Our research should be seen in the light of the worldwide increase of antimicrobial resistance (AMR), which is a serious threat to human health. To prevent the spread of AMR, fast reliable diagnostics tools that facilitate optimal antibiotic stewardship are of urgent need. Raman spectroscopy (RS) is a promising tool for rapid label- and culture-free identification and antimicrobial susceptibility testing (AST) in a single step. To take full advantage of RS for bacterial identification machine learning (ML) analysis is essential. Many limitations must be addressed before RS will be a practical platform for point-of-care diagnostics applications in clinics and hospitals. RS is sensitive to factors such as the growth stage, changes in measurement environment and inconsistency in sample preparation. We address the issues of sample preparation, changes in measurement environment and limited data availability. We reduce sample preparation to merely transferring the bacteria to the measurement environment, hereby minimizing the issue of sample inconsistency and the additional benefit of removing sample preparation. To alleviate the situation of limited data availability for ML model training, we have developed a novel spectral transformer (ST) ML model that is efficient after training on both small- and large RS bacteria datasets. We explicit demonstrated that our ST outperforms a state-of-the-art domain-specific residual CNN both in terms of accuracy with 7.5%. Where we attain more than 96% classification accuracy on a dataset consisting of 15 different classes and 95.6% classification accuracy for six MR–MS bacteria species.
Quantum frequency conversion, the process of shifting the frequency of an optical quantum state while preserving quantum coherence, can be used to produce non-classical light at otherwise unapproachable wavelengths. We present experimental results based on highly efficient sum-frequency generation (SFG) between a vacuum squeezed state at 1064 nm and a tunable pump source at 850 nm ± 50 nm for the generation of bright squeezed light at 472 nm ± 4 nm. We demonstrate that the SFG process conserves part of the quantum coherence as a 4.2(±0.2) dB 1064 nm vacuum squeezed state is converted to a 1.6(±0.2) dB tunable bright blue squeezed state.
In the QuantERA project QURAMAN (Quantum Raman) are we aiming for a combination of breakthroughs and improvements of existing components and already existing setups for building a commercial quantum Raman microscope. By combining the project partners’ expertise and skills in quantum optics, nonlinear optics, Raman spectroscopy and medical device design we will develop the next-generation Raman microscope for bio-imaging with quantum-enhanced sensitivity. The background knowledge and idea behind the QuRAMAN project is described in our recent publications (Optica 7, 470-475 (2020)). Where we have demonstrated that the use of continuous wave (CW) squeezed light can improve the SNR of weak Raman signals. However, to beat the performance of state-of-the-art SRS microscopes by means of squeezed light, one must employ amplitude squeezed picosecond pulses in a strongly focusing configuration (using an objective with a numerical aperture above unity). This will enable the imaging of weak Raman features and will push the Raman technology beyond the state of the art by applying pulsed amplitude squeezed light for signal enhancement.
Stimulated Raman spectroscopy has become a powerful tool to study the spatio-dynamics of molecular bonds with high sensitivity, resolution, and speed. However, the sensitivity and speed of stimulated Raman spectroscopy are ultimately limited by the shot-noise of the light beam probing the Raman process. Here, we demonstrate an enhancement of the sensitivity of stimulated Raman spectroscopy by reducing the noise below the shot-noise limit by means of squeezed states of light. Our demonstration constitutes the first step towards a new generation of quantum-enhanced Raman microscopes.
A photoacoustic (PA) sensor for spectroscopic measurements of NO2-N2 at ambient pressure and temperature is demonstrated. The PA sensor is pumped resonantly by a nanosecond pulsed single-mode mid-infrared (MIR) optical parametric oscillator (OPO). Spectroscopic measurements of NO2-N2 in the 3.25 μm to 3.55 μm wavelength region with a resolution bandwidth of 5 cm-1 and with a single shot detection limit of 1.6 ppmV (μmol/mol) is demonstrated. The measurements were conducted with a constant flow rate of 300 ml/min, thus demonstrating the suitability of the gas sensor for real time trace gas measurements. The acquired spectra is compared with data from the Hitran database and good agreement is found. An Allan deviation analysis shows that the detection limit at optimum integration time for the PAS sensor is 14 ppbV (nmol/mol) at 170 seconds of integration time, corresponding to a normalized noise equivalent absorption (NNEA) coefficient of 3.3×10-7 W cm-1 Hz-1/2.
A photoacoustic (PA) sensor for fast and real-time gas sensing is demonstrated. The PA cell has been designed for flow noise immunity using computational fluid dynamics (CFD) analysis. PA measurements were conducted at different flow rates by exciting molecular C-H stretch vibrational bands of hexane (C6H14) in clean air at 2950cm-1 (3.38 μm) with a custom made mid-infrared interband cascade laser (ICL). The PA sensor will contribute to solve a major problem in a number of industries using compressed air by the detection of oil contaminants in high purity compressed air. We observe a (1σ, standard deviation) sensitivity of 0.4 ±0.1 ppb (nmol/mol) for hexane in clean air at flow rates up to 2 L/min, corresponding to a normalized noise equivalent absorption (NNEA) coefficient of 2.5×10-9 W cm-1 Hz1/2, thus demonstrating high sensitivity and fast and real-time gas analysis. The PA sensor is not limited to molecules with C-H stretching modes, but can be tailored to measure any trace gas by simply changing the excitation wavelength (i.e. the laser source) making it useful for many different applications where fast and sensitive trace gas measurements are needed.
An innovative and novel quartz-enhanced photoacoustic spectroscopy (QEPAS) sensor for highly sensitive and selective breath gas analysis is introduced. The QEPAS sensor consists of two acoustically coupled micro- resonators (mR) with an off-axis 20 kHz quartz tuning fork (QTF). The complete acoustically coupled mR system is optimized based on finite element simulations and experimentally verified. Due to the very low fabrication costs the QEPAS sensor presents a clear breakthrough in the field of photoacoustic spectroscopy by introducing novel disposable gas chambers in order to avoid cleaning after each test. The QEPAS sensor is pumped resonantly by a nanosecond pulsed single-mode mid-infrared optical parametric oscillator (MIR OPO). Spectroscopic measurements of methane and methanol in the 3.1 μm to 3.7 μm wavelength region is conducted. Demonstrating a resolution bandwidth of 1 cm-1. An Allan deviation analysis shows that the detection limit at optimum integration time for the QEPAS sensor is 32 ppbv@190s for methane and that the background noise is solely due to the thermal noise of the QTF. Spectra of both individual molecules as well as mixtures of molecules were measured and analyzed. The molecules are representative of exhaled breath gasses that are bio-markers for medical diagnostics.
Fluctuations in the field of a 2nd order nonlinear multi-mode parametric downcoverter exhibit nonclassical correlations in the transverse plane. We present results of measurements of the classical pattern for a degenerate, multi-mode parametric optical parametric oscillator (OPO) operating above threshold. We also present results of autocorrelation measurements of intensity fluctuations in the transverse plane both in the near field and in the far field with the OPO operating both below and above threshold -- a method we believe will ultimately enable us to display the nonclassical correlations of the OPO output.
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