,” Opt. Express 16(15), 11141–11146 (2008). [CrossRef]
16. A. M. Morrison, T. Liang, and G. E. Douberly, “Automation of an "Aculight" continuous-wave optical parametric oscillator,” Rev. Sci. Instrum. 84(1), 013102 (2013). [CrossRef]
17. A. Henderson and R. Stafford, “Low-threshold, singly-resonant CW OPO pumped by an all-fiber pump source,” Opt. Express 14(2), 767–772 (2006). [CrossRef]
18. L. C. Hale and A. H. Slocum, “Optimal design techniques for kinematic coupling,” Precis. Eng. 25(2), 114–127 (2001). [CrossRef]
19. A. Ly, C. Siour, and F. Bretenaker, “30-Hz relative linewidth watt output power 1.65 µm continuous-wave singly resonant optical parametric oscillator,” Opt. Express 25(8), 9049–9060 (2017). [CrossRef]
20. T. Shimanouchi, Tables of Molecular Vibrational Frequencies Consolidated Volume I (United States Department of Commerce, 1972).
21. J. V. Auwera, D. Hurtmans, M. Carleer, and M. Herman, “The ν3 fundamental in C2H2,” J. Mol. Spectrosc. 157(2), 337–357 (1993). [CrossRef]
22. I. Gordon, L. Rothman, C. Hill, R. Kochanov, Y. Tan, P. Bernath, M. Birk, V. Boudon, A. Campargue, K. Chance, B. Drouin, J.-M. Flaud, R. Gamache, J. Hodges, D. Jacquemart, V. Perevalov, A. Perrin, K. Shine, M.-A. Smith, J. Tennyson, G. Toon, H. Tran, V. Tyuterev, A. Barbe, A. Császár, V. Devi, T. Furtenbacher, J. Harrison, J.-M. Hartmann, A. Jolly, T. Johnson, T. Karman, I. Kleiner, A. Kyuberis, J. Loos, O. Lyulin, S. Massie, S. Mikhailenko, N. Moazzen-Ahmadi, H. Müller, O. Naumenko, A. Nikitin, O. Polyansky, M. Rey, M. Rotger, S. Sharpe, K. Sung, E. Starikova, S. Tashkun, J. V. Auwera, G. Wagner, J. Wilzewski, P. Wcislo, S. Yu, and E. Zak, “The HITRAN2016 molecular spectroscopic database,” J. Quant. Spectrosc. Radiat. Transfer 203, 3–69 (2017). [CrossRef]
23. D. Benner, C. P. Rinsland, V. Devi, M. A. H. Smith, and D. Atkins, “A multispectrum nonlinear least squares fitting technique,” J. Quant. Spectrosc. Radiat. Transfer 53(6), 705–721 (1995). [CrossRef]
24. E. V. Kovalchuk, T. Schuldt, and A. Peters, “Combination of a continuous-wave optical parametric oscillator and a femtosecond frequency comb for optical frequency metrology,” Opt. Lett. 30(23), 3141–3143 (2005). [CrossRef]
25. U. Eismann, M. Enderlein, K. Simeonidis, F. Keller, F. Rohde, D. Opalevs, M. Scholz, W. Kaenders, and J. Stuhler, “Active and passive stabilization of a high-power violet frequency-doubled diode laser,” in Conference on Lasers and Electro-Optics, p. JTu5A.65 (Optical Society of America, 2016).
26. U. Eismann, M. Scholz, T. Paasch-Colberg, and J. Stuhler, “Short, shorter, shortest: Diode lasers in the deep ultraviolet,” Laser Focus World 52(6), 39–44 (2016).
