Lumibird (France)

Abstract. Accurate estimation of second-order turbulence statistics using pulsed Doppler lidar has been a challenge for a long time, mainly due to the negative influence of probe volume averaging. The present study aims to investigate a novel approach to extracting first- and second-order turbulence statistics directly from the average Doppler spectra in the frequency domain. The main hypothesis is that averaging Doppler spectra over 10 min intervals can mitigate the influence of probe volume averaging and random noise in velocity retrievals, thereby improving estimates of velocity variance. To achieve this, we develop a new analytical model for the time-averaged Doppler spectrum, beginning with a theoretical formulation based on the beat signal within the range gate. The model is applied to 10 min averaged Doppler spectra collected by a pulsed lidar system pointing toward a sonic anemometer mounted on a meteorological mast in front of a Vestas V52 wind turbine at the DTU Risø campus in Denmark. Validation results demonstrate that the Doppler spectra model, when fitted to 400 ns nominal pulse durations, closely matches sonic anemometer measurements in both mean radial velocities and standard deviations. This agreement is quantified by the orthogonal least squares fit slopes of 0.976 for the mean velocities and 0.983 for the standard deviations. In comparison to the conventional time-domain approach, which accounts for only 72.1 % of the standard deviation, the proposed spectral method captures 98.3 % of the standard deviation observed in the sonic anemometer. However, this model does not accurately estimate variances using the short pulse (200 ns) of the instrument. Despite this limitation for the short pulse, the proposed method is an important step towards better turbulence estimation from pulsed Doppler lidars.

Abstract. Accurate estimation of second-order turbulence statistics using pulsed Doppler lidar has been a challenge for a long time, mainly due to the negative influence of probe volume averaging. The present study aims to investigate a novel approach to extracting first- and second-order turbulence statistics directly from the average Doppler spectra in the frequency domain. The main hypothesis is that averaging Doppler spectra over 10-minute intervals can mitigate the influence of probe volume averaging and random noise in velocity retrievals, thereby improving estimates of velocity variance. To achieve this, we develop a new analytical model for the time-averaged Doppler spectrum, beginning with a theoretical formulation based on the beat signal within the interrogation window. The model is applied to 10-minute averaged Doppler spectra collected by a pulsed lidar system pointing toward a sonic anemometer mounted on a meteorological mast in front of a Vestas V52 wind turbine at the DTU Risø campus in Denmark. Validation results demonstrate that the Doppler spectra model, when fitted to 400 ns nominal pulse durations, closely matches sonic anemometer measurements in both mean radial velocities and standard deviations. This agreement is quantified by the least orthogonal square fit slopes of 0.978 for the mean velocities and 0.967 for the standard deviations. In comparison to the conventional time-domain approach, which accounts for only 70.6 % of the standard deviation, the proposed spectral method captures 96.7 %, corresponding to an 88.7 % reduction in estimation loss. However, this model does not accurately estimate variances using the short pulse (200 ns) of the instrument. Despite this limitation for the short pulse, the proposed method is an important step towards better turbulence estimation from pulsed Doppler lidars.

Current models describing spin noise in interacting samples are based on an effective single particle dynamics in a bath. Here, we report the observation of a strong interaction regime which significantly affects the spin dynamics.

Graphene nanostructures, such as Graphene Quantum Dots (G-QDs), Graphene Nanoribbons (G-NRs) and Carbon Nanotubes (C-NTs), combine the unique mechanical and electronical transport properties of sp2- hybridized carbon materials and the optical properties of direct semiconductors provided by the optical gap resulting from the reduction of dimensionally. Here we use transient absorption of 30 fs temporal resolution with polarization-controlled configuration to probe the hot exciton relaxation (internal conversion, Sn→S1) in rectangular G-QDs of various lateral lengths. We selectively excite the different samples at the second optically active electronic transition and, thought the appearance of a photo-induced emission signal at the energy corresponding to the bandedge and red-shifted vibrational replica (i.e. at the position of the steady-state photoluminescence peaks), the dynamics of relaxation were unveiled. The resulting relaxation times range from 100 fs to 175 fs. These results allowed to discuss the mechanism of relaxation, with the effect of the length of the graphene nanoflakes and of the fluence excitation.

Thanks to the development of high power uni-travelling-carrier photodiodes, we studied optoelectronic oscillators architectures with optical gain. We compared the phase noise performances with two different optical amplifiers, based on erbium-doped fiber or semiconductor. Optical intensity noise is the main limitation for the phase noise, both at low and high offset frequencies. With a semiconductor optical amplifier, ultra-low phase noise is reached with equivalent performances from 8 to 15 GHz.

Averaging is a fundamental necessity for deep photoacoustic (PA) imaging when using low-energy pulsed laser sources or LED’s. Intrinsic (breathing, heartbeat…) or extrinsic (freehand probe guidance) tissue motion, however, leads to phase cancellation of the averaged PA signal when the axial displacement of tissue becomes larger than half the acoustic wavelength at the probe’s centre frequency. Motion-compensated averaging (DCA) is a solution to this problem, and allows the detection of deep structures that are else not visible. In a combined PA and echo-ultrasound (US) system, tissue motion can be quantified in US images that are interleaved with PA images. In this chapter, we exemplarily illustrate the power of this technique when trying to image the optical absorption inside the carotid artery, using a fully integrated PA/US system based on a handheld clinical probe containing a miniaturised laser source. The key components of DCA are discussed and exemplified on volunteer data, and the influence of various parameters on image contrast is investigated. We demonstrate that DCA enables freehand PA detection of blood vessels at a depth of 1.5 cm using only 2 mJ pulse energy, and give some guidelines for image interpretation.