The dark-matter axion mass (1708.07521v1)

Abstract: We evaluate the efficiency of axion production from spatially random initial conditions in the axion field, so a network of axionic strings is present. For the first time, we perform numerical simulations which fully account for the large short-distance contributions to the axionic string tension, and the resulting dense network of high-tension axionic strings. We find nevertheless that the total axion production is somewhat less efficient than in the angle-averaged misalignment case. Combining our results with a recent determination of the hot QCD topological susceptibility (Borsanyi et al 2016), we find that if the axion makes up all of the dark matter, then the axion mass is m_a = 26.2 +-3.4 micro-electron volts.

• The paper determines an axion mass of roughly 26.2 ± 3.4 μeV by integrating large-tension axionic string dynamics.
• The study employs advanced numerical simulations to reveal a 22% lower axion production efficiency in inhomogeneous setups.
• The findings refine dark matter models and provide concrete parameters for future experimental axion searches.

Overview of "The Dark-Matter Axion Mass"

This paper by Vincent B. Klaer and Guy D. Moore provides a detailed exploration into the dynamics of axion production with a specific focus on its implications for the axion mass as a candidate for dark matter. The authors employed comprehensive numerical simulations to address the contributions and tensions within a network of axionic strings, marking a significant stride in understanding axion production efficiency.

The QCD axion, a hypothetical particle emerging from the Peccei-Quinn mechanism, serves as a potential solution to the strong CP problem and is also a dark matter candidate. In the standard cosmological model, such an axion field begins from spatially random initial conditions post-inflation, resulting in a complex dynamics that includes axionic strings and domain walls.

The authors focused on four primary hypotheses: the existence of axions, PQ symmetry restoration post-inflation with the axion field starting randomly, standard cosmological evolution with expected matter content during axion production, and axions comprising all dark matter. Through their numerical simulations, the authors were able to integrate the large short-distance contributions effectively to the axionic string tension, providing more precise insights into axion number generation.

Numerical Results

A key numerical result of the paper is the establishment of the axion mass, derived from the axion's contribution to the dark matter density. The authors found the axion mass to be approximately $m_a = 26.2\pm 3.4\ \mu\mathrm{eV}$. This value was determined by comparing axion densities in an inhomogeneous setup against a homogeneous, angle-averaged misalignment setup, where the former demonstrated a marginal 22% lesser efficiency in axion production.

Significantly, the authors concluded that high-tension axionic strings, despite their density and robustness, result in only a marginal reduction in axion number production. This finding contrasts with prior assumptions that might have expected higher axion numbers from such setups, suggesting a nuanced dynamical interplay between axonic strings and domain walls.

Implications and Speculations

The robust numerical framework offered by Klaer and Moore solidifies our understanding of axion dynamics, showcasing a methodology that integrates large tension strings effectively. The established axion mass value informs current experimental searches for axions, providing a concrete parameter space for astrophysical and laboratory searches. From a theoretical perspective, this work contributes to constraint-driven model refinement within particle physics.

Moving forward, improved lattice simulations with greater RAM could mitigate volume and numerical artifacts, offering even more refined predictions. Further examination of the late-stage dynamics of string networks could unlock deeper insights into axion production efficiency. As computational resources and algorithmic strategies evolve, such simulations might bridge current gaps and facilitate sharper predictions aligned with observational data.

The research thus aligns with ongoing pursuits in particle physics and cosmology, refining the landscape of dark matter candidates by elucidating properties of hypothetical particles like the axion, and highlighting the interplay between theoretical physics and computational advancements.