arXiv subjects

Keito Watanabe

Publications and source records attributed to Keito Watanabe.

11 recordsLinked to original sources

arXiv2026

Reconstruction of anomalous air showers with SKA-Low

Double-bump showers are a surprising class of extensive air showers (EAS) predicted by Monte Carlo simulations, which, so far, no experiment has been able to directly detect. They occur when a high-energy secondary particle, the leading particle, travels significantly farther than the rest, creating a distinct double-peaked longitudinal profile. The unique radio footprint of double-bump showers, characterized by multiple pulses in the signals and interference patterns in the frequency spectra, enables reconstruction of longitudinal profiles from radio observations. With its dense antenna array and broad frequency range, SKA-Low will be the first observatory capable of detecting these features, offering a new opportunity to probe hadronic interactions and use the distinctive signatures of elements to provide new mass composition measurements. The goal of this analysis is to take the first steps toward using these radio signatures to reconstruct the relevant parameters of the longitudinal profile of a double-bump shower. We will start by explaining the radio signal of double-bump}showers compared to that of average showers. Then we will create a simple 2-point emission model to explain the interference patterns in the frequency spectra, which can be inverted to obtain rudimentary estimates of atmospheric depth of both peaks. Lastly, we implement a brute-force approach to reconstruct multiple parameters of the double bump.

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arXiv2026

Beyond $X_\mathrm{max}$ : Reconstructing Air Shower Profiles with Information Field Theory with SKA-Low

While radio measurements of extensive air showers have shown to achieve a high precision of $X_\mathrm{max}$ sensitivity, it has been shown that parameters beyond $X_\mathrm{max}$ can also be reconstructed. These shape parameters contain additional sensitivity to the hadronic physics in the shower as well as its mass composition. In this work, we showcase a reconstruction framework to recover the full longitudinal profile from realistic radio measurements. The framework is based on Information Field Theory that infers the full profile with a forward-based model, which uses a Gaisser-Hillas profile with weakly informative shower priors, SMIET with a template library to synthesise pulses at any event geometry, and a realistic antenna response and noise level emulating that of SKA-Low. We verify the self-consistency of our framework with $\sim 900$ events generated with SMIET with antennas placed on the $\vec{v} \times (\vec{v} \times \vec{B})$ axis. The framework recovers the full profile within uncertainty and capture correlations between shower parameters. We yield an $X_\mathrm{max}$ resolution of $< 9$ g cm$^{-2}$ as well as resolutions of the width and asymmetry with minimal bias. The profile is also recovered with a bias of $< 4$% at all atmospheric depths $< 1200$ g cm$^{-2}$. We aim to apply this framework with pulses simulated from CoREAS with measured noise, ultimately extending the framework to realistic antenna layouts such as from LOFAR or SKA-Low.

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arXiv2026

Unveiling the Mysteries of Lightning: Exploring its fundamental Physical Processes with SKA-LOW

Lightning is a surprisingly poorly understood phenomena. It consists of a wide variety of complex processes such as initiation, propagation, connection to ground, even emission of high-energy radiation. However, due to the extreme challenges in observing lightning at fast time scales, small spatial scales, and behind obscuring clouds, these processes are not well understood. In the past, interferometers such as the LOFAR radio telescope have provided unique insight and discoveries into the physics of lightning. The new SKA-LOW being built in western Australia will provide unrivaled spectral bandwidth and sensitivity, which will be combined with high resolution resulting from large antenna baselines. We will use SKA-LOW to observe lightning in order to explore its fundamental plasma physics, such as how it initiates and propagates. SKA's high bandwidth will allow us to test how lightning emits VHF radiation, giving tremendous insight into precisely how the plasma behaves. SKA's sensitivity will allow us to explore extremely faint lightning processes, such as the very first radio emission from a lightning flash. Here, we detail the lightning physics that can be explored with SKA, as well as the observation strategy needed explore such physics.

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arXiv2026

Anomalous Air Showers and What They Reveal About Hadronic Interactions and Cosmic-ray Masses

The identification of the sources and acceleration mechanisms of cosmic rays require precise measurements of their mass composition. Currently, the most reliable method is to measure the atmospheric depth at which cosmic ray air showers in our atmosphere reach their maximum (\Xmax). However, the hadronic interaction properties that govern the longitudinal development of air showers are not precisely known, which is a major source of systematic uncertainty on the mass composition. SKA-Low will observe cosmic rays in the 10$^{16}$ - 10$^{18}$ eV energy range with unprecedented resolution and bandwidth. This allows for a much more detailed reconstruction of the longitudinal shower evolution, which can be used to gain better understanding of the hadronic interactions, as well as the primary mass composition. After the first interaction of the cosmic ray with an atom in an air molecule, the secondary particles still carry a significant fraction of the total energy. When one of these particle travels very far before interacting again, it produces a sub-shower that can be recognized as a secondary bump in the longitudinal profile. Simulations have demonstrated that SKA-Low can resolve such double bump profiles by virtue of its high antenna density and broad bandwidth. In this chapter, we demonstrate how double-bump showers and other anomalous longitudinal developments can be used to constrain hadronic interaction properties, and to determine the mass composition of cosmic rays in the Galactic-to-extragalactic transition region.

