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Detection of multiple stellar systems from single-epoch photometry.

Project duration Jan 2024 - In progress

The effort of properly accounting for multiplicity among stars has delivered many studies and thousands of catalogued systems, most recently dwarfed by about 800 thousand characterised binary stars by the ESA’s Gaia mission data release 3. This number is however 3 magnitudes lower than there are sources in the Gaia catalogue, indicating that far more binary stars are yet to be discovered according to the observed multiplicity statistics.

Identifying binary stars through single-epoch photometry

This project is an exploratory study that aims to advance the identification of binary stars. It aims to detect binary stars through single-epoch photometry, whose precision is sufficient to constrain the spectral energy distribution (SED) of a given source at the level necessary (~mmag) for discriminating between single and binary stellar systems. It’s built on the idea that in a wide range of parameter space, a SED of a binary stellar system has a unique shape that cannot be mistaken for a single-star SED.

Distinguishing between stellar systems on this basis enables the detection of otherwise hidden binary stars and the use of less expensive and readily available single-epoch photometric observations.

In this project, we will use colour indices derived from observed photometry and 3D all-sky extinction maps coupled with a parallax (where available) to constrain the shape of the SED and predict the probability of a source being either a single or binary star.

The development of Artificial Intelligence (AI) facilitated the adoption of the underlying machine learning (ML) techniques in many areas of Astrophysics. Specifically, it paved the way for faster and improved detection and analysis techniques in spectroscopy.

Using these techniques, we plan to create a classifier that will be validated on observed binary stars, detected and characterised by large-scale surveys of the sky such as Gaia, Galah, Gaia-ESO, and Apogee. This will provide insight into our method’s capabilities for detection concerning the parameter space covered by properties of binary systems.


  • Faculty of mathematics and Physics, University of Ljubljana
  • European Space Agency (ESA)

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