: Ultrafast laser pulses featuring both high spatio-temporal beam quality and excellent energy stability are crucial for many applications. Here, we present a seed laser with high beam quality and energy stability, based on a collinear optical parametric chirped pulse amplification (OPCPA) stage, delivering 46 µ J pulses with a 25 fs Fourier limit at 1 kHz repetition rate. While saturation of the OPCPA stage is necessary for achieving the highest possible energy stability, it also leads to a degradation of the beam quality. Using simulations, we show that spectrally dependent, rotationally symmetric aberrations dominate the collinear OPCPA in saturation. We experimentally characterize these aberrations and then remove distinct spatial frequencies to greatly improve the spectral homogeneity of the beam quality, while keeping an excellent energy stability of 0.2 % rms measured over 70 hours.

Spatio-spectral couplings in saturated collinear OPCPA

: We report a method for integrating GaAs waveguide circuits containing self-assembled quantum dots on a Si/SiO 2 wafer, using die-to-wafer bonding. The large refractive-index contrast between GaAs and SiO 2 enables fabricating single-mode waveguides without compromising the photon-emitter coupling. Anti-bunched emission from individual quantum dots is observed, along with a waveguide propagation loss < 7 dB/mm, which is comparable with the performance of suspended GaAs circuits. These results enable the integration of quantum emitters with different material platforms, towards the realization of scalable quantum photonic integrated circuits.

Integration of GaAs waveguides on a silicon substrate for quantum photonic circuits

Neuroradiologists and neurosurgeons increasingly opt to use functional magnetic resonance imaging (fMRI) to map functionally relevant brain regions for noninvasive presurgical planning and intraoperative neuronavigation. This application requires a high degree of spatial accuracy, but the fMRI signal-to-noise ratio (SNR) decreases as spatial resolution increases. In practice, fMRI scans can be collected at multiple spatial resolutions, and it is of interest to make more accurate inference on brain activity by combining data with different resolutions. To this end, we develop a new Bayesian model to leverage both better anatomical precision in high resolution fMRI and higher SNR in standard resolution fMRI. We assign a Gaussian process prior to the mean intensity function and develop an efficient, scalable posterior computation algorithm to integrate both sources of data. We draw posterior samples using an algorithm analogous to Riemann manifold Hamiltonian Monte Carlo in an expanded parameter space. We illustrate our method in analysis of presurgical fMRI data, and show in simulation that it infers the mean intensity more accurately than alternatives that use either the high or standard resolution fMRI data alone.

Bayesian inference for brain activity from functional magnetic resonance imaging collected at two spatial resolutions

: Propolis and honey are bioproducts produced by Tetragonula laeviceps , a stingless bee species. Both products have anti-inflammatory, antimicrobial, and antibacterial properties. Modular Tetragonula hives of different sizes were used in the cultivation of T. laeviceps to increase the productivity of propolis while maintaining the sustainability of the bee colonies. This study was carried out in Jatinangor, West Java, Indonesia, with three size variations: small (21 × 18 × 14 cm), medium (26 × 22 ×17 cm), and large (30 × 26 × 17 cm). Each hive was equipped with a mesh of a different material. The results obtained in this study showed that increasing the hive’s size increases the productivity of propolis. The highest productivity of propolis (2.53 ± 0.37 g/colony/week) was obtained when T. laeviceps was cultivated in large hives equipped with a nylon-based mesh. The highest productivity of honey (0.78 ± 0.18 g/colony/week) was obtained when T. laeviceps was cultivated in medium hives equipped with an aluminum-based mesh. The harvested propolis was extracted using a maceration

Effects of hive sizes and mesh materials on the productivity of propolis and honey produced by tetragonula laeviceps

We introduce an imaging-based passive on-axis technique for measuring the distance of individual objects in complex scenes. Two axially separated pupil positions acquire images (can be realized simultaneously or sequentially). Based on the difference in magnification for objects within the images, the distance to the objects can be inferred. The method avoids some of the disadvantages of passive triangulation sensors (e.g., correspondence, shadowing), is easy to implement and offers high lateral resolution. Due to the principle of operation it is especially suited for applications requiring only low to medium axial resolution. Theoretical findings, as well as follow-up experimental measurements, show obtainable resolutions in the range of few centimeters for distances of up to several meters. © 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

Depth from axial differential perspective

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