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arXiv2026

Measuring High-Energy Cosmic Particles with the SKA

The origin of high-energy cosmic rays remain one of astrophysics' greatest unsolved mysteries. SKA-Low will be able to measure air showers initiated by cosmic rays with unprecedented precision in the PeV - EeV energy range, covering the critical transition region between Galactic and extragalactic sources. SKA-Low's densely instrumented core and broad bandwidth will allow for measurements of individual air showers with a level of detail unmatched by any existing or planned detector. The depth of shower maximum, the primary mass-sensitive observable, will be reconstructed with a resolution of better than 8~g/cm$^2$, a significant improvement over existing methods. Additionally, new reconstruction methods are expected to enable full air shower reconstruction across a wide energy range, down to PeV levels. At these energies, efficient photon/hadron separation may offer an opportunity to measure PeV gamma-ray air showers. Furthermore, SKA-Low opens a window into studying high-energy hadronic interactions, including via the unique channel of anomalous air showers. This combination of measurements provides a unique opportunity to investigate the origins and physics of high-energy cosmic rays. A dedicated particle detector array will provide triggered readout of raw antenna-level voltage buffers, enabling fully commensal cosmic-ray observations alongside regular operations. We outline our science case and discuss the observational strategy, signal properties and detector design underpinning these measurements. We also summarize the accompanying book chapters, which address composition measurements in the Galactic-to-extragalactic transition region, next-generation interferometric reconstruction techniques, hadronic interaction physics through anomalous air showers, the prospects for detecting PeV gamma-rays from Galactic sources, and the related project of imaging lightning using SKA-Low.

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arXiv2026

Interferometric Analysis of Air-shower Radio Emission in the Near Field with an Information Field Theory Approach

Current reconstruction techniques for air-shower radio emission generated by cosmic rays have shown great success, having been applied to several radio detectors over the last decade. Nevertheless, they are limited by their high computational cost, simplified approximations, and signal information used for reconstruction. As such, advanced analyses are required to not only be able to perform a holistic reconstruction of all parameters, but also to conduct near-field interferometry of the air shower. This can be achieved through Information Field Theory (IFT), an imaging reconstruction framework based on Bayesian inference that can extract all available information within the signal to infer distributions of field-like quantities. In this chapter, we highlight current novel approaches that use IFT for air shower reconstruction, and the potential of their applicability towards SKA-Low.

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arXiv2026

Using SKA-Low to Detect PeV Gamma-rays from Galactic Sources

Detecting so called PeVatrons is considered one of the prime goals of $\gamma$-ray astronomy. PeVatrons are astrophysical objects in the Galaxy that are sources of cosmic rays exceeding PeV ($10^{15}$ eV) energies, the highest in our Galaxy. Their nature is unknown as of now, with some candidates reaching barely above PeV energies just having been identified. Serendipitously, the energy threshold of air shower detection using radio emission, has been proven at 50 PeV. There is a case to be made that SKA-Low with its unprecedented number of antennas, can reach lower in energy, while the size of the core is sufficiently large provide a significant effective area to measure PeV fluxes. While this promises a novel angle towards understanding the cosmic ray accelerators in our Galaxy, it also would be the first detection of $\gamma$-ray air showers using radio emission.

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arXiv2026

A Bayesian Method for Air-Shower Reconstruction using Information Field Theory

The radio detection of extensive air showers provides a powerful method for studying the origin of high-energy cosmic rays. The Low-Frequency Array (LOFAR) offers unprecedentedly detailed measurements of the radio emission footprint. However, fully exploiting this information requires advanced reconstruction techniques. In this paper, we introduce a novel framework for air shower reconstruction based on Bayesian inference and Information Field Theory (IFT). Our method is built on a fully differentiable forward model of the radio signal, which incorporates a physical emission parameterization and a precise wavefront model. Additionally, we augment this physical model with Gaussian processes to account for systematic uncertainties in both the signal fluence and arrival timing. By leveraging gradient information, our approach enables efficient (three orders of magnitude acceleration w.r.t.\ the legacy method) and robust inference of the underlying physical shower parameters, such as primary energy and the depth of shower maximum, $X_\text{max}$. This work provides not only point estimates but also a rigorous quantification of uncertainties. We achieve a resolution in $X_\text{max}$ of $25\,\mathrm{g/cm^2}$ and a radiation energy resolution of $12\%$ on simulations for LOFAR.

