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Hybrid Active-Passive Galactic Cosmic Ray Simulator: experimental implementation and microdosimetric characterization

Enrico Pierobon, Luca Lunati, Tim Wagner, Marco Durante, Christoph Schuy

TL;DR

The paper addresses the challenge of ground-based Galactic Cosmic Ray (GCR) studies by introducing a European hybrid active-passive GCR simulator that reproduces a space-like radiation field through six sequential configurations weighted to match a 1 AU, solar-minimum environment after aluminum shielding. The approach combines an energy-switching primary beam, passive mesh/complex/slab modulators, TEPC microdosimetry, and Geant4 Monte Carlo validation to characterize the resulting field and extract quality factors. Key contributions include experimental microdosimetric spectra for each configuration, a weighted total spectrum that approximates a GCR field, and validation of the designed quality factor against measurements and space data, supporting the simulator’s relevance for electronics and biology research. The European facility provides a path to bridge physical radiation description with biological outcomes, with planned accessibility in 2026 to enable comprehensive GCR studies on Earth.

Abstract

Space radiation is one of the major obstacles to space exploration. If not mitigated, radiation can interact both with biological and electronic systems, inducing damage and posing significant risk to space missions. Countermeasures can only be studied effectively with ground-based accelerators that act as a proxy for space radiation. Following an in-silico design and optimization process we have developed a galactic cosmic ray (GCR) simulator using a hybrid active-passive methodology. In this approach, the primary beam energy is actively switched and the beam interacts with specifically designed passive modulators. In this paper, we present the implementation of such a GCR simulator and its experimental microdosimetric characterization. Measuring the GCR field is of paramount importance, both before providing it to the user as a validated radiation field and for achieving the best possible radiation description. The issue is addressed in this paper by using a tissue equivalent proportional counter to measure radiation quality and by comparing experimental measurements with Monte Carlo simulations. In conclusion, we will demonstrate the GCR simulator's capability to reproduce a GCR field.

Hybrid Active-Passive Galactic Cosmic Ray Simulator: experimental implementation and microdosimetric characterization

TL;DR

The paper addresses the challenge of ground-based Galactic Cosmic Ray (GCR) studies by introducing a European hybrid active-passive GCR simulator that reproduces a space-like radiation field through six sequential configurations weighted to match a 1 AU, solar-minimum environment after aluminum shielding. The approach combines an energy-switching primary beam, passive mesh/complex/slab modulators, TEPC microdosimetry, and Geant4 Monte Carlo validation to characterize the resulting field and extract quality factors. Key contributions include experimental microdosimetric spectra for each configuration, a weighted total spectrum that approximates a GCR field, and validation of the designed quality factor against measurements and space data, supporting the simulator’s relevance for electronics and biology research. The European facility provides a path to bridge physical radiation description with biological outcomes, with planned accessibility in 2026 to enable comprehensive GCR studies on Earth.

Abstract

Space radiation is one of the major obstacles to space exploration. If not mitigated, radiation can interact both with biological and electronic systems, inducing damage and posing significant risk to space missions. Countermeasures can only be studied effectively with ground-based accelerators that act as a proxy for space radiation. Following an in-silico design and optimization process we have developed a galactic cosmic ray (GCR) simulator using a hybrid active-passive methodology. In this approach, the primary beam energy is actively switched and the beam interacts with specifically designed passive modulators. In this paper, we present the implementation of such a GCR simulator and its experimental microdosimetric characterization. Measuring the GCR field is of paramount importance, both before providing it to the user as a validated radiation field and for achieving the best possible radiation description. The issue is addressed in this paper by using a tissue equivalent proportional counter to measure radiation quality and by comparing experimental measurements with Monte Carlo simulations. In conclusion, we will demonstrate the GCR simulator's capability to reproduce a GCR field.

Paper Structure

This paper contains 20 sections, 2 equations, 8 figures, 2 tables.

Figures (8)

  • Figure 1: Photo of the experimental setup implemented in Cave A.
  • Figure 2: Schematic of the experimental setup of the GCR simulator implemented in Cave A for the TEPC measurement. The picture, for illustrative purposes, shows all the elements in the beam path. Once a GCR simulator configuration has been selected, the elements are removed/inserted into the beamline via remote controllable modulator exchangers accordingly. Item colors are assigned based on their respective materials. Vertical axis is not to scale, all units are in .
  • Figure 3: Scheme of the setup implemented in the Monte Carlo simulation. The picture, for illustrative purposes, shows all the elements in the beam path. Upon selecting a GCR simulator configuration, only the required elements are initialized accordingly. Item colors are assigned to their respective materials. Vertical axis is not to scale, all units are in $mm$.
  • Figure 4: Comparison of experimental (red) and simulated (blue) $f(y)$ distribution for the three complex modulators configurations. Errors are estimated using the statistical error.
  • Figure 5: Comparison of experimental (red) and simulated (blue) $f(y)$ distribution for the three slab modulator configurations. Errors are estimated using the statistical error.
  • ...and 3 more figures