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The “Condor Array Telescope” or “Condor” is a high-performance “array telescope” comprised of six apochromatic refracting telescopes of objective diameter 180 mm, each equipped with a large-format, very low-read-noise (≈1.2 e − ), very rapid-read-time (<1 s) CMOS camera. Condor is located at a very dark astronomical site in the southwest corner of New Mexico, at the Dark Sky New Mexico observatory near Animas, roughly midway between (and more than 150 km from either) Tucson and El Paso. Condor enjoys a wide field of view (2.29 × 1.53 deg 2 or 3.50 deg 2 ), is optimized for measuring both point sources and extended, very low-surface-brightness features, and for broad-band images can operate at a cadence of 60 s (or even less) while remaining sky-noise limited with a duty cycle near 100%. In its normal mode of operation, Condor obtains broad-band exposures of exposure time 60 s over dwell times spanning dozens or hundreds of hours. In this way, Condor builds up deep, sensitive images while simultaneously monitoring tens or hundreds of thousands of point sources per field at a cadence of 60 s. Condor is also equipped with diffraction gratings and with a set of He ii 468.6 nm, [O iii ] 500.7 nm, He i 587.5 nm, H α 656.3 nm, [N ii ] 658.4 nm, and [S ii ] 671.6 nm narrow-band filters, allowing it to address a variety of broad- and narrow-band science issues. Given its unique capabilities, Condor can access regions of “astronomical discovery space” that have never before been studied. Here we introduce Condor and describe various aspects of its performance.

The Ground Wide Angle Camera Network (GWAC-N) is a network of robotic multi-aperture, multiple field-of-view (FoV) optical telescopes. The main contingent of GWAC-N instruments are provided by the Ground Wide Angle Cameras Array (GWAC-A), and additional, narrower FoV telescopes are utilized to provide fast multi-band follow-up capabilities. The primary scientific goal of the GWAC-N is to search for optical counterparts of gamma-ray bursts that will be detected by the Space Variable Object Monitor (SVOM) satellite. The GWAC-N performs many additional observing tasks including follow-up of Target of Opportunities (ToO) targets and the detection (and monitoring) of variable objects and optical transients. To handle these use cases (and to allow for extensibility), we have designed ten observation modes and 175 observation strategies, including a joint strategy with multiple GWAC-N telescopes for the follow-up of gravitational wave (GW) events. To perform these observations, we develop an Automatic Observation Management (AOM) system capable of performing object management, dynamic scheduling, automatic broadcasting across the network, and image handling. The AOM system combines the individual telescopes which comprise the GWAC-N into a network and smoothly organizes all associated operations, completely meeting the requirements dictated by GWAC-N. With its modular design, the AOM is scientifically and technically viable for other general-purpose telescope networks. As the GWAC-N extends and evolves, the AOM will greatly enhance its discovery potential. In this first paper of a series, we present the scientific goals of the GWAC-N and detail the hardware, software, and workflow developed to achieve these goals. The structure, technical design, implementation, and performance of the AOM system are also described in detail. We conclude with a summary of the current status of the GWAC-N and our near-future development plan.

SPECULOOS is a ground-based transit survey consisting of six identical 1 m robotic telescopes. The immediate goal of the project is to detect temperate terrestrial planets transiting nearby ultracool dwarfs (late M-dwarf stars and brown dwarfs), which could be amenable for atmospheric research with the next generation of telescopes. Here, we report the developments of the northern counterpart of the project—SPECULOOS Northern Observatory, and present its performance during the first three years of operations from mid-2019 to mid-2022. Currently, the observatory consists of one telescope, which is named Artemis. The Artemis telescope demonstrates remarkable photometric precision, allowing it to be ready to detect new transiting terrestrial exoplanets around ultracool dwarfs. Over the period of the first three years after the installation, we observed 96 objects from the SPECULOOS target list for 6000 hr with a typical photometric precision of 0.5%, and reaching a precision of 0.2% for relatively bright non-variable targets with a typical exposure time of 25 s. Our weather downtime (clouds, high wind speed, high humidity, precipitation and/or high concentration of dust particles in the air) over the period of three years was 30% of overall night time. Our actual downtime is 40% because of additional time loss associated with technical problems.

Small aperture telescopes provide the opportunity to conduct high frequency, targeted observations of near-Earth Asteroids that are not feasible with larger facilities due to highly competitive time allocation requirements. Observations of asteroids with these types of facilities often focus on rotational brightness variations rather than longer-term phase angle-dependent variations (phase curves) due to the difficulty of achieving high precision photometric calibration. We have developed an automated asteroid light curve extraction and calibration pipeline for images of moving objects from the 0.43 m Physics Innovations Robotic Telescope Explorer. This allows for the frequency and quality of observations required to construct asteroid phase curves. Optimizations in standard data reduction procedures are identified that may allow for similar small aperture facilities, constructed from commercially available/off-the-shelf components, to improve the image and subsequent data quality. A demonstration of the hardware and software capabilities is expressed through observation statistics from a 10 months observing campaign, and through the photometric characterization of near-Earth Asteroids 8014 (1990 MF) and 19764 (2000 NF5).

