New Particles at the Z-Pole: Tera-Z factories as discovery and precision machines

TL;DR

Future Tera-Z colliders like FCC-ee and CEPC could discover or precisely measure new particles with extremely small couplings to the Z-boson, acting as both discovery and precision machines.

Contribution

The paper provides simple analytic estimates for the sensitivity of Tera-Z factories to long-lived particles, including a code for generating sensitivity curves.

Findings

Potential to produce millions to billions of new particles like heavy neutral leptons and axion-like particles.

Analytic estimates can effectively assess the sensitivity of future colliders for new physics searches.

The provided code enables quick generation of sensitivity curves for various models.

Abstract

Several proposed future lepton colliders are capable of producing trillions of Z-bosons, including FCC-ee, CEPC, LEP3 and LEP-Z. Such Tera-Z factories can discover new elementary particles with couplings to the Z-boson that are orders of magnitude smaller than current bounds. For couplings near the currently excluded parameter regions they could produce sufficiently large samples to study the new particles' properties in detail, hence acting as a discovery and precision machine in one. Using simple analytic estimates, we quantify the dependence of the expected event yield in long-lived particle searches on the number of produced Z-bosons and on the detector dimensions. From this, we derive estimates for both the discovery reach and the measurement precision attainable at such facilities. While the precision of such estimates of course falls short of proper simulations, the analytic approach is suitable for a quick assessment of the sensitivity for a given design. We illustrate this with two examples, heavy neutral leptons and axion-like particles. Under optimistic assumptions, these could be produced in the millions and billions, respectively, effectively turning future lepton colliders into exotics factories. We provide a code that quickly generates the sensitivity curves displayed in this work and can be extended to other models at https://github.com/liyuanzhen98/LLPatTeraZ.