Robust high-contrast companion detection from interferometric observations. The CANDID algorithm and an application to six binary Cepheids
A. Gallenne, A. M\'erand, P. Kervella, J. D. Monnier, G. H. Schaefer,, F. Baron, J. Breitfelder, J. B. Le Bouquin, R. M. Roettenbacher, W. Gieren,, G. Pietrzynski, H. McAlister, T. ten Brummelaar, J. Sturmann, L. Sturmann, N., Turner, S. Ridgway, S. Kraus

TL;DR
This paper introduces the CANDID algorithm, a robust Python tool for detecting high-contrast companions in interferometric data, demonstrated through application to six binary Cepheids, improving detection confidence and limits.
Contribution
The paper presents CANDID, a new systematic method and software for high-contrast companion detection in interferometry, with analytical detection limits and validation on real binary Cepheid data.
Findings
Confirmed previous companions with >13 sigma significance.
Detected a new companion around AW Per at >15 sigma.
Set upper limits on undetected companions' spectral types.
Abstract
Long-baseline interferometry is an important technique to spatially resolve binary or multiple systems in close orbits. By combining several telescopes together and spectrally dispersing the light, it is possible to detect faint components around bright stars. Aims. We provide a rigorous and detailed method to search for high-contrast companions around stars, determine the detection level, and estimate the dynamic range from interferometric observations. We developed the code CANDID (Companion Analysis and Non-Detection in Interferometric Data), a set of Python tools that allows us to search systematically for point-source, high-contrast companions and estimate the detection limit. The search pro- cedure is made on a N x N grid of fit, whose minimum needed resolution is estimated a posteriori. It includes a tool to estimate the detection level of the companion in the number of sigmas.…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astro and Planetary Science · Astrophysics and Star Formation Studies
