Observation of high-energy neutrinos from the Galactic plane

Abbasi, R., Ackermann, M., Adams, J., Aguilar, J. A., Ahlers, M., Ahrens, M., Alameddine, J. M., Alves, A. A. Jr., Amin, N. M., Andeen, K., Anderson, T., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Axani, S., Bai, X., V., A. Balagopal, Barwick, S. W., Basu, V., Baur, S., Bay, R., Beatty, J. J., Becker, K. -H., Tjus, J. Becker, Beise, J., Bellenghi, C., Benda, S., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Binder, G., Bindig, D., Blaufuss, E., Blot, S., Boddenberg, M., Bontempo, F., Book, J. Y., Borowka, J., Böser, S., Botner, O., Böttcher, J., Bourbeau, E., Bradascio, F., Braun, J., Brinson, B., Bron, S., Brostean-Kaiser, J., Burley, R. T., Busse, R. S., Campana, M. A., Carnie-Bronca, E. G., Chen, C., Chen, Z., Chirkin, D., Choi, K., Clark, B. A., Clark, K., Classen, L., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Correa, P., Cowen, D. F., Cross, R., Dappen, C., Dave, P., De Clercq, C., DeLaunay, J. J., López, D. Delgado, Dembinski, H., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Dujmovic, H., Dunkman, M., DuVernois, M. A., Ehrhardt, T., Eller, P., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Fienberg, A. T., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Friedman, E., Fritz, A., Fürst, P., Gaisser, T. K., Gallagher, J., Ganster, E., Garcia, A., Garrappa, S., Gerhardt, L., Ghadimi, A., Glaser, C., Glauch, T., Glüsenkamp, T., Goehlke, N., Goldschmidt, A., Gonzalez, J. G., Goswami, S., Grant, D., Grégoire, T., Griswold, S., Günther, C., Gutjahr, P., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Minh, M. Ha, Hanson, K., Hardin, J., Harnisch, A. A., Haungs, A., Helbing, K., Henningsen, F., Hettinger, E. C., Hickford, S., Hignight, J., Hill, C., Hill, G. C., Hoffman, K. 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Jul-10-2023–arXiv.org Artificial Intelligence 

The origin of high-energy cosmic rays, atomic nuclei that continuously impact Earth's atmosphere, has been a mystery for over a century. Due to deflection in interstellar magnetic fields, cosmic rays from the Milky Way arrive at Earth from random directions. However, near their sources and during propagation, cosmic rays interact with matter and produce high-energy neutrinos. We search for neutrino emission using machine learning techniques applied to ten years of data from the IceCube Neutrino Observatory. We identify neutrino emission from the Galactic plane at the 4.5$\sigma$ level of significance, by comparing diffuse emission models to a background-only hypothesis. The signal is consistent with modeled diffuse emission from the Galactic plane, but could also arise from a population of unresolved point sources.