RNO is the mid-scale discovery instrument designed to make the first observation of neutrinos from the cosmos at extreme energies, with sensitivity well beyond current instrument capabilities. This new observatory will be the largest ground-based neutrino telescope to date, enabling the measurement of neutrinos above 10 16 eV, determining the nature of the astrophysical neutrino flux that has been measured by IceCube at higher energies, similarly extending the reach of multi-messenger astrophysics to the highest energies, and enabling investigations of fundamental physics at energies unreachable by particle accelerators on Earth.

We discuss the current design of the cold hardware and cold electronics to be used in the upcoming SuperCDMS Soudan deployment. Engineering challenges associated with such concerns as thermal isolation, microphonics, radiopurity, and power dissipation are discussed, along with identifying the design changes necessary for SuperCDMS SNOLAB. The Cryogenic Dark Matter Search (CDMS) employs ultrapure 1-inch thick, 3-inch diameter germanium crystals operating below 50 mK in a dilution cryostat. These detectors give an ionization and phonon signal, which gives us rejection capabilities regarding background events versus dark matter signals.

Evolutionary algorithms are a type of artificial intelligence that utilize principles of evolution to efficiently determine solutions to defined problems. These algorithms are particularly powerful at finding solutions that are too complex to solve with traditional techniques and at improving solutions found with simplified methods. The GENETIS collaboration is developing genetic algorithms (GAs) to design antennas that are more sensitive to ultra-high energy neutrino-induced radio pulses than current detectors. Improving antenna sensitivity is critical because UHE neutrinos are rare and require massive detector volumes with stations dispersed over hundreds of km 2 . The GENETIS algorithm evolves antenna designs using simulated neutrino sensitivity as a measure of fitness by integrating with XFdtd, a finite-difference time-domain modeling program, and with simulations of neutrino experiments. The best antennas will then be deployed in-ice for initial testing. The GA's aim is to create antennas that improve on the designs used in the existing ARA experiment by more than a factor of 2 in neutrino sensitivities. This research could improve antenna sensitivities in future experiments and thus accelerate the discovery of UHE neutrinos. This is the first time that antennas have been designed using GAs with a fitness score based on a physics outcome, which will motivate the continued use of GA-designed instrumentation in astrophysics and beyond. This proceeding will report on advancements to the algorithm, steps taken to improve the GA performance, the latest results from our evolutions, and the manufacturing road map.

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