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The Transiting Exoplanet Survey Satellite (TESS), launched successfully on 2018 April 18 will observe nearly the full sky, and will provide timeseries imaging data in ∼27-day-long campaigns. TESS is equipped with four cameras, each of which has a field of view of 24 × 24°. During the first two years of the primary mission, one of these cameras, Camera #1, is going to observe fields centered at an ecliptic latitude of 18°. While the ecliptic plane itself is not covered during the primary mission, the characteristic scale height of the main asteroid belt and Kuiper Belt implies that a significant amount of small solar system bodies will cross this camera's field of view. Based on the comparison of the expected amount of information of TESS and Kepler/K2, we can compute the cumulative étendues of the two optical setups. This comparison results in roughly comparable optical étendues; however, the net étendue is significantly larger in the case of TESS because all of the imaging data provided by the 30-minute cadence frames are downlinked rather than the pre-selected stamps of Kepler/K2. In addition, many principles of the data acquisition and optical setup are clearly different, including the level of confusing background sources; full-frame integration and cadence; the field-of-view centroid with respect to the apparent position of the Sun; as well as the differences in the duration of the campaigns. As one would expect, TESS will yield timeseries photometry, and hence rotational properties for only brighter objects, but in terms of spatial and phase space coverage, this sample will be more homogeneous and more complete. Here, we review the main analogs and differences between the Kepler/K2 mission and the TESS mission, focusing on scientific implications and possible yields related to our solar system.

Classical T Tauri stars are low-mass objects that are still accreting material from the surrounding circumstellar disk. The accretion process is essential in the formation of Sun-like stars and in setting the properties of the disk at the time when planet formation occurs. We constructed a complex data set in order to examine the accretion process of VW Cha, a classical T Tauri multiple system, with the aim of studying the physical origin of the photometric and spectroscopic variability of the system. The TESS space telescope observed VW Cha between 2019 April 22 and June 19, and we complemented these data with contemporaneous ground-based I CJHK-band photometric measurements. In addition, we obtained high-resolution optical spectra with the VLT/ESPRESSO and the 2.2 m/FEROS instruments. Analyzing these data, we found that the TESS light curve shows photometric variations on timescales from minutes to weeks with a peak-to-peak amplitude of ∼0.8 mag. The near-infrared light curves follow the shape of the optical measurements; however, the peak-to-peak amplitudes are slightly increasing toward the longer wavelengths. We took spectra in both fainter and brighter photometric states of the system, allowing us to examine the origin of a photometric brightening event. Our results show that this brightening event can be explained by increased accretion. In addition, our spectroscopic data also suggest that the primary component of VW Cha is a spectroscopic binary, as was proposed in earlier works.

Gaia19fct is one of the Gaia-alerted eruptive young stars that has undergone several brightening events. We conducted monitoring observations using multifilter optical and near-infrared photometry, as well as near-infrared spectroscopy, to understand the physical properties of Gaia19fct and investigate whether it fits into the historically defined two classes. We present the analyses of light curves, color variations, spectral lines, and CO modeling. The light curves show at least five brightening events since 2015, and the multifilter color evolutions are mostly gray. The gray evolution indicates that bursts are triggered by mechanisms other than extinction. Our near-infrared spectra exhibit both absorption and emission lines and show time variability throughout our observations. We found lower rotational velocity and lower temperature from the near-infrared atomic absorption lines than from the optical lines, suggesting that Gaia19fct has a Keplerian rotating disk. The CO overtone features show a superposition of absorption and emission components, which is unlike other young stellar objects. We modeled the CO lines, and the result suggests that the emission and absorption components are formed in different regions. We found that although Gaia19fct exhibits characteristics of both types of eruptive young stars, FU Orionis–type objects and EX Lupi–type objects, it shows more similarity with EXors in general.

If one has to attain high accuracy over long timescales during the numerical computation of the N -body problem, the method called Lie-integration is one of the most effective algorithms. In this paper, we present a set of recurrence relations with which the coefficients needed by the Lie-integration of the orbital elements related to the spatial N -body problem can be derived up to arbitrary order. Similarly to the planar case, these formulae yield identically zero series in the case of no perturbations. In addition, the derivation of the formulae has two stages, analogously to the planar problem. Namely, the formulae are obtained to the first order, and then, higher-order relations are expanded by involving directly the multilinear and fractional properties of the Lie-operator.

Lie-integration is one of the most efficient algorithms for numerical integration of ordinary differential equations if high precision is needed for longer terms. The method is based on the computation of the Taylor coefficients of the solution as a set of recurrence relations. In this paper, we present these recurrence formulae for orbital elements and other integrals of motion for the planar N -body problem. We show that if the reference frame is fixed to one of the bodies—for instance to the Sun in the case of the Solar System—the higher order coefficients for all orbital elements and integrals of motion depend only on the mutual terms corresponding to the orbiting bodies.

