New Capabilities in Exoplanet Research Using Unique MASTER Global Robotic Net Archive with Lomonosov Supercomputer Powers

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Abstract We present the algorithm of exoplanets transit search in MASTER global robotic telescope network database, that has been created with the involvement and use of artificial intelligence methods. MASTER’s 2003–2023 years archive images are stored at data storage and analysis center in Lomonosov supercomputer. For exoplanets transit search we used the images of SWIFT gamma-ray bursts alerts (GRB), received by MASTER telescopes during several hours at target nights. The algorithm includes cross-correlation of GRB error-boxes coordinates and TESS exoplanetary transits candidates inside 4 square degrees of each field. Our analyses is based on wide-field images obtained on MASTER-Amur, -Tunka, -Kislovodsk, -Tavrida, MASTER-IAC, MASTER-OAGH, MASTER-OAFA and MASTER-SAAO robotic telescopes. We used data storage and analysis center in Lomonosov supercomputer with MASTER images archive, calculated light curves for target stars and approximate them to find eclipse by exoplanets. The centralized storage of this data allows us to simplify and significantly speed up access to the huge archive of images formed during the entire operation of the robotic network for automatic processing and facilitate the manual search for the necessary information by the researcher. From this storage we compared the program with unique long homogeneous series of Swift GRBs alert and inspection observations, which we analyzed. The main result is reduction of unique light curves of exoplanetary transits of TIC 127115861.01 TESS candidate, obtained by MASTER long before the TESS space observatory.

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