Mini-EUSO is part of the JEM-EUSO program and operates on board the International Space Station (ISS). It is a UV-telescope with single-photon counting capability looking at nighttime downwards to the Earth through a nadir-facing UV-transparent window. As part of the pre-flight tests, the Mini-EUSO engineering model, a telescope with 1/9 of the original focal surface and a lens of 2.5 cm diameter, has been built and tested. Tests of the Mini-EUSO engineering model have been made in laboratory and in open-sky conditions. Laboratory tests have been performed at the TurLab facility, located at the Physics Department of the University of Turin, equipped with a rotating tank containing different types of materials and light sources. In this way, the configuration for the observation of the Earth from space was emulated, including the Mini-EUSO trigger schemes. In addition to the qualification and calibration tests, the Mini-EUSO engineering model has also been used to evaluate the possibility of using a JEM-EUSO-type detector for applications such as observation of space debris. Furthermore, observations in open-sky conditions allowed the studies of natural light sources such as stars, meteors, planets, and artificial light sources such as airplanes, satellites reflecting the sunlight, and city lights. Most of these targets could be detected also with Mini-EUSO. In this paper, the tests in laboratory and in open-sky conditions are reported, as well as the obtained results. In addition, the contribution that such tests provided to foresee and improve the performance of Mini-EUSO on board the ISS is discussed.

Context. Observations of meteors in the Earth’s atmosphere offer a unique tool for determining the flux of meteoroids that are too small to be detected by direct telescopic observations. Although these objects are routinely observed from ground-based facilities, such as meteor and fireball networks, space-based instruments come with notable advantages and have the potential to achieve a broad and uniform exposure. Aims. In this paper, we describe the first observations of meteor events with Mini-EUSO, a very wide field-of-view telescope launched in August 2019 from the Baikonur cosmodrome and installed on board the Russian Zvezda module of the International Space Station. Mini-EUSO can map the night-time Earth in the near-UV range (290-130 nm) with a field of view equal to 44° × 44° and a spatial resolution of about 4.7 km at an altitude of 100 km from the ground. The detector saves triggered transient phenomena with a sampling frequency of 2.5 µs and 320 µs, as well as a continuous acquisition at 40.96 ms scale that is suitable for meteor observations. Methods. We designed two dedicated and complementary trigger methods, together with an analysis pipeline able to estimate the main physical parameters of the observed population of meteors, such as the duration, horizontal speed, azimuth, and absolute magnitude. To compute the absolute flux of meteors from Mini-EUSO observations, we implemented a simulation framework able to estimate the detection efficiency as a function of the meteor magnitude and the background illumination conditions. Results. The instrument detected 24 thousand meteors within the first 40 data-taking sessions from November 2019 to August 2021, for a total observation time of approximately 6 days with a limiting absolute magnitude of +6. Our estimation of the absolute flux density of meteoroids in the range of mass between 10⁻⁵ kg to 10⁻¹ kg was found to be comparable to other results available in the literature. Conclusions. The results of this work prove the potential for space-based observations to increase the statistics of meteor observations achievable with instruments operating on the ground. The slope of the mass distribution of meteoroids sampled with Mini-EUSO suggests a mass index of either s = 2.09 ± 0.02 or s = 2.31 ± 0.03, according to two different methodologies for the computation of the pre-atmospheric mass starting from the luminosity of each event.

The JEM-EUSO program aims to study ultra-high energy cosmic rays from space. To achieve this goal, it has realized a series of experiments installed on the ground (EUSO-TA), various on stratospheric balloons (with the most recent one EUSO-SPB2), and inside the International Space Station (Mini-EUSO), in light of future missions such as K-EUSO and POEMMA. At nighttime, these instruments aim to monitor the Earth’s atmosphere measuring fluorescence and Cherenkov light produced by extensive air showers generated both by very high-energy cosmic rays from outside the atmosphere and by neutrino decays. As the two light components differ in duration (order of microseconds for fluorescence light and a few nanoseconds for Cherenkov light) they each require specialized sensors and acquisition electronics. So far, the sensors used for the fluorescence camera are the Multi-Anode Photomultiplier Tubes (MAPMTs), while for the Cherenkov one, new systems based on Silicon PhotoMultipliers (SiPMs) have been developed. In this contribution, a brief review of the experiments is followed by a discussion of the tests performed on the optical sensors. Particular attention is paid to the development, test, and calibration conducted on SiPMs, also in view to optimize the geometry, mass, and weight in light of the installation of mass-critical applications such as balloon- and space-borne instrumentation.

In this article, we present cutting-edge machine learning-based techniques for the detection and reconstruction of meteors and space debris in the Mini-EUSO experiment, a detector installed on board of the International Space Station, and pointing toward the Earth. We base our approach on a recent technique, the STACKing method plus Convolutional Neural Network (STACK-CNN), originally developed as an online trigger in an orbiting remediation system to detect space debris. Our proposed method, the refined-STACKing method plus convolutional neural network (R-Stack-CNN), makes the STACKing method plus convolutional neural network (STACK-CNN) more robust, thanks to a random forest that learns the temporal development of these events in the camera. We prove the flexibility of our method by showing that it is sensitive to any space object that moves linearly in the field of view. First, we search small space debris, never observed by Mini-EUSO. Due to the limiting statistics, also in this case, no debris were found. However, since meteors produce signals similar to space debris but they are much more frequent, the R-Stack-CNN is adapted to identify such events while avoiding the numerous false positives of the Stack-CNN. Results from real data show that the R-Stack-CNN is able to find more meteors than a classical thresholding method and a new method of two neural networks. We also show that the method is also able to accurately reconstruct speed and direction of meteors with simulated data.