We outline the impact of a small two-band UV-photometry satellite mission on the field of stellar physics, magnetospheres of stars, binaries, stellar clusters, interstellar matter, and exoplanets. On specific examples of different types of stars and stellar systems, we discuss particular requirements for such a satellite mission in terms of specific mission parameters such as bandpass, precision, cadence, and mission duration. We show that such a mission may provide crucial data not only for hot stars that emit most of their light in UV, but also for cool stars, where UV traces their activity. This is important, for instance, for exoplanetary studies, because the level of stellar activity influences habitability. While the main asset of the two-band UV mission rests in time-domain astronomy, an example of open clusters proves that such a mission would be important also for the study of stellar populations. Properties of the interstellar dust are best explored when combining optical and IR information with observations in UV. It is well known that dust absorbs UV radiation efficiently. Consequently, we outline how such a UV mission can be used to detect eclipses of sufficiently hot stars by various dusty objects and study disks, rings, clouds, disintegrating exoplanets or exoasteroids. Furthermore, UV radiation can be used to study the cooling of neutron stars providing information about the extreme states of matter in the interiors of neutron stars and used for mapping heated spots on their surfaces.

The Transiting Exoplanet Survey Satellite (TESS) is a NASA Explorer-class mission designed for finding exoplanets around nearby stars. TESS image data can also serve as a valuable resource for asteroid and comet detection, including near-Earth objects (NEOs). In order to exploit the TESS image data for moving object detection and potential object discovery, our team has developed an image processing pipeline as part of the Lincoln Near-Earth Asteroid Research (LINEAR) program, sponsored by the NASA NEO Observations Program. The LINEAR-TESS pipeline is currently in operation and reporting asteroid observations to the Minor Planet Center. In this paper we discuss the algorithms and methodology utilized to push the limits of the astrometric accuracy and photometric sensitivity of the TESS instrument for asteroid detection without a priori information on the ephemerides of the objects, and report on observation statistics from the first two years of TESS mission data.

Due to the advancement of nano-satellite technology, CubeSats and fleets of CubeSats can form an alternative to high-cost large-size satellite missions with the advantage of extended spatial coverage. One of these initiatives is the Cubesats Applied for MEasuring and LOcalising Transients (CAMELOT) mission concept, aimed at detecting and localizing gamma-ray bursts with an efficiency and accuracy comparable to large gamma-ray space observatories. While precise attitude control is not necessary for such a mission, attitude determination is an important issue in the interpretation of scintillator detector data as well as optimizing downlink telemetry. The employment of star trackers is not always a viable option for such small satellites, hence another alternative is necessary. A new method is proposed in this series of papers, utilizing thermal imaging sensors to provide simultaneous measurement of the attitude of the Sun and the horizon by employing a homogeneous array of such detectors. The combination with Sun and horizon detection w.r.t. the spacecraft would allow the full 3-DoF recovery of its attitude. In this paper we determine the spherical projection function of the MLX90640 infrasensors planned to be used for this purpose. We apply a polynomial transformation with radial corrections to map the spatial coordinates to the sensor plane. With the determined projection function the location of an infrared point source can be determined with an accuracy of ∼40′ , well below the design goals of a nano-satellite designed for gamma-ray detection.

This paper is the second part of a series of studies discussing a novel attitude determination method for nano-satellites. Our approach is based on the utilization of thermal imaging sensors to determine the direction of the Sun and the nadir with respect to the satellite with sub-degree accuracy. The proposed method is planned to be applied during the Cubesats Applied for MEasuring and LOcalising Transients (CAMELOT) mission aimed at detecting and localizing gamma-ray bursts with an efficiency and accuracy comparable to large gamma-ray space observatories. In our previous work we determined the spherical projection function of the MLX90640 infrasensors planned to be used for this purpose. We showed that with the known projection function the direction of the Sun can be located with an overall accuracy of ∼40′ . In this paper we introduce a simulation model aimed at testing the applicability of our attitude determination approach. Its first part simulates the orbit and rotation of a satellite with arbitrary initial conditions while its second part applies our attitude determination algorithm which is based on a multiplicative extended Kalman filter. The simulated satellite is assumed to be equipped with a GPS system, MEMS gyroscopes and the infrasensors. These instruments provide the required data input for the Kalman filter. We demonstrate the applicability of our attitude determination algorithm by simulating the motion of a nano-satellite on Low Earth Orbit. Our results show that the attitude determination may have a 1 σ error of ∼30′ even with a large gyroscope drift during the orbital periods when the infrasensors provide both the direction of the Sun and the Earth (the nadir). This accuracy is an improvement on the point source detection accuracy of the infrasensors. However, the attitude determination error can get as high as 25 ∘ during periods when the Sun is occulted by the Earth. We show that following an occultation period the attitude information is immediately recovered by the Kalman filter once the Sun is observed again.

Conventional classifiers are generally unable to identify samples from classes absent during the model’s training. However, such samples frequently emerge in real-world scenarios, necessitating the extension of classifier capabilities. Open-Set Recognition (OSR) models are designed to address this challenge. Previously, we developed a robust OSR method that employs generated—“fake”—features to model the space of unknown classes encountered during deployment. Like most OSR models, this method was initially designed for image datasets. However, it is essential to extend OSR techniques to other data types, given their widespread use in practice. In this work, we adapt our model to time-series data while preserving its core efficiency advantage. Thanks to the model’s modular design, only the feature extraction component required modification. We implemented three approaches: a one-dimensional convolutional network for accurate representation, a lightweight method based on predefined statistical features, and a frequency-domain neural network. Further, we evaluated combinations of these methods. Experiments on a biometric time-series dataset, used here as a case study, demonstrate that our model achieves excellent open-set detection and closed-set accuracy. Combining feature extraction strategies yields the best performance, while individual methods offer flexibility: CNNs deliver high accuracy, whereas handcrafted features enable resource-efficient deployment. This adaptability makes the proposed framework suitable for scenarios with varying computational constraints.