Search

The Radio Neutrino Observatory in Greenland (RNO-G) is the first in-ice radio array in the northern hemisphere for the detection of ultra-high energy neutrinos via the coherent radio emission from neutrino-induced particle cascades within the ice. The array is currently in phased construction near Summit Station on the Greenland ice sheet, with 7~stations deployed during the first two boreal summer field seasons of 2021 and 2022. In this paper, we describe the installation and system design of these initial RNO-G stations, and discuss the performance of the array as of summer 2024.

For high-energy cosmic-ray physics, it is imperative to determine the mass and energy of the cosmic ray that initiated the air shower in the atmosphere. This information can be extracted from the longitudinal profile of the air shower. In radio-metric observations, this profile is customarily determined through an extensive fitting procedure where calculated radio intensity is fitted to data. Beamforming the measured signals offers a promising alternative to bypass the cumbersome fitting procedure and to determine the longitudinal profile directly. Finite aperture effects in beamforming hamper the resolution with which this profile can be determined. We present a comprehensive investigation of the beamforming resolution in radiometric observations of air showers. There are two, principally different, approaches possible in air-shower beamforming, one where the total beamforming intensity is determined and an alternative where the beamforming trace is cross-correlated with a known response function. The effects due to a finite aperture (size of antenna array and bandwidth) are large for both approaches. We argue that it is possible to correct for the aperture corrections using an unfolding procedure. We give an explicit expression for the folding function, the kernel. Being able to calculate the folding function allows for unfolding the finite aperture effects from the data. We show that, in a model-to-model comparison, this allows for an accurate reconstruction of the current profile as the shower develops in the atmosphere. We present also an example where we reconstruct the longitudinal current profile of a shower developing under thunderstorm conditions where the atmospheric electric fields greatly alter the orientation of the transverse current in the shower front., Comment: Accepted for publication in Phys. Rev. D

The LOw Frequency ARray (LOFAR) has successfully measured cosmic rays for over a decade now. With its dense core of antenna fields in the Netherlands, it is an ideal tool for studying the radio emission from extensive air showers in the $10^{16}$ eV to $10^{18.5}$ eV range. Every air shower is measured with a small particle detector array and hundreds of antennas, which sets LOFAR apart from other air shower arrays. We present our current achievements and progress in reconstruction, interpolation, and software development during the final phases of measurement of LOFAR 1.0, before the LOFAR array gets a significant upgrade, including also plans for the final data release and refined analyses., Comment: Proceedings of the 10th ARENA Workshop 2024

A novel excitation signal design strategy based on a receding horizon control inspired optimization is presented. The proposed method is shown to effectively generate space-filling designs within the input space of a nonlinear dynamic process, thereby enabling sophisticated acquisition of information in previously unexplored operational areas. Additionally, the strategy can intensify the exploitation of specific operational areas during information gathering, offering flexibility in meeting application-specific requirements., Comment: Will be published in 34th Workshop Computational Intelligence, Berlin (2024)

The effectiveness of data-driven techniques significantly relies on the input signal used to generate the training data. Nevertheless, there is a notable gap in research when it comes to designing excitation signals for identifying nonlinear dynamic systems, likely because of the challenges involved. Based on current knowledge, it is crucial for excitation signals to effectively capture the nonlinearity across the entire operational area and to gather insights into the area-specific dynamic process characteristics. The Incremental Dynamic Space-Filling Design (IDS-FID) strategy designs excitation signals to achieve a space-filling distribution across the input space of a nonlinear approximator used in external dynamics modeling, gathering information throughout its operational area. Simultaneously, the approach enables for a heightened focus on either the systems steady-state or transient responses during information acquisition by altering the excitation signals dynamics, facilitating targeted insights into dynamic process characteristics., Comment: Will be published in 4th MECC (2024)

Multi-stage threats like advanced persistent threats (APT) pose severe risks by stealing data and destroying infrastructure, with detection being challenging. APTs use novel attack vectors and evade signature-based detection by obfuscating their network presence, often going unnoticed due to their novelty. Although machine learning models offer high accuracy, they still struggle to identify true APT behavior, overwhelming analysts with excessive data. Effective detection requires training on multiple datasets from various clients, which introduces privacy issues under regulations like GDPR. To address these challenges, this paper proposes a novel 3-phase unsupervised federated learning (FL) framework to detect APTs. It identifies unique log event types, extracts suspicious patterns from related log events, and orders them by complexity and frequency. The framework ensures privacy through a federated approach and enhances security using Paillier's partial homomorphic encryption. Tested on the SoTM 34 dataset, our framework compares favorably against traditional methods, demonstrating efficient pattern extraction and analysis from log files, reducing analyst workload, and maintaining stringent data privacy. This approach addresses significant gaps in current methodologies, offering a robust solution to APT detection in compliance with privacy laws.