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arXiv2025

Impact of Cosmic Ray Acceleration on the Early Evolution of Bow Shocks around Massive Runaway Stars

Bow shocks generated from the interaction of winds from massive runaway stars with the interstellar medium have been shown to be prominent particle accelerators through recent $\gamma$-ray and radio synchrotron observations. Here, we study particle acceleration from bow shocks by conducting 3D ideal cosmic ray magnetohydrodynamic simulations in the advection-diffusion limit. We use the Eulerian grid-based code FLASH, where stellar winds are injected through tabulated wind velocities and mass loss rates. We implement a gradient-based shock detection algorithm to resolve the shocked regions where the CRs are injected dynamically. Simulations are performed for different values of the CR diffusion coefficient and star velocities within an ISM-like environment up to 180 kyr to showcase the impact of dynamical CR injection on the early evolution of the wind-driven bow shock. With a simplified spectral model in post-processing, we calculate the expected upper limits of $\gamma$-ray and synchrotron emission and compare with those from current observations. We observe that variations of CR diffusion rates can strongly dictate the morphology of the bow shock and the overall $\gamma$-ray and radio synchrotron luminosity due to the balance between the CR injection efficiency and diffusion. Our results yield qualitatively comparable results with current observations, primarily attributed to the high-energy protons and electrons contributing to non-thermal emission from efficient acceleration at the forward shock through the approximations and assumptions in the injection algorithm. We conclude that CR acceleration, with varying CR diffusion rates, may substantially affect the morphology of wind-driven bow shocks and their non-thermal emission, if there is efficient particle acceleration in the forward shock. [abridged]

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arXiv2025

A Bayesian Framework for UHECR Source Association and Parameter Inference

The identification of potential sources of ultra-high-energy cosmic rays (UHECRs) remains challenging due to magnetic deflections and propagation losses, which are particularly strong for nuclei. In previous iterations of this work, we proposed an approach for UHECR astronomy based on Bayesian inference through explicit modelling of propagation and magnetic deflection effects. The event-by-event mass information is expected to provide tighter constraints on these parameters and to help identify unknown sources. However, the measurements of the average mass through observations from the surface detectors at the Pierre Auger Observatory already indicate that the UHECR masses are well represented through its statistical average. In this contribution, we present our framework which uses energy and mass moments of $\ln A$ to infer the source parameters of UHECRs, including the mass composition at the source. We demonstrate the performance of our model using simulated datasets based on the Pierre Auger Observatory and Telescope Array Project. Our model can be readily applied to currently available data, and we discuss the implications of our results for UHECR source identification.

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arXiv2025

SMIET: Fast and accurate synthesis of radio pulses from extensive air shower using simulated templates

Interpreting the data from radio detectors for extensive air showers typically relies on Monte-Carlo based simulation codes, which, despite their accuracy are computationally expensive and present bottlenecks for analyses. To address this issue we developed a novel method called template synthesis, which synthesises the radio emission from cosmic ray air showers in seconds. This hybrid approach uses a microscopically simulated, sliced shower (the origin) as an input. It rescales the emission from each slice individually to synthesise the emission from a shower with different properties (the target). In order to be able to change the arrival direction during synthesis, we adjust the phases based on the expected geometrical delays. We benchmark the method by comparing synthesised traces to CoREAS simulations over a wide frequency range of [30, 500] MHz . The synthesis quality is primarily influenced by the difference in $X_{max}$ between the origin and target shower. When $\Delta X_{max} \leq 100 g/cm^2$ , the scatter on the maximum amplitudes of the geomagnetic traces is at most 4%. For the traces from the charge-excess component this scatter is smaller than 6%. We also observe a bias with $\Delta X_{max}$ up to 5% for both components, which appears to depend on the antenna position. Since the bias is symmetrical around $\Delta X_{max} = 0 g/cm^2$, we can use an interpolation approach to correct for it. We have implemented the template synthesis algorithm in a Python package called \texttt{SMIET}, which includes all the necessary parameters. This package has been successfully tested with air showers with zenith angles up to $50^{\circ}$ and can be used with any atmosphere, observation level and magnetic field. We demonstrate that the synthesis quality remains comparable to our main benchmarks across various scenarios and discuss use cases, including machine-learning-based analyses.

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