First observation and analysis of DANCE: Dark matter Axion search with riNg Cavity Experiment
Yuka Oshima, Hiroki Fujimoto, Masaki Ando, Tomohiro Fujita, Jun'ya, Kume, Yuta Michimura, Soichiro Morisaki, Koji Nagano, Hiromasa Nakatsuka,, Atsushi Nishizawa, Ippei Obata, Taihei Watanabe

TL;DR
The paper reports the first observation and analysis of DANCE, a novel experiment using a ring cavity to search for axion dark matter by detecting polarization rotation, demonstrating technical feasibility and setting new sensitivity limits.
Contribution
This work introduces DANCE, a new ring cavity experiment for axion detection, and presents initial results from a prototype demonstrating its potential and technical viability.
Findings
Successful first 12-day observation period.
Achieved sensitivity of 3×10⁻⁶ rad/√Hz at 10 Hz.
Demonstrated feasibility of polarization rotation detection with ring cavity.
Abstract
Dark matter Axion search with riNg Cavity Experiment (DANCE) was proposed to search for axion dark matter [Phys. Rev. Lett. 121, 161301 (2018)]. We aim to detect the rotation and oscillation of optical linear polarization caused by axion-photon coupling with a bow-tie cavity. DANCE can improve the sensitivity to axion-photon coupling constant for axion mass by several orders of magnitude compared to the best upper limits at present. A prototype experiment DANCE Act-1 is ongoing to demonstrate the feasibility of the method and to investigate technical noises. The optics was assembled and the performance of the cavity was evaluated. The first 12-day observation was successfully performed in May 2021. We reached at in the one-sided amplitude spectral density of the rotation angle of linear…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsDark Matter and Cosmic Phenomena · Computational Physics and Python Applications · Chemical and Physical Properties of Materials
