Sensitivity of the KM3NeT/ARCA neutrino telescope to point-like neutrino sources Aiello, S. Díaz García, Antonio Francisco López Coto, Daniel Navas Concha, Sergio Astrophysical neutrino sources Cherenkov underwater neutrino telescope KM3NeT will be a network of deep-sea neutrino telescopes in the Mediterranean Sea. The KM3NeT/ARCA detector, to be installed at the Capo Passero site (Italy), is optimised for the detection of high-energy neutrinos of cosmic origin. Thanks to its geographical location on the Northern hemisphere, KM3NeT/ARCA can observe upgoing neutrinos from most of the Galactic Plane, including the Galactic Centre. Given its effective area and excellent pointing resolution, KM3NeT/ARCA will measure or significantly constrain the neutrino flux from potential astrophysical neutrino sources. At the same time, it will test flux predictions based on gamma-ray measurements and the assumption that the gamma-ray flux is of hadronic origin. Assuming this scenario, discovery potentials and sensitivities for a selected list of Galactic sources and to generic point sources with an E −2 spectrum are presented. These spectra are assumed to be time independent. The results indicate that an observation with 3 σsignificance is possible in about six years of operation for the most intense sources, such as Supernovae Remnants RX J1713.7-3946 and Vela Jr. If no signal will be found during this time, the fraction of the gamma-ray flux coming from hadronic processes can be constrained to be below 50% for these two objects. 2020-04-28T11:56:54Z 2020-04-28T11:56:54Z 2019-04-05 info:eu-repo/semantics/article Aiello, S., Akrame, S. E., Ameli, F., Anassontzis, E. G., Andre, M., Androulakis, G., ... & Avgitas, T. (2019). Sensitivity of the KM3NeT/ARCA neutrino telescope to point-like neutrino sources. Astroparticle Physics, 111, 100-110. http://hdl.handle.net/10481/61659 10.1016/j.astropartphys.2019.04.002 eng http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess Atribución-NoComercial-SinDerivadas 3.0 España Elsevier Inc.