The Radio Neutrino Observatory - Greenland (RNO-G) seeks discovery of ultra-high energy neutrinos from the cosmos through their interactions in ice. The science program extends beyond particle astrophysics to include radioglaciology and, as we show herein, solar observations, as well. Currently seven of 35 planned radio-receiver stations (24 antennas/station) are operational. These stations are sensitive to impulsive radio signals with frequencies between 80 and 700 MHz and feature a neutrino trigger threshold for recording data close to the thermal floor. RNO-G can also trigger on elevated signals from the Sun, resulting in nanosecond resolution time-domain flare data; such temporal resolution is significantly shorter than from most dedicated solar observatories. In addition to possible RNO-G solar flare polarization measurements, the Sun also represents an extremely useful above-surface calibration source. Using RNO-G data recorded during the summers of 2022 and 2023, we find signal excesses during solar flares reported by the solar-observing Callisto network and also in coincidence with $\sim$2/3 of the brightest excesses recorded by the SWAVES satellite. These observed flares are characterized by significant time-domain impulsivity. Using the known position of the Sun, the flare sample is used to calibrate the RNO-G absolute pointing on the radio signal arrival direction to sub-degree resolution. We thus establish the Sun as a regularly observed astronomical calibration source to provide the accurate absolute pointing required for neutrino astronomy.

The IceCube-Gen2 facility will extend the energy range of IceCube to ultra-high energies. The key component to detect neutrinos with energies above 10 PeV is a large array of in-ice radio detectors. In previous work, direction reconstruction algorithms using the forward-folding technique have been developed for both shallow ($\lesssim 20$ m) and deep in-ice detectors, and have also been successfully used to reconstruct cosmic rays with ARIANNA. Here, we focus on the reconstruction algorithm for the deep in-ice detector, which was recently introduced in the context of the Radio Neutrino Observatory in Greenland (RNO-G). We discuss the performance-critical aspects of the algorithm, as well as recent and future improvements, and apply it to study the performance of a station of the IceCube-Gen2 in-ice radio array. We obtain the angular resolution, which turns out to be strongly asymmetric, and use this to optimize the configuration of a single station., Comment: Presented at the 38th International Cosmic Ray Conference (ICRC2023). See arXiv:2307.13048 for all IceCube-Gen2 contributions

IceCube-Gen2 is a planned next-generation neutrino observatory at the South Pole that builds upon the successful design of IceCube. Integrating two complementary detection technologies for neutrinos, optical and radio Cherenkov emission, in combination with a surface array for cosmic ray air shower detection, IceCube-Gen2 will cover a broad neutrino energy range from MeV to EeV. This index of contributions to the 38th International Cosmic Ray Conference in Nagoya, Japan (July 26 - August 3, 2023) describes research and development efforts for IceCube-Gen2. Included are summaries of the design, status, and sensitivity of the IceCube-Gen2 optical, surface, and radio components; performance studies of next-generation optical sensors detecting optical Cherenkov radiation from cosmic ray and neutrino events; reconstruction techniques of radio and optical events in terms of energy, direction, and neutrino flavor; and sensitivity studies of astrophysical neutrino flavors, diffuse neutrino fluxes, and cosmic ray anisotropies. Contributions related to IceCube and the scheduled IceCube Upgrade are available in a separate collection., Comment: To access the list of contributions, please follow the "HTML" link. Links to individual contributions will fill in as authors upload their material

