In a groundbreaking analysis of data collected by NASA’s Dawn spacecraft, scientists have unveiled new insights into the internal structure of the asteroid Vesta, revealing a surprisingly small core beneath its crust. Over the course of a year-long science phase orbiting Vesta, Dawn meticulously gathered radio tracking and high-resolution imaging data, enabling researchers to create the most precise models to date of the asteroid’s gravity field, shape, and rotation. These models have provided unprecedented constraints on Vesta’s internal composition, further illuminating the processes that shaped one of the Solar System’s most intriguing protoplanetary bodies.
During Dawn’s mission at Vesta, the spacecraft was equipped with sophisticated instruments including X-band radio communication systems used for two-way Deep Space Network (DSN) tracking, and dual framing cameras designed to capture the asteroid’s surface with exceptional clarity. The DSN tracking data, encompassing both range and Doppler measurements, allowed scientists to determine Dawn’s relative velocity and distance from Earth to sub-meter accuracy. Meanwhile, the framing cameras delivered vital surface-relative positional information necessary for orbit reconstruction and for refining the long-wavelength gravitational signals. This dual data acquisition approach formed the backbone of the orbit determination technique crucial for extracting details about Vesta’s gravity field and rotational properties.
Dawn’s extensive observational campaign at Vesta was divided into several phases, including approach, survey, high- and low-altitude mapping orbits (HAMO and LAMO, respectively), and a second HAMO phase. Throughout these intervals, the spacecraft transitioned between altitudes spanning from approximately 25,000 kilometers down to as low as 169 kilometers above Vesta’s surface. With the vast majority of data acquired during the Survey, HAMO, LAMO, and HAMO-2 phases, the mission achieved global coverage, enabling a comprehensive recovery of both Vesta’s shape and gravity field. Notably, maneuvers associated with orbital transfers introduced non-gravitational forces which were excluded from the gravity analysis to maintain data integrity.
Central to understanding Vesta’s physical characteristics is the determination of its shape, accomplished through an advanced technique known as stereophotoclinometry (SPC). SPC combines multiple camera images taken from varying angles to construct detailed three-dimensional topographic models of the surface. Dawn’s primary framing camera, FC2, captured a staggering 16,500 images with resolution scales ranging from hundreds of meters down to 20 meters per pixel during the critical mapping orbits. These images were meticulously processed to produce a global shape model with an effective spatial resolution of about 50 meters, supported by approximately 75,000 overlapping tiled maps. Such precision allowed for unprecedented geophysical analysis, including the calculation of the position of Vesta’s center of figure relative to its center of mass.
The resulting SPC-derived shape models offer significant insight into Vesta’s overall form, revealing an ellipsoid characterized by axes measuring roughly 285, 277, and 226 kilometers. This geometric approximation highlights Vesta’s departure from a perfect sphere, a shape influenced by its rotational and internal structural dynamics. The meticulously archived data sets, including shape models and associated spacecraft and rotational parameters, are now publicly available in NASA’s Planetary Data System, providing the scientific community with critical tools for ongoing and future research.
Gravity field modeling, essential for probing beneath Vesta’s rugged exterior, was performed using spherical harmonic expansions. This mathematical framework represents the gravitational potential as an infinite series of terms characterized by degrees and orders, each corresponding to particular spatial scales and patterns in the gravity field. In this model, the contribution of each spherical harmonic coefficient encapsulates complexities in Vesta’s mass distribution. The analysis leveraged degrees up to twenty-six to ensure fine spatial resolution—down to roughly 32 kilometers—thus capturing subtle gravitational variations attributable to internal density differences.
The orientations and time-dependent changes in Vesta’s spin axis and rotational behavior were modeled using a framework encompassing right ascension, declination, and rotation angles. These parameters, integrated through time with accounting for precession and nutation effects, were constrained via iterative fitting of Dawn’s combined radio and optical data. Importantly, the rotation model is anchored to a body-fixed frame defined by a landmark crater named Claudia, which establishes a standardized meridian system unique to Vesta. Through this detailed approach, scientists achieved remarkable congruence between predicted and observed rotational dynamics.
A significant challenge faced during prior analyses was the calibration discrepancy between Doppler radio tracking and optical imaging datasets, resulting in conflicts in orbit determination outcomes. However, advances realized through subsequent missions, notably at Ceres, led to refined calibration methods harmonizing both data types. Reprocessing the Vesta data with these enhanced techniques eliminated the systematic errors, enabling a high-fidelity global gravity solution consistent with independent shape models. This synergy exemplifies the necessity of joint data calibration in planetary geophysics and underpins the robust conclusion of the current study.
From the refined gravity and shape models, the team derived essential physical parameters of Vesta, including its gravitational parameter (GM), mass, volume, and bulk density. Utilizing the latest universal gravitational constant values, the measured GM translates to a mass of approximately 2.59 × 10²⁰ kilograms. Combined with the accurately determined volume from the shape model, this implies a bulk density near 3.46 grams per cubic centimeter, reflecting a composition denser than typical stony asteroids and suggesting differentiation with metallic core components.
