Number Of Asteroids Research Articles

On the Dynamical Evolution of the Asteroid Belt in a Massive Star–Neutron Star Binary

Some fast radio bursts (FRBs) exhibit repetitive behaviors, and their origins remain enigmatic. It has been argued that repeating FRBs could be produced by the interaction between a neutron star and an asteroid belt. Here, we consider the systems in which an asteroid belt dwells around a massive star, while a neutron star, as a companion of the massive star, interacts with the belt through gravitational force. Various orbital configurations are assumed for the system. Direct N-body simulations are performed to investigate the dynamical evolution of the asteroids' belt. It is found that a larger orbital eccentricity of the neutron star will destroy the belt more quickly, with a large number of asteroids being scattered out of the system. A low inclination not only suppresses the collisions but also inhibits the ejection rate at early stages. However, highly inclined systems may undergo strong oscillations, resulting in the Kozai–Lidov instabilities. Among the various configurations, a clear periodicity is observed in the collision events for the case with an orbital eccentricity of 0.7 and mutual inclination of 0◦. It is found that such a periodicity can be sustained for at least eight neutron star orbital periods, supporting this mechanism as a possible explanation for periodically repeating FRBs. Our studies also suggest that the active stage of these kinds of FRB sources should be limited, since the asteroid belt would finally be destroyed by the neutron star after multiple passages.

Rotation periods of asteroids from light curves of TESS data

Understanding the dynamical evolution of asteroids through the secular Yarkovsky effect requires the determination of many physical properties, including the rotation period. We propose a method aimed at obtaining a robust determination of the rotation period of asteroids, while avoiding the pitfalls of aliases. We applied this approach to thousands of asteroid light curves measured by the NASA mission. We developed a robust period-analysis algorithm based on a Fourier series. Our approach includes a comparison of the results from multiple orders and tests on the number of extremes to identify and reject potential aliases. We also provide the uncertainty interval for the result as well as additional periods that may be plausible. We report the rotation period for nbTenPercent asteroids within a precision of 10<!PCT!>. A comparison with the literature (whenever available) reveals a very good agreement and validates the approach presented here. Our approach also highlights cases for which the determination of the period should be considered invalid. The dataset presented here confirms the apparent small number of asteroids with a rotation between 50 and 100 h and correlated with diameter. The amplitude of the light curves is found to increase toward smaller diameters, as asteroids become less and less spherical. Finally, there is a systematic difference between the broad C and S complex in the amplitude-period, revealing the statistically lower density of C-types compared to S-type asteroids. Our approach to the determination of asteroid rotation period is based on simple concepts, yet it is nonetheless robust. It can be applied to large corpora of time series photometry, such as those extracted from exoplanet transit surveys.

Deep learning-assisted near-Earth asteroid tracking in astronomical images

The large number of near-Earth asteroids (NEAs) has greatly impacted human space activities and Earth security. However, detecting NEAs in astronomical images with complex, varying backgrounds is still extremely challenging. In this paper, we propose a deep segmentation assisted asteroid tracking algorithm, termed DSAT, to construct a possible pipeline for faint NEA tracking in astronomical images. First, the single-frame object detection problem is converted to a segmentation problem, enabling robust extraction of faint potential moving objects. Then, a multiframe motion prior-based moving object tracking algorithm is proposed to find real NEAs. We further propose a distance tolerance criterion to help DSAT achieve effective tracking in practical situations when detection has partially failed. Finally, the pipeline is tested with both simulated and real astronomical images at different SNRs and in crowded fields. The results showed that our pipeline has the potential to detect and track faint NEAs in complex backgrounds. Our code is publicly available at https://github.com/zhenhongdu/DeepSegAsteroidTracker.

Secular change in the spin states of asteroids due to radiation and gravitation torques

Context. The rotation state of small asteroids is affected in the long term by perturbing torques of gravitational and radiative origin (the YORP effect). The former can be detected by a change in the spin-axis orientation in the inertial space; the latter manifests itself by a quadratic increase in the rotation phase. Aims. Direct observational evidence of the YORP effect is the primary goal of our work. This includes both the YORP detection for new objects and an improvement in the accuracy of previously known detections. Methods. We carried out photometric observations of five near-Earth asteroids: (1862) Apollo, (2100) Ra-Shalom, (85989) 1999 JD6, (138852) 2000 WN10, and (161989) Cacus. Then we applied the light-curve inversion method to all available data to determine the spin state and a convex shape model for each of the five studied asteroids. The YORP effect was modeled as a linear change of the rotation frequency υ ≡ dω/dt. In the case of (2100) Ra-Shalom, the analysis required that the spin-axis precession due to the solar gravitational torque also be included. Results. We obtained two new detections of the YORP effect: (i) υ = (2.9 ± 2.0) × 10−9 rad d−2 for (2100) Ra-Shalom, and (ii) υ = (5.5 ± 0.7) × 10−8 rad d−2 for (138852) 2000 WN10. The analysis of Ra-Shalom also reveals a precession of the spin axis with a precession constant α ~ 3000″ yr−1. This is the first such detection from Earth-bound photometric data. For the other two asteroids, we improved the accuracy of the previously reported YORP detection: (i) υ = (4.94 ± 0.09) × 10−8 rad d−2 for (1862) Apollo, and (ii) υ = (1.86 ± 0.09) × 10−8 rad d−2 for (161989) Cacus. With this value, Apollo has the most precisely determined YORP effect so far. Despite the recent report of a detected YORP effect for (85989) 1999 JD6, we show that the model without YORP cannot be rejected statistically. Therefore, the detection of the YORP effect for this asteroid requires future observations. In several of our targets, the currently available observations do not provide enough constraints on the shape model (even at large scales) to compute the theoretical YORP effect with sufficient precision. Nevertheless, the interpretation of the detected signal as the YORP effect is fairly plausible. The spin-axis precession constant of Ra-Shalom determined from observations matches the theoretically expected value. Conclusions. The total number of asteroids with a YORP detection has increased to 12. In all cases, the rotation frequency increases in time. The analysis of a rich