The ARIANNA experiment is an Askaryan detector designed to record radio signals induced by neutrino interactions in the Antarctic ice. Because of the low neutrino flux at high energies (Eν > 1016 eV), the physics output is limited by statistics. Hence, an increase in sensitivity significantly improves the interpretation of data and offers the ability to probe new parameter spaces. The amplitudes of the trigger threshold are limited by the rate of triggering on unavoidable thermal noise fluctuations. We present a real-time thermal noise rejection algorithm that enables the trigger thresholds to be lowered, which increases the sensitivity to neutrinos by up to a factor of two (depending on energy) compared to the current ARIANNA capabilities. A deep learning discriminator, based on a Convolutional Neural Network (CNN), is implemented to identify and remove thermal events in real time. We describe a CNN trained on MC data that runs on the current ARIANNA microcomputer and retains 95% of the neutrino signal at a thermal noise rejection factor of 105, compared to a template matching procedure which reaches only 102 for the same signal efficiency. Then the results are verified in a lab measurement by feeding in generated neutrino-like signal pulses and thermal noise directly into the ARIANNA data acquisition system. Lastly, the same CNN is used to classify cosmic-rays events to make sure they are not rejected. The network classified 102 out of 104 cosmic-ray events as signal.

The ARIANNA detector is designed to detect neutrinos with energies above 1017 eV. Due to the similarities in generated radio signals, cosmic rays are often used as test beams for neutrino detectors. Some ARIANNA detector stations are equipped with antennas capable of detecting air showers. Since the radio emission properties of air showers are well understood, and the polarization of the radio signal can be predicted from the arrival direction, cosmic rays can be used as a proxy to assess the reconstruction capabilities of the ARIANNA neutrino detector. We report on dedicated efforts of reconstructing the polarization of cosmic-ray radio pulses. After correcting for difference in hardware, the two stations used in this study showed similar performance in terms of event rate and agreed with simulation. Subselecting high quality cosmic rays, the polarizations of these cosmic rays were reconstructed with a resolution of 2.5° (68% containment), which agrees with the expected value obtained from simulation. A large fraction of this resolution originates from uncertainties in the predicted polarization because of the contribution of the subdominant Askaryan effect in addition to the dominant geomagnetic emission. Subselecting events with a zenith angle greater than 70° removes most influence of the Askaryan emission, and, with limited statistics, we found the polarization uncertainty is reduced to 1.3° (68% containment).

A radio-frequency polarization measurement by the ARIANNA surface station was performed using a residual hole from the South Pole Ice Core (SPICEcore) Project. Radio pulses were emitted from a transmitter located down to 1.7 km below the snow surface. After deconvolving the raw signals for the detector response and attenuation from propagation through the ice, the signal pulses show no significant distortion and agree with a reference measurement of the emitter made in an anechoic chamber. The direction to transmitted radio pulse was measured with an angular resolution of 0.37 degree [statistical error]. For polarization, the statistical error of the polarization vector is depth dependent and below 1 degree. In addition, a slowly-varying systematic variation is observed as a function of depth with an rms error of 2.7 degrees. Neither the direction or polarization measurement show a significant offset as a function of depth relative to expectation. We also report on the results of a simulation study of the ARIANNA neutrino direction and energy resolution. The software tool NuRadioMC was used to reconstruct the polarization and viewing angle to determine the neutrino direction. Multiple models of Askaryan radiation and detector sites along with a range of neutrino energies were evaluated. The neutrino space angle resolution was determined to be below 3 degrees, which is comparable to the systematic polarization uncertainty. Therefore it is expected that the polarization resolution, which is the dominant contribution to the neutrino space angle resolution, will be improved in future studies by determining and eliminating systematic effects.

