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The bound origin of low-mass stellar binaries

Nature Astronomy (2025)Cite this article

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Abstract

Most main sequence stars, unlike our Sun, belong to multiple systems containing two or more stars. How and when these multiples come together and become bound is uncertain, as the earliest stages of star formation are difficult to resolve. Here we analyse simulations of star cluster formation in Milky Way-like conditions, including all key physics and stellar feedback mechanisms, to understand how multiple systems form. We show that ~70–80% of binaries are gravitationally bound from the moment the second star forms. Binaries evolve and accrete together, which will affect their planetary systems and chemical evolution. Half of the binaries are disrupted by the end of the star-formation epoch, such that ~40% of the final single stars belonged to a multiple at some point, with implications for the stellar initial mass function. Formation in multiples is the dominant mode of star formation, accounting for at least 57% of stars.

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Fig. 1: Example binaries and surrounding gas at formation.
Fig. 2: Boundedness of binary pairs at formation.
Fig. 3: Distribution of binary velocities and formation times.
Fig. 4: Schematic summarizing basic statistics on binary formation and survival.
Fig. 5: Ratio of the number of surviving to disrupted binaries versus the final mass of the binary stars.

Data availability

The full snapshots, containing gas and sink data from the underlying STARFORGE simulations, are available upon request to M.Y.G. at mgrudic@flatironinstitute.org.

Code availability

The scripts used to compute halos, identify multiples and generate figures are published as a Code Ocean capsule at https://doi.org/10.24433/CO.6648239.v1. We made use of ChatGPT for code refactoring. This project made use of the open-source package pytreegrav, available via GitHub at https://github.com/mikegrudic/pytreegrav, for the calculation of tidal forces. The open-source package Meshoid, available via GitHub at https://github.com/mikegrudic/meshoid, was used for the visualization in Fig. 1. STARFORGE uses a numerical framework implemented in the Gizmo code. The public version of the Gizmo code, which includes self-gravity, MHD, radiation transfer and various other physics modules is available at https://bitbucket.org/phopkins/gizmo-public/src/master/.

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Acknowledgements

We thank J. Farias for helpful comments and discussions. A.G. was supported at the Technion by a Zuckerman Fellowship. A.G., S.S.R.O. and K.M.K. acknowledge support from NSF AAG 2407522. S.S.R.O. also acknowledges support from a Peter O’Donnell Research Fellowship and a Donald Harrington Faculty Fellowship. We acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing computational resources that have contributed to the research results reported within this Article (http://www.tacc.utexas.edu).

Author information

Author notes

  1. These authors contributed equally: Stella S. R. Offner, Kaitlin M. Kratter, Hagai B. Perets.

Authors and Affiliations

  1. Physics Dept, Technion Israel Institute of Technology, Haifa, Israel

    Aleksey Generozov & Hagai B. Perets

  2. Astronomy Dept, University of Texas at Austin, Austin, TX, USA

    Aleksey Generozov, Stella S. R. Offner & Dávid Guszejnov

  3. Oden Institute, University of Texas at Austin, Austin, TX, USA

    Aleksey Generozov & Stella S. R. Offner

  4. Steward Obs and Astronomy Dept, University of Arizona, Tuscon, AZ, USA

    Kaitlin M. Kratter

  5. Department of Natural Sciences, Astrophysics Research Center of the Open University, Raanana, Israel

    Hagai B. Perets

  6. Center for Computational Astrophysics, Flatiron Institute, New York, NY, USA

    Michael Y. Grudić

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  1. Aleksey Generozov
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Contributions

A.G. developed code for multiple and gas halo identification, with help from D.G., and carried out the analysis. M.Y.G. ran the STARFORGE simulation models. S.S.R.O. provided expertise related to the STARFORGE simulations and facilitated the analysis. A.G., S.S.R.O., K.M.K. and H.B.P. contributed to the interpretation and discussion of the results and writing and editing of the paper.

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Correspondence to Aleksey Generozov.

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Nature Astronomy thanks G. N. Dremova, Francesco Flammini Dotti and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Early evolution of orbital elements and masses for example binaries.

Early evolution of the semi-major axes (top), eccentricities (middle) for example binaries. When the binary is bound, the eccentricity and semi-major axis are a thick, brown line. If the stars’ are bound to other objects their orbital elements are thin orange or purple lines. For reference, we show the stars’ gravitational softening length as a horizontal gray line in the top panels. The bottom panels show the mass evolution for these binaries. The solid lines show the mass of each star and its halo, while the dashed lines show the masses of the stars alone.

Extended Data Fig. 2 Cumulative distribution of the delay from formation of stars to their first identification in a (persistent) multiple system (binary, triple, or quadruple).

Each coloured line corresponds to 1 of 10 logarithmically spaced mass bins, where stars are binned by their final masses. Persistent multiples are those that survive for more than one snapshot and at least one period. Note that many low mass stars are never in multiples, so the maximum cumulative fraction remains below one.

Extended Data Fig. 3 Bound from birth fraction versus mass for surviving and non-surviving binaries.

The fraction is shown with open, blue circles (filled, orange triangles) for surviving (non-surviving) binaries. The mass is the maximum of the two stars’ final masses. The error bars show the standard deviation, from the Bayesian formula \(\sqrt{\frac{(N-k+1)(k+1)}{(N+3){(N+2)}^{2}}}\), where k is the number of bound binaries and N is the total number of binaries in the mass bin. From left to right k is 194, 306, 157, 16, 1 for the survivors and 117, 259, 182, 86, 6 for the non-survivors. From left to right N is 224, 397, 251, 75, 10 for the survivors and 150, 331, 282, 145, 18 for the non-survivors. While high mass stars tend to form in multiple systems, many of these are disrupted by exchanges, leading to a decline in the overall bound-from-birth fraction with mass.

Extended Data Fig. 4 Ratio between maximum gas halo mass and the final stellar mass.

Rescaled probability density (orange) and CDF (blue) of the ratio between the maximum gas halo mass and the final stellar mass for all of the stars in the simulation for ft = 1 (top left), ft = 8 (top right), and ft = 0.082 (bottom). Note the different axis ranges in the bottom panel.

Extended Data Fig. 5 Stellar initial mass function (IMF).

The blue histogram shows the overall IMF, while the green histogram shows the IMF of singles that were in binaries at some point. The latter has a flatter slope above 0.3 M⊙, as indicated by the power-law fits (dashed blue and green lines). The flatter slope is comparable to that of the IMF of all stars in the simulation (gray histogram). The dash-dotted orange histogram shows the IMF of singles that were in higher multiples, but not in binaries (indicating they are outer companions). The solid orange histogram shows the IMF of stars that were never in multiple systems.

Extended Data Table 1 Summary of binary statistics for simulations with different virial parameters and metalicities
Full size table

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2.

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Generozov, A., Offner, S.S.R., Kratter, K.M. et al. The bound origin of low-mass stellar binaries. Nat Astron (2025). https://doi.org/10.1038/s41550-025-02686-5

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