To interpret these physical constraints within a geophysical context, researchers developed a three-layer internal structure model of Vesta, incorporating uniform-density layers representing the crust, mantle, and core. Computing gravity coefficients for such layered ellipsoidal models requires careful integration of geometric and density contributions, further complicated by assumptions about hydrostatic equilibrium and the non-spherical shapes of internal boundaries. By solving associated algebraic equations governing ellipsoidal parameters, this model adeptly reproduces Vesta’s observed mass, shape, and gravitational harmonics, providing a vital link between observed gravitational fields and subsurface density distributions.
To statistically invert the model parameters and characterize uncertainties, the team employed an affine-invariant Markov Chain Monte Carlo (MCMC) method. This advanced ensemble sampling approach efficiently explores complex parameter spaces and identifies parameter sets that maximize match between model predictions and observed data. The likelihood function was crafted to evaluate differences in principal moments of inertia, flattening factors, and the so-called effective density spectrum—a representation of density variations at different internal scales derived from spherical harmonic gravity and shape coefficients—allowing an integrated assessment of Vesta’s internal composition.
Delving deeper into the concept of the effective density spectrum, the analysis leverages the mathematical expansion of both gravitational potential and shape using spherical harmonics. Variance spectra derived from these expansions quantify how mass distribution anomalies correlate with topographic features at varying spatial scales. The effective density is essentially a measure of how density varies with depth beneath the surface, inferred indirectly by comparing observed gravity to what would be expected from a homogeneous interior with the same shape. The spectrum shows a general trend of decreasing effective density with increasing spherical harmonic degree, reflecting typical planetary interiors where density tends to increase with depth.
Analytically, the team derived integral expressions connecting the effective density coefficients to radial density gradients within a layered model, providing a rigorous framework for interpreting the observed data. This approach accounts for density jumps at internal boundaries, such as at the core-mantle interface, and incorporates shape factors reflecting ellipsoidal deviations. One remarkable outcome is the ability to connect high-degree spherical harmonic effective densities directly to surface densities, offering a pathway to constrain crustal properties independently of deeper internal complexities.
Recognizing the inherent uncertainties in measured gravity data and modeling assumptions, the researchers carefully evaluated errors in the effective density spectrum. This involved generating ensembles of plausible gravity coefficient realizations (gravity clones) and quantifying resultant variations in the density spectrum. Moreover, residual analysis of best-fit models was used to quantify noise arising from internal heterogeneities and observational limitations. Combining these components yielded comprehensive error estimates, essential for robust inference of Vesta’s internal layering.
Synthesizing all lines of evidence, the research concluded that Vesta possesses a notably small core relative to its overall size, marking a departure from some prior models. This finding carries significant implications for understanding the asteroid’s thermal evolution, differentiation history, and collisional past. The constrained parameters of core size and density suggest a complex formation and alteration pathway, potentially involving early melting, metal segregation, and prolonged cooling, all of which shape the present-day internal structure observable via subtle gravitational perturbations.
Beyond advancing knowledge about Vesta itself, the methodologies developed and refined in this study set a new standard for planetary body characterization using combined spacecraft tracking and imaging data. The approach showcases how multifaceted datasets, integrated through state-of-the-art computational and statistical models, can break new ground in probing otherwise inaccessible internal worlds. This paves the way for future missions targeting other small bodies, where understanding internal composition is key to unraveling Solar System formation processes and the origins of planetary diversity.
This study elegantly demonstrates the power of precision spacecraft navigation data combined with high-resolution imaging to illuminate the interior of a distant asteroid. The success in resolving calibration discrepancies and achieving meter-scale orbital accuracy underscores the sophistication of modern planetary science missions. Furthermore, the public archival of richly detailed shape and gravity models ensures that the scientific community can build upon these results, stimulating further research and discovery about protoplanetary bodies and asteroid evolution pathways.
In summary, the Dawn mission’s comprehensive exploration of Vesta has culminated in a refined portrait of this protoplanet’s internal make-up, revealing a surprisingly diminutive core and providing tighter bounds on its rotational and gravitational characteristics. These insights enrich our broader understanding of planetary differentiation processes, offer clues about early Solar System history, and exemplify the synergy of spacecraft instrumentation, advanced modeling, and rigorous data analysis in planetary science.
Subject of Research: Vesta asteroid internal structure and geophysical properties.
Article Title: A small core in Vesta inferred from Dawn’s observations.
Article References:
Park, R.S., Ermakov, A.I., Konopliv, A.S. et al. A small core in Vesta inferred from Dawn’s observations. Nat Astron (2025). https://doi.org/10.1038/s41550-025-02533-7
Image Credits: AI Generated
