Expected Sensitivity of the Light Dark Matter eXperiment to Long-Lived Dark Photons and Axion-Like Particles

TL;DR

LDMX, primarily designed for sub-GeV dark matter detection via missing energy, can also effectively search for long-lived dark photons and axion-like particles, expanding its exploration of the dark sector.

Contribution

This paper provides the first detailed simulation-based evaluation of LDMX's sensitivity to long-lived, visibly decaying particles like dark photons and axion-like particles.

Findings

LDMX can achieve competitive sensitivity to long-lived particles.

The analysis incorporates realistic detection efficiencies and background levels.

LDMX's dual search strategy enhances its capability to explore the dark sector.

Abstract

The Light Dark Matter eXperiment (LDMX) is an electron-beam fixed-target experiment primarily designed to achieve world-leading, model-independent sensitivity to sub-GeV dark matter particles. LDMX aims to identify dark sector particle production through the detection of events with substantial missing energy and momentum, a signature of invisible particles escaping detection. Beyond this primary objective, LDMX offers a complementary search strategy for long-lived, visibly decaying particles, such as dark photons and axion-like particles. We present the first detailed evaluation of the ability of LDMX to identify visibly decaying, long-lived particles that couple to electrons using a detailed simulation, based on the Geant4-toolkit, that incorporates realistic detection efficiencies and background levels. We demonstrate that LDMX can achieve a sensitivity that is competitive with other experiments that are currently running. The models explored in this paper are distinct and complementary to those probed in the LDMX flagship missing-momentum analysis. Through searching for both invisible dark matter and visibly decaying long-lived signatures, LDMX will significantly advance the search for light dark matter and provide a broad exploration of the sub-GeV dark sector.