Terahertz-Radiometer for AXions (T-RAX): Simulations of Plasmonic Materials for Enhanced Detection of meV Dark Matter

ORAL

Abstract

The direct detection of dark matter (DM) is critical for understanding its identity and properties—mass, spin, and couplings—and would also solve many fundamental questions in particle physics and cosmology, but its weak energy deposition is difficult to detect. Axions are a particularly well-motivated DM candidate, entering as a solution to the standard model’s strong charge-parity problem. Many experiments and proposals search various axion masses using the Primakoff effect (axion-photon conversion in a magnetic field), yet the meV (THz) regime remains poorly constrained. Dielectric and plasma haloscopes operating at low frequencies require smaller and more precise structures for the THz range, and material resonance detectors for higher frequencies suffer from a lack of well-studied low-loss THz materials. Mechanical tuning limits practicality in both. We propose a THz-Radiometer for AXions (T-RAX) using recent advancements in semiconductor quantum structures and metamaterials with electromagnetically tunable plasma frequencies for meV DM detection. We simulate several materials including quantum well and graphene metamaterials with experimentally obtained properties and show resonant enhancements of the axion-induced electromagnetic signal reaching significant power boosts.

*This material is based upon work supported by the National Science Foundation Graduate Research Fellowship. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation.

Publication: Planned paper: T-RAX (Terahertz-Radiometer for AXions): New Materials for Enhanced Detection of meV Dark Matter

Presenters

  • Jaanita S Mehrani

    • Rice University

Authors

  • Jaanita S Mehrani

    • Rice University
  • Shengxi Huang

    • Rice University
  • Junichiro Kono

    • Rice University
  • Kuver Sinha

    • University of Oklahoma
  • Tao Xu

    • University of Oklahoma
  • Andrew J Long

    • Rice University
  • Andrey Baydin

    • Rice University
  • Henry O Everitt

    • Rice University