High-Quality Axion Models with the Anomalous $U(1)_X$ Gauge Symmetry

TL;DR

This paper introduces high-quality axion models with an anomalous $U(1)_X$ gauge symmetry, solving the axion quality problem and achieving gauge coupling unification with minimal vector-like particles.

Contribution

It presents novel axion models with anomalous $U(1)_X$ symmetry, demonstrating anomaly cancellation, axion quality enhancement, and gauge coupling unification with fewer particles than previous models.

Findings

Axion quality problem is solved via high-dimensional operators of dimension eleven or higher.

Three specific models with two pairs of vector-like particles are constructed and shown to cancel anomalies.

Gauge coupling unification is achieved at around $10^{16}$ GeV with minimal additional particles.

Abstract

We propose the generic high-quality axion models with anomalous $U(1)_X$ gauge symmetry and vector-like particles. We briefly review the gauge anomaly cancellations via the Green-Schwarz mechanism, study the breaking of the $U(1)_X$ gauge symmetry, as well as derive the Nambu-Goldstone boson, Peccei-Quinn (PQ) axion, and axion decay constant in general. The high-dimensional operators, which break the $U(1)_{PQ}$ global symmetry, have dimension eleven or higher due to the anomalous $U(1)_X$ gauge symmetry, and thus the axion quality problem is solved. In particular, unlike the high-quality axion models with anomaly free $U(1)$ gauge symmetry, we only need to introduce two pairs of vector-like particles. To be concrete, we present three specific models with two pairs of vector-like particles. We show that gauge anomalies in all three models can be canceled via the Green-Schwarz mechanism. To achieve gauge coupling unification, we need to introduce additional vector-like particles only in Model I. We find that gauge coupling unification is achieved at the unification scale around $10^{16}$ GeV with a relative error of less than 1\%. Notably, gauge coupling unification in Model II is achieved naturally with the smallest relative error of 0.1\%.