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PreprintCC BY 4.0arXiv

Near-exact Upper Confidence Limits for Axion Haloscopes

  • Andrea Gallo Rosso
  • Jan Conrad
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Abstract

The data acquisition of axion haloscopes commonly implements sequential adaptive frequency scans. We present a method to calculate likelihood-based upper confidence limits on axion-photon coupling under this circumstance. We compare the likelihood-based method conceptually and quantitatively with tailor-made methods, i.e. the one proposed by Brubaker et al. (Geometric) and its upgrade the Bayesian Power-Measured (BPM) framework proposed by Palken et al. We find that the likelihood method yields average upper limits that are significantly more constraining than those obtained from these methods. For example, expected constraints improve by a factor of 1.4 as compared with the current state of the art when applied to projections for the ALPHA Plasma-haloscope. We further clarify the statistical basis for the Geometric and BPM methods. In particular, we point out the correspondence of BPM to e-values, proposed as an alternative to conventional p-values in statistics.

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Cite

BibTeXRIS
BibTeX
@misc{rosso2026nearexact,
  title = {{Near-exact Upper Confidence Limits for Axion Haloscopes}},
  author = {Andrea Gallo Rosso and Jan Conrad},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.34325},
  eprint = {2610.34325},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.34325},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Near-exact Upper Confidence Limits for Axion Haloscopes
AU  - Andrea Gallo Rosso
AU  - Jan Conrad
PY  - 2026
DA  - 2026/10/25
PB  - arXiv
DO  - 10.48550/arxiv.2610.34325
UR  - https://arxiv.org/abs/2610.34325
AB  - The data acquisition of axion haloscopes commonly implements sequential adaptive frequency scans. We present a method to calculate likelihood-based upper confidence limits on axion-photon coupling under this circumstance. We compare the likelihood-based method conceptually and quantitatively with tailor-made methods, i.e. the one proposed by Brubaker et al. (Geometric) and its upgrade the Bayesian Power-Measured (BPM) framework proposed by Palken et al. We find that the likelihood method yields average upper limits that are significantly more constraining than those obtained from these methods. For example, expected constraints improve by a factor of 1.4 as compared with the current state of the art when applied to projections for the ALPHA Plasma-haloscope. We further clarify the statistical basis for the Geometric and BPM methods. In particular, we point out the correspondence of BPM to e-values, proposed as an alternative to conventional p-values in statistics.
ER  -