The ARIANNA detector is designed to detect neutrinos of energies above 1016 eV. Due to the similarities in generated radio signals, cosmic rays are often used as test beams for neutrino detectors. Some ARIANNA detector stations are equipped with antennas capable of detecting air showers. The radio emission properties of air showers are well understood, and the polarization of the radio signal can be predicted from arrival direction with high precision. For this reason, cosmic rays can be used as a proxy to assess the reconstruction capabilities of the ARIANNA neutrino detector. We report on dedicated efforts of reconstructing the polarization of cosmic-ray radio pulses. A total of 148 cosmic rays are identified from over 90,000 triggered events collected between Nov 21, 2018 and Mar 15, 2019. A cut was put on these events requiring them to have a signal-to-noise (SNR) ratio of at least 4.5 in all upward-facing channels. This was to improve the performance of arrival direction and polarization reconstruction algorithms. Polarization of these cosmic rays were reconstructed with a resolution of 3.5 degrees (68% containment), which agrees with the expected value we obtained from simulation. Furthermore, if we subselect events with zenith angle greater than 70 deg, the contribution to polarization of Askaryan effect is reduced, which reduces the error in the predicted polarization. With limited statistics, we find the polarization uncertainty is reduced to 1.3 deg (68% containment).

The ARIANNA experiment is a proposed Askaryan detector designed to record radio signals induced by neutrino interactions in the Antarctic ice. Because of the low neutrino flux at high energies, the physics output is limited by statistics. Hence, an increase in sensitivity significantly improves the interpretation of data and offers the ability to probe new parameter spaces. The trigger thresholds are limited by the rate of triggering on unavoidable thermal noise fluctuations. The real-time thermal noise rejection algorithm enables the thresholds to be lowered substantially and increases the sensitivity by up to a factor of two compared to the current ARIANNA capabilities. A deep learning discriminator, based on a Convolutional Neural Network (CNN), is implemented to identify and remove a high percentage of thermal events in real time while retaining most of the neutrino signals. We describe a CNN that runs on the current ARIANNA microcomputer and retains 95% of the neutrino signals at a thermal rejection factor of 105. Finally, the experimental verification from lab measurements are conducted.

High energy neutrinos (E >1017 eV) are detected cost-efficiently via the Askaryan effect in ice, where a particle cascade induced by the neutrino interaction produces coherent radio emission that can be picked up by antennas installed below the surface. A good knowledge of the near surface ice (aka firn) properties is required to reconstruct the neutrino properties. In particular, a continuous monitoring of the snow accumulation (which changes the depth of the antennas) and the index-of-refraction profile are crucial for an accurate determination of the neutrino’s direction and energy. We present an in-situ calibration system that extends the radio detector station with a radio emitter to continuously monitor the firn properties by measuring time differences of direct and reflected (off the surface) signals (D’n’R). We optimized the station layout in a simulation study and quantified the achievable precision. We present 14 months of data of the ARIANNA detector on the Ross Ice Shelf, Antarctica, where a prototype of this calibration system was successfully used to monitor the snow accumulation with unprecedented precision of 1 mm. We explore and test several algorithms to extract the D’n’R time difference from noisy data (including deep learning). This constitutes an in-situ test of the neutrino vertex distance reconstruction using the D’n’R technique which is needed to determine the neutrino energy.

The ARIANNA neutrino detector, located at sea-level on the Ross Ice Shelf, Antarctica, consists of 200 autonomous and independent detector stations separated by 1 kilometer in a uniform triangular mesh, and serves to inform the planning of the future projects. The primary science mission of ARIANNA is to search for sources of neutrinos with energies greater than 1017 eV, complementing the reach of IceCube and other neutrino telescopes that focus on lower energies. An ARIANNA observation of a neutrino source would provide strong insight into the enigmatic sources of cosmic rays. ARIANNA observes the radio emission from high energy neutrino interactions in the Antarctic ice. Among radio based concepts under current investigation, ARIANNA would uniquely survey the vast majority of the southern sky at any instant in time, and an important region of the northern sky, by virtue of its location on the surface of the Ross Ice Shelf at Moore’s Bay. The broad sky coverage is specific to the Moore’s Bay site, providing capabilities to observe explosive sources from unknown directions. The ARIANNA architecture is designed to measure the angular direction to within 4 degrees for every neutrino candidate, which too plays an important role in the pursuit of multi-messenger observations of astrophysical sources. The sea level location reduces the impact of a potentially serious background associated with the cores of cosmic ray air showers striking the ice surface, generating radio pulses which are similar to those expected from neutrino events. Reflecting layers at the bottom or within the ice sheet (which are known to exist in thick ice sheets) might create a troublesome rate of background events, provided the reflection coefficients are large enough, that arrive at the detector from the same directions as neutrinos.