The Ragozzine research group studies exoplanets and Kuiper Belt Objects using theoretical orbital dynamics, advanced statistical techniques, computational data analysis, and the best astronomical data. 

Selected Publications

Benjamin C. N. Proudfoot and Darin Ragozzine
The dwarf planet (136108) Haumea has an intriguing combination of unique physical properties: near-breakup spin, two regular satellites, and an unexpectedly compact family. While these properties point toward formation by a collision, there is no self-consistent and reasonably probable formation hypothesis that can connect the unusually rapid spin and low relative velocities of Haumea family members ("Haumeans"). We explore and test the proposed formation hypotheses (catastrophic collision, graze-and-merge, and satellite collision) in detail. We flexibly parameterize the properties of the collision (e.g., the collision location) and use simple models for the unique three-dimensional velocity ejection field expected from each model to generate simulated families. These are then compared to the observed Kuiper Belt objects using Bayesian parameter inference, including a mixture model that robustly allows for interlopers from the background population. After testing our methodology, we find that the best match to the observed Haumeans is an essentially isotropic ejection field with a typical velocity of 150 m s−1. The graze-and-merge formation hypothesis—in which Haumeans are shed due to excess angular momentum—is clearly disfavored because the observed Haumeans are not oriented in a plane. The satellite collision model is also disfavored. Including these new constraints, we present a detailed discussion of the formation hypotheses, including variations, some of which are tested. Some new hypotheses are proposed (a cratering collision and a collision where Haumea's upper layers are "missing") and scrutinized. We do not identify a satisfactory formation hypothesis, but we do propose several avenues of additional investigation. In the process of these analyses, we identify many new candidate Haumeans and dynamically confirm seven of them as consistent with the observed family. We also confirm that Haumeans have a shallow size distribution and discuss implications for the discovery and identification of new Haumeans.
We visually analyzed the transit timing variation (TTV) data of 5930 Kepler Objects of Interest (KOIs) homogeneously. Using data from Rowe et al. and Holczer et al., we investigated TTVs for nearly all KOIs in Kepler’s Data Release 24 catalog. Using TTV plots, periodograms, and phase-folded quadratic plus sinusoid fits, we visually rated each KOI’s TTV data in five categories. Our ratings emphasize the hundreds of planets with TTVs that are weaker than the ∼200 that have been studied in detail. Our findings are consistent with statistical methods for identifying strong TTVs, though we found some additional systems worth investigation. Between about 3–50 days and 1.3–6 Earth radii, the frequency of strong TTVs increases with period and radius. As expected, strong TTVs are very common when period ratios are near a resonance, but there is not a one-to-one correspondence. The observed planet-by-planet frequency of strong TTVs is only somewhat lower in systems with one or two known planets (7% ± 1%) than in systems with three or more known planets (11% ± 2%). We attribute TTVs to known planets in multitransiting systems but find ∼30 cases where the perturbing planet is unknown. Our conclusions are valuable as an ensemble for learning about planetary system architectures and individually as stepping stones toward more-detailed mass–radius constraints. We also discuss Data Release 25 TTVs, investigate ∼100 KOIs with transit duration and/or depth variations, and estimate that the Transiting Exoplanet Survey Satellite will likely find only ∼10 planets with strong TTVs.
Kepler-9, discovered by Holman et al. (2010), was the first system with multiple confirmed transiting planets and the first system to clearly show long-anticipated transit timing variations (TTVs). It was the first major novel exoplanet discovery of the Kepler Space Telescope mission. The Kepler pipeline identified two Saturn-radius candidates (called Kepler Objects of Interest or KOIs): KOI-377.01 with a 19-day period and KOI-377.02 with a 39-day period. Even with only 9 transits for KOI-377.01 and 6 of KOI-377.02, the transit times were completely inconsistent with a linear ephemeris and showed strongly anti-correlated variations in transit times. Holman et al. (2010) were able to readily show that these objects were planetary mass, confirming them as bona fide planets Kepler-9b and Kepler-9c. As a multi-transiting system exhibiting strong TTVs, the relative planetary properties (e.g., mass ratio, radius ratio) were strongly constrained, opening a new chapter in comparative planetology. KOI-377.03, a small planet with a 1.5-day period, was not initially discovered by the Kepler pipeline, but was identified during the analysis of the other planets and was later confirmed as Kepler-9d through the BLENDER technique by Torres et al. 2011. Holman et al. (2010) included significant dynamical analysis to characterize Kepler-9’s particular TTVs: planets near resonance show large amplitude anti-correlated TTVs with a period corresponding to the rotation of the line of conjunctions and an additional “chopping” signal due to the changing positions of the planets. We review the historical circumstances behind the discovery and characterization of these planets and the publication of Holman et al. (2010). We also review the updated properties of this system and propose ideas for future investigations.
Radial velocity (RV) surveys have detected hundreds of exoplanets through their gravitational interactions with their host stars. Some will be transiting, but most lack sufficient follow-up observations to confidently detect (or rule out) transits. We use published stellar, orbital, and planetary parameters to estimate the transit probabilities for nearly all exoplanets that have been discovered via the RV method. From these probabilities, we predict that  of the known RV exoplanets should transit their host stars. This prediction is more than double the amount of RV exoplanets that are currently known to transit. The Transiting Exoplanet Survey Satellite (TESS) presents a valuable opportunity to explore the transiting nature of many of the known RV exoplanet systems. Based on the anticipated pointing of TESS during its two-year primary mission, we identify the known RV exoplanets that it will observe and predict that  of them will have transits detected by TESS. However, we only expect the discovery of transits for ∼3 of these exoplanets to be novel (i.e., not previously known). We predict that the TESS photometry will yield dispositive null results for the transits of ∼125 RV exoplanets. This will represent a substantial increase in the effort to refine ephemerides of known RV exoplanets. We demonstrate that these results are robust to changes in the ecliptic longitudes of future TESS observing sectors. Finally, we consider how several potential TESS extended mission scenarios affect the number of transiting RV exoplanets we expect TESS to observe.
D. Ragozzine (et al.)
We present high spatial resolution images of the binary transneptunian object Gǃkúnǁ'hòmdímà (229762 2007 UK126) obtained with the Hubble Space Telescope and with the Keck observatory on Mauna Kea to determine the orbit of Gǃò'é ǃhúGǃò'é ǃhú, the much smaller and redder satellite. Gǃò'é ǃhú orbits in a prograde sense, on a circular or near-circular orbit with a period of 11.3 days and a semimajor axis of 6000 km. Tidal evolution is expected to be slow, so it is likely that the system formed already in a low-eccentricity configuration, and possibly also with the orbit plane of the satellite in or close to the plane of Gǃkúnǁ'hòmdímà's equator. From the orbital parameters we can compute the system mass to be 1.4 × 1020 kg. Combined with estimates of the size of Gǃkúnǁ'hòmdímà from thermal observations and stellar occultations, we can estimate the bulk density as about 1 g cm−3. This low density is indicative of an ice-rich composition, unless there is substantial internal porosity. We consider the hypothesis that the composition is not unusually ice-rich compared with larger TNOs and comet nuclei, and instead the porosity is high, suggesting that mid-sized objects in the 400 to 1000 km diameter range mark the transition between small, porous objects and larger objects that have collapsed their internal void space as a result of their much higher internal pressures and temperatures.

We present a new framework to characterize the occurrence rates of planet candidates identified by Kepler based on hierarchical Bayesian modeling, approximate Bayesian computing (ABC), and sequential importance sampling. For this study, we adopt a simple 2D grid in planet radius and orbital period as our model and apply our algorithm to estimate occurrence rates for Q1–Q16 planet candidates orbiting solar-type stars. We arrive at significantly increased planet occurrence rates for small planet candidates (Rp < 1.25 R) at larger orbital periods (P > 80 day) compared to the rates estimated by the more common inverse detection efficiency method (IDEM). Our improved methodology estimates that the occurrence rate density of small planet candidates in the habitable zone of solar-type stars is 1.6 per factor of 2 in planet radius and orbital period. Additionally, we observe a local minimum in the occurrence rate for strong planet candidates marginalized over orbital period between 1.5 and 2 R that is consistent with previous studies. For future improvements, the forward modeling approach of ABC is ideally suited to incorporating multiple populations, such as planets, astrophysical false positives, and pipeline false alarms, to provide accurate planet occurrence rates and uncertainties. Furthermore, ABC provides a practical statistical framework for answering complex questions (e.g., frequency of different planetary architectures) and providing sound uncertainties, even in the face of complex selection effects, observational biases, and follow-up strategies. In summary, ABC offers a powerful tool for accurately characterizing a wide variety of astrophysical populations.