The design, manufacturing and field tests of a new astronomical telescope mount are the main topics of this paper. The new robotic mount dedicated for 0.5 m class telescopes is the first mount developed, developed and produced as fully Polish concept by engineers and researchers representing the automation and robotics discipline (Pozna University of Technology) and astronomy (Nicolaus Copernicus Astronomical Centre of the Polish Academy of Sciences). The mount is an alt-azimuth fork-type design which allows tracking of typical astronomical targets (sidereal tracking) but also man made objects (satellite tracking). Thanks to a unique mechanical design based on direct drive motors and high precision encoders coupled with custom electronics and on-board software implementing modern control theory achievements it was possible to obtain very good trajectory tracking precision throughout the entire dynamic range defined by the user scenarios. Additionally, the used control algorithms are robust to some class of disturbances such as friction which in turn allows for very high precision tracking in a wide range of angular velocities-from quasi-static movements to high-velocity satellite tracking. The test-bed infrastructure of the system is located in a dedicated astronomical research laboratory at the Pozna University of Technology campus. Local, remote as well as automatic observations can be carried out in the facility.

This paper proposes an online continual learning (OCL) methodology tested on hardware and validated for space applications using an object detection close-proximity operations task. The proposed OCL algorithm simulates a streaming scenario and uses experience replay to enable the model to update its knowledge without suffering catastrophic forgetting by saving past inputs in an onboard reservoir that will be sampled during updates. A stream buffer is introduced to enable online training, i.e., the ability to update the model as data is streamed, one sample at a time, rather than being available in batches. Hyperparameters such as buffer sizes, update rate, batch size, batch concatenation parameters and number of iterations per batch are all investigated to find an optimized approach for the incremental domain and streaming learning task. The algorithm is tested on a customized dataset for space applications simulating changes in visual environments that significantly impact the deployed model’s performance. Our OCL methodology uses Weighted Sampling, a novel approach which allows the system to analytically choose more useful input samples during training, the results show that a model can be updated online achieving up to 60% Average Learning while Average Forgetting can be as low as 13% all with a Model Size Efficiency of 1, meaning the model size does not increase. An additional contribution is an implementation of On-Device Continual Training for embedded applications, a hardware experiment is carried out on the Zynq 7100 FPGA where a pre-trained CNN model is updated online using our FPGA backpropagation pipeline and OCL methodology to take into account new data and satisfactorily complete the planned task in less than 5 min achieving 90 FPS.

Exoplanet observations have been performed on the automated Pulkovo Observatory telescopes. We have obtained 33 transit light curves for 16 known exoplanets and six transit observations for three exoplanet candidates discovered by the Kepler telescope. Based on our observations, we have reliably confirmed the existence of an exoplanet with an extremely large radius, R pl = 1.83 ± 0.16 R Jup , in the system KOI 256 and detected a strong deviation of its orbital revolution from the theoretically predicted one. During the transit of the exoplanet WASP-12b across the stellar disk, we detected bursts that could be caused by the planet transit across spots on the star or by the presence of a satellite around this exoplanet. We detected possible periodic variations in the duration of the exoplanet transit across the stellar disk with time for HAT-P-12b that could be caused by variations in orbital inclination. The transit duration and depth, the central transit time, and the radius and orbital inclination of the planet have been estimated. The equilibrium temperature and albedo have been estimated for several exoplanets.

Time-domain astrophysics benefits from extreme-latitude sites, which can combine intrinsically extended nighttime with good sky conditions. One such location is the Polar Environment Atmospheric Research Laboratory (PEARL), at 80° North latitude, on the northwestern edge of Ellesmere Island, Canada. Experience gained deploying seeing monitors there has been incorporated into an automated system called \"Ukaliq\" after the common arctic hare, which is also very well suited to its local environment. Even with modest aperture, high photometric reliability may be achieved using simple adaptive optics together with observing strategies that best fit the unique set of advantages available at PEARL: excellent image quality maintained during many clear, calm, dark periods of 100 hours or more. A potential multi-year search for gravitational microlensing of quasars with Ukaliq helps illustrate this niche in the era of large wide-field survey facilities.

The development of ontologies involves continuous but relatively small modifications. However, existing ontology reasoners do not take advantage of the similarities between different versions of an ontology. In this paper, we propose a collection of techniques for incremental reasoning—that is, reasoning that reuses information obtained from previous versions of an ontology. We have applied our results to incremental classification of OWL ontologies and found significant improvement over regular classification time on a set of real-world ontologies.

The process of engineering analysis, especially its preprocessing stage, comprises some knowledge-based tasks which influence the quality of the results greatly, require considerable level of expertise from an engineer; the support for these tasks by the contemporary CAE systems is limited. Analysis of the knowledge and reasoning involved in solving these tasks shows that the appropriate support for them by an automated system can be implemented using case-based reasoning (CBR) technology. In this paper the automated knowledge-based system for intelligent support of the preprocessing stage of engineering analysis in the contact mechanics domain is presented which employs the CBR mechanism. The case representation model is proposed which is centered on the structured qualitative model of a technical object. The model is formally represented by the Ontology Web Language Description Logics (OWL DL) ontology. Case retrieval and adaptation algorithms for this model are described which according to the initial tests perform better in the chosen domain then the known prototypes. The automated system is described and a sample problem-solving scenario from the contact mechanics domain is presented. Use of such system can potentially lower costs of engineering analysis by reducing the number of inappropriate decisions and analysis iterations and facilitate knowledge transfer from research into industry.