The ARIANNA experiment is an Askaryan radio detector designed to measure high-energy neutrino induced cascades within the Antarctic ice. Ultra-high-energy neutrinos above $10^{16}$ eV have an extremely low flux, so experimental data captured at trigger level need to be classified correctly to retain more neutrino signal. We first describe two new physics-based neutrino selection methods, (the updown and dipole cut) that extend the previously published analysis to a specialized ARIANNA station with 8 antenna channels, which is double the number used in the prior analysis. For a standard trigger with a threshold signal to noise ratio at 4.4, the new cuts produce a neutrino efficiency of > 95% per station-year, while rejecting 99.93% of the background (corresponding to 53 remaining experimental background events). When the new cuts are combined with a previously developed cut using neutrino waveform templates, all background is removed at no change of efficiency. In addition, the neutrino efficiency is extrapolated to 1,000 station-years, obtaining 91%. This work then introduces a new selection method (deep learning (DL) cut) to augment the identification of neutrino events by using DL methods and compares the efficiency to the physics-based analysis. The DL cut gives 99% signal efficiency per station-year of operation while rejecting 99.997% of the background (corresponding to 2 remaining experimental background events), which are then removed by the waveform template cut at no significant change in efficiency. The results of the DL cut were verified using measured cosmic rays which shows the simulations do not introduce artifacts with respect to experimental data. The paper demonstrates the background rejection and signal efficiency of near surface antennas meets the requirements of a large scale future array, as considered in baseline design of the radio component of IceCube-Gen2., Comment: 29 pages, 16 figures, 3 tables

Experiments seeking to detect radio emission stemming from neutrino interactions will soon reach sensitivities that bring a detection within reach. Since experiments like RNO-G or the future IceCube-Gen2 target more than an order of magnitude more effective volume than existing experiments, the renewed and detailed study of rare backgrounds is needed. In this paper, we study the potential background from energy losses of highly energetic atmospheric muons. Due to both limited experimental measurements and limited modeling in hadronic interaction models, the expected event rate is subject to large uncertainties. Here, we estimate rate predictions and their uncertainties for different models and instrumental parameters. We also study possible routes towards mitigation of the muon background, such as parent air shower detection, and illustrate what is needed to make the first measurement of the prompt muon flux at energies above 10 PeV., Comment: 19 pages, 14 figures plus references and appendix, v3 includes minor changes requested by peer review

Measuring the radio emission from cosmic ray particle cascades has proven to be a very efficient method to determine their properties such as the mass composition. Efficient modeling of the radio emission from air showers is crucial in order to extract the cosmic ray physics parameters from the measured radio emission. MGMR3D is a fast semi-analytic code that calculates the complete radio footprint, i.e.\ intensity, polarization, and pulse shapes, for a parametrized shower-current density and can be used in a chi-square optimization to fit a given radio data. It is many orders of magnitude faster than its Monte Carlo counterparts. We provide a detailed comparative study of MGMR3D to Monte Carlo simulations, where, with improved parametrizations, the shower maximum $\Xmax$ is found to have very strong agreement with a small dependency on the incoming zenith angle of the shower. Another interesting feature we observe with MGMR3D is sensitivity to the shape of the longitudinal profile in addition to $\Xmax$. This is achieved by probing the distinguishable radio footprint produced by a shower having a different longitudinal profile than usual. Furthermore, for the first time, we show the results of reconstructing shower parameters for LOFAR data using MGMR3D, and obtaining a $\Xmax$ resolution of 22 g/cm$^2$ and energy resolution of 19\%.

The current generation of air shower radio arrays has demonstrated that the atmospheric depth of the shower maximum Xmax can be reconstructed with high accuracy. These experiments are now contributing to mass composition studies in the energy range where a transition from galactic to extragalactic cosmic-ray sources is expected. However, we are still far away from an unambiguous interpretation of the data. Here we propose to use radio measurements to derive a new type of constraint on the mass composition, by reconstructing the shower length L. The low-frequency part of the Square Kilometer Array will have an extremely high antenna density of roughly 60.000 antennas within one square kilometer, and is the perfect site for high-resolution studies of air showers. In this contribution, we discuss the impact of being able to reconstruct L, and the unique contribution that SKA can make to cosmic-ray science., Comment: Proceedings 9th International Workshop on Acoustic and Radio EeV Neutrino Detection Activities - ARENA2022, 7-10 June 2022, Santiago de Compostela, Spain (8 pages)

Analysis of radio signals from cosmic-ray induced air showers has been shown to be a reliable method to extract shower parameters such as primary energy and depth of shower maximum. The required detailed air shower simulations take 1 to 3 days of CPU time per shower for a few hundred antennas. With nearly $60,000$ antennas envisioned to be used for air shower studies at the Square Kilometre Array (SKA), simulating all of these would come at unreasonable costs. We present an interpolation algorithm to reconstruct the full pulse time series at any position in the radio footprint, from a set of antennas simulated on a polar grid. Relying on Fourier series representations and cubic splines, it significantly improves on existing linear methods. We show that simulating about 200 antennas is sufficient for high-precision analysis in the SKA era, including e.g. interferometry which relies on accurate pulse shapes and timings. We therefore propose the interpolation algorithm and its implementation as a useful extension of radio simulation codes, to limit computational effort while retaining accuracy., Comment: 21 pages, 14 figures. Accepted for publication in JINST (Journal of Instrumentation)

Glacial ice is used as a target material for the detection of ultra-high energy neutrinos, by measuring the radio signals that are emitted when those neutrinos interact in the ice. Thanks to the large attenuation length at radio frequencies, these signals can be detected over distances of several kilometers. One experiment taking advantage of this is the Radio Neutrino Observatory Greenland (RNO-G), currently under construction at Summit Station, near the apex of the Greenland ice sheet. These experiments require a thorough understanding of the dielectric properties of ice at radio frequencies. Towards this goal, calibration campaigns have been undertaken at Summit, during which we recorded radio reflections off internal layers in the ice sheet. Using data from the nearby GISP2 and GRIP ice cores, we show that these reflectors can be associated with features in the ice conductivity profiles; we use this connection to determine the index of refraction of the bulk ice as n=1.778 +/- 0.006.

We explore the possibilities of measuring the longitudinal profile of individual air showers beyond $X_{\rm max}$ when using very dense radio arrays such as SKA. The low-frequency part of the Square Kilometre Array, to be built in Australia, features an enormous antenna density of about $50,000$ antennas in the inner core region of radius 500 m, with a frequency band from 50 to 350 MHz. From CoREAS simulations, a SKA-Low antenna model plus noise contributions, and adapted LOFAR analysis scripts, we obtain a resolution in the shower maximum $X_{\rm max}$ and energy that is considerably better than at LOFAR. Already from this setup, we show that at least one additional parameter of the longitudinal profile can be measured. This would improve mass composition analysis by measuring an additional composition-dependent quantity. Moreover, it would offer an opportunity to discriminate between the different predictions of hadronic interaction models, hence contributing to hadronic physics at energy levels beyond man-made accelerators., Comment: 8 pages, 6 figures. Presented at ARENA Conference 2022, Santiago de Compostela, Spain

In-ice radio detectors are a promising tool for the discovery of EeV neutrinos. For astrophysics, the implications of such a discovery will rely on the reconstruction of the neutrino arrival direction. This paper describes a first complete neutrino arrival direction reconstruction for detectors employing deep antennas such as RNO-G or planning to employ them like IceCube-Gen2. We will didactically introduce the challenges of neutrino direction reconstruction using radio emission in ice, elaborate on the detail of the algorithm used, and describe the obtainable performance based on a simulation study and discuss its implication for astrophysics., Comment: Minor updates for clarity; version accepted for publication

We recently reported on the radio-frequency attenuation length of cold polar ice at Summit Station, Greenland, based on bistatic radar measurements of radio-frequency bedrock echo strengths taken during the summer of 2021. Those data also include echoes attributed to stratified impurities or dielectric discontinuities within the ice sheet (layers), which allow studies of a) estimation of the relative contribution of coherent (discrete layers, e.g.) vs. incoherent (bulk volumetric, e.g.) scattering, b) the magnitude of internal layer reflection coefficients, c) limits on the azimuthal asymmetry of reflections (birefringence), and d) limits on signal dispersion in-ice over a bandwidth of ~100 MHz. We find that i) after averaging 10000 echo triggers, reflected signal observable over the thermal floor (to depths of approximately 1500 m) are consistent with being entirely coherent, ii) internal layer reflection coefficients are measured at approximately -60 to -70 dB, iii) birefringent effects for vertically propagating signals are smaller by an order of magnitude relative to comparable studies performed at South Pole, and iv) within our experimental limits, glacial ice is non-dispersive over the frequency band relevant for neutrino detection experiments.