Detecting and Characterizing Companions with a Calibrated Gaia DR2, DR3, and Hipparcos Catalog (G23H)

Gaia DR4 epoch astrometry will enable the detection of thousands of exoplanets through astrometric motion. Here, we present a composite catalog and modeling framework that extracts the maximum information from existing Hipparcos and Gaia data releases. We calibrate Gaia DR2 proper motions and DR3-DR2 scaled position differences against the Gaia DR3 reference frame, and combine these with the Hipparcos-Gaia Catalog of Accelerations, the Hipparcos intermediate astrometric data, Gaia astrometric excess noise, and Gaia radial velocity variability constraints. We implement a joint likelihood model for these data in Octofitter that marginalizes over Gaia’s unpublished observation epochs. This results in full orbit posteriors that can be computed uniformly for a large class of companions. We compare these posteriors to published orbital solutions for 25 stellar binaries from the Sixth Catalog of Orbits of Visual Binary Stars, recovering all companions at high significance and broadly consistent orbital separations. We then recover independent evidence to support 94 of 120 tested Jovian exoplanetary systems from the NASA Exoplanet Archive (plus 3 known stellar companions, and one previously detected planet we now rule out). We demonstrate that in cases like 14 Her b, the posteriors confirm the planetary nature of a signal using only Gaia and Hipparcos data. We find no false positives among 25 RV-quiet standard stars without significant Hipparcos-Gaia accelerations. Our method can break degeneracies inherent to proper motion anomaly or excess noise modeling alone by resolving orbital curvature within the Gaia baseline. The catalog and updated Octofitter are made publicly available to the community.

💡 Research Summary

The paper presents a comprehensive framework for detecting and characterizing stellar and sub‑stellar companions by jointly exploiting existing astrometric data from Hipparcos, Gaia DR2, and Gaia DR3, in preparation for the upcoming Gaia DR4 epoch astrometry. The authors first construct a calibrated catalog that places all proper motions and position differences onto the Gaia DR3 reference frame. This involves a two‑step correction of Gaia DR2 proper motions: a global, magnitude‑dependent rotation fit across 84 magnitude bins, followed by a local correction within HEALPix level‑6 sky tiles using a Gaussian‑mixture model to estimate both systematic offsets and an error‑inflation factor (α). Correlations between DR2 and DR3 measurements are explicitly accounted for via a correlation coefficient (ρ), which reduces the variance of the difference and prevents over‑estimation of acceleration signals.

Next, the paper integrates several complementary observables into a single Bayesian likelihood: (1) the Hipparcos‑Gaia proper‑motion anomaly (PMA) as provided by the Hipparcos‑Gaia Catalog of Accelerations (HGCA); (2) the Hipparcos intermediate astrometric data (IAD), which contain individual scan‑level measurements and thus encode orbital curvature; (3) Gaia DR3 astrometric excess noise (AEN), re‑derived from the published uncertainty inflation in the DR3 linear fit; and (4) Gaia radial‑velocity (RV) variability, quantified from the sample variance of the Gaia DR3 mean RVs. The joint likelihood is

L(θ) = ∏_i P(PMA_i | θ) · ∏_j P(IAD_j | θ) · ∏_k P(AEN_k | θ) · ∏_l P(RV_l | θ),

where θ comprises the full set of orbital elements (semi‑major axis, eccentricity, inclination, longitude of ascending node, argument of periastron, epoch of periastron passage) together with the calibration parameters (global rotation, local offsets, α, ρ). Because Gaia’s observation epochs are not publicly released, the authors marginalize over possible epoch samplings (“epoch marginalization”), effectively integrating out this nuisance while preserving the information contained in the time baseline.

The likelihood is sampled with a No‑U‑Turn Sampler (NUTS) implementation within the open‑source orbit‑fitting package Octofitter, which the authors have extended to ingest the calibrated catalog and the additional constraints. The resulting posterior distributions provide full orbital solutions and companion mass estimates, even when only astrometric data are available.

Validation is performed on two fronts. First, the authors recover the orbits of 25 visual binaries from the Sixth Catalog of Orbits of Visual Binary Stars, achieving high statistical significance and orbital parameters consistent with published solutions. Second, they apply the method to 120 known Jovian exoplanet systems listed in the NASA Exoplanet Archive. Using only Gaia and Hipparcos data, they obtain significant detections for 94 of these planets, correctly identifying planetary‑mass companions and ruling out false positives. Notably, the case of 14 Her b demonstrates that the posterior is sufficiently concentrated to confirm a planetary nature without any radial‑velocity input. A control sample of 25 RV‑quiet stars with no significant Hipparcos‑Gaia accelerations yields zero detections, confirming a low false‑positive rate.

The key contributions of the work are: (1) a rigorously calibrated, unified astrometric catalog that aligns Gaia DR2, DR3, and Hipparcos measurements; (2) a Bayesian framework that simultaneously incorporates proper‑motion anomalies, IAD, astrometric excess noise, and RV variability, thereby breaking degeneracies inherent in any single indicator; (3) an open‑source implementation (Octofitter) that can be applied uniformly to millions of stars brighter than G≈16 mag within 1 kpc. The authors make the catalog of 18 million calibrated sources and the updated Octofitter code publicly available.

Looking ahead, the methodology is poised to exploit Gaia DR4 epoch astrometry once released. Direct inclusion of epoch‑level measurements will further tighten orbital curvature constraints, enable precise dynamical mass determinations, and facilitate large‑scale population studies of exoplanets and brown dwarfs. Moreover, the modular nature of the framework allows seamless integration with complementary data such as direct imaging, high‑precision RV, and relativistic astrometry, opening the path toward a comprehensive census of companions across a wide range of orbital separations.