English

Direct detection of solar chameleons with electron recoil data from XENONnT

High Energy Physics - Phenomenology 2026-05-29 v2 Cosmology and Nongalactic Astrophysics General Relativity and Quantum Cosmology High Energy Physics - Experiment

Abstract

We reassess prospects for direct detection of solar chameleons, in light of recent progress in modeling their production, and the availability of new XENONnT data. We show that the contribution from Primakoff production in the electric fields of electrons and ions dominates the electron recoil event rate, which is enhanced compared to earlier estimates based on magnetic conversion in the tachocline alone. We argue that the signal is governed by the effective coupling βeffβγMe4\beta_{\text{eff}} \equiv \beta_{\gamma}M_e^{-4}, which encodes the combined effects of production and detection, where βγ\beta_{\gamma} and MeM_e are the chameleon-photon (conformal) coupling and chameleon-electron disformal coupling scale, respectively. Setting the height of the chameleon potential to the dark energy (DE) scale Λ2.4meV\Lambda \simeq 2.4\,{\text{meV}}, we show that XENONnT electron recoil data set the upper limit log10βeff<6.9\log_{10}\beta_{\text{eff}}<-6.9. This limit is independent of the conformal matter coupling βm\beta_m and index nn, and applies to the whole class of inverse power-law chameleons, well beyond the n=1n=1 case usually studied. We comment on how future multi-target experiments and lower-threshold analyses could distinguish solar chameleons from other light (pseudo)scalar particles such as axions. Our work demonstrates that existing dark matter direct detection experiments can probe regions of parameter space relevant to screened DE models, providing complementary tests to astrophysical and fifth-force searches at no additional experimental cost.

Keywords

Cite

@article{arxiv.2511.01655,
  title  = {Direct detection of solar chameleons with electron recoil data from XENONnT},
  author = {Guan-Wen Yuan and Anne-Christine Davis and Maurizio Giannotti and Sunny Vagnozzi and Luca Visinelli and Julia K. Vogel},
  journal= {arXiv preprint arXiv:2511.01655},
  year   = {2026}
}

Comments

23 pages, 8 figures. v2: additional references added, very minor changes to code and figures. Version accepted for publication in PRD. Code available at https://github.com/yuanguanwen/Chameleon_Detection