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We present a novel solution to automated beam alignment optimization. This device is based on a Raspberry Pi computer, stepper motors, commercial optomechanics and electronic devices, and the open source machine learning algorithm M-LOOP. We provide schematic drawings for the custom hardware necessary to operate the device and discuss diagnostic techniques to determine the performance. The beam auto-aligning device has been used to improve the alignment of a laser beam into a single-mode optical fiber from manually optimized fiber alignment with an iteration time of typically 20~minutes. We present example data of one such measurement to illustrate device performance.
We report an automated characterization of a single-photon detector based on commercial silicon avalanche photodiode (PerkinElmer C30902SH). The photodiode is characterized by I-V curves at different illumination levels (darkness, 10 pW and 10 uW), d
Hot cavity resonant ionization laser ion sources (RILIS) provide a multitude of radioactive ion beams with high ionization efficiency and element selective ionization. However, in hot cavity RILIS there still remains isobaric contaminations in the ex
At CEILAP (CITEDEF-CONICET), a multiangle LIDAR is under development to monitor aerosol extinction coefficients in the frame of the CTA (Cherenkov Telescope Array) Project. This is an initiative to build the next generation of ground-based instrument
In atomic force microscopy (AFM), the exchange and alignment of the AFM cantilever with respect to the optical beam and position-sensitive detector (PSD) are often performed manually. This process is tedious and time-consuming and sometimes damages t
Automated machine learning (AutoML) aims to find optimal machine learning solutions automatically given a machine learning problem. It could release the burden of data scientists from the multifarious manual tuning process and enable the access of do