BAYESIAN ANALYSIS OF COSMIC RAY PROPAGATION: EVIDENCE AGAINST HOMOGENEOUS DIFFUSION

Area of Science:

• Astrophysics
• Cosmic Ray Physics
• Computational Physics

Background:

• Cosmic ray (CR) injection and propagation models are crucial for understanding astrophysical phenomena.
• Previous studies often calibrated propagation parameters using light element ratios like B/C and 10Be/9Be.

Purpose of the Study:

• To conduct the most comprehensive scan of the parameter space for cosmic ray injection and propagation.
• To investigate the distinct propagation parameters required for low-mass isotopes versus light elements.

Main Methods:

• Employed a Bayesian search using the MultiNest nested sampling algorithm, enhanced by the BAMBI machine-learning package.
• Separated low-mass isotopes (protons, helium) from light elements (Be, B, C, N, O) for independent analysis.
• Performed a detailed scan of the GALPROP parameter space.

Main Results:

• Found significantly different propagation parameters best-fitting low-mass isotopes compared to light elements.
• Demonstrated that B/C and 10Be/9Be ratios do not adequately represent propagation for all species.
• Identified distinct interstellar medium properties probed by different elemental groups.

Conclusions:

• The standard approach of calibrating CR propagation parameters using B/C ratios can lead to inaccurate models.
• Separate sets of propagation parameters are necessary for low-mass isotopes and light elements.
• New GALPROP parameters will be released to improve future cosmic ray propagation models.