A Unified Charge-Dependent Modulation Model for AMS-02 Proton and Antiproton Fluxes during Solar Minimum

TL;DR

Addresses charge-sign dependent solar modulation by solving the $3$-dimensional Parker transport equation with a wavy heliospheric current sheet to model drift effects. Combines a GALPROP-derived local interstellar spectrum with HELPROP drift physics and uses PropMat neural surrogates to enable fast global fits to AMS-02 proton and antiproton fluxes and Voyager LIS data during solar minimum. Demonstrates that a unified, physically motivated modulation model can reproduce the observed proton and antiproton fluxes across time with reasonable parameters, capturing tilt-angle dependent drift signatures that differ between positive and negative charges. Provides a computationally efficient framework for integrating Galactic propagation and heliospheric modulation, extendable to electrons/positrons and other solar conditions.

Abstract

We develop a unified charge-dependent solar modulation model by solving the three-dimensional Parker transport equation, incorporating a realistic wavy heliospheric current sheet to treat drift effects self-consistently. Using a local interstellar spectrum from GALPROP constrained by Voyager data, we fit the model to time-resolved proton and antiproton fluxes measured by the Alpha Magnetic Spectrometer - 02 (AMS-02) during the solar-quiet period (May 2011 to June 2022). To enable rapid parameter scans, we employ neural-network-based surrogate models to compute propagation and modulation matrices efficiently. The results demonstrate that the model simultaneously describes the observed proton and antiproton fluxes with physically reasonable parameters, providing a unified account of charge-dependent modulation.

Figures (8)

• Figure 1: Representative particle trajectories simulated with HELPROP for A > 0 polarity. The red and blue curves correspond to the proton and antiproton tracks, respectively. The gray wavy line denotes the HCS.
• Figure 2: Deep learning architecture for spectral data processing in space physics, featuring propagation matrix (PropMat) generation and analysis across spatial domains (Galaxy and Heliosphere) using an encoder-decoder framework.
• Figure 3: Prediction accuracy of proton's LIS, which is below the corresponding uncertainty of the AMS-02 experiment.
• Figure 4: Prediction accuracy of the modulated proton spectrum, which is below the corresponding uncertainty of the AMS-02 experiment.
• Figure 5: Magnetic field strength $B_0$ and tilt angle $\alpha$ as functions of Bartels rotation. The curves represent measurements from Ref. smithACEMagneticFields1998hoeksemaLargeScaleStructureHeliospheric1995, with dashed segments corresponding to active periods and solid segments to solar minimum. Stars mark the rotations selected for training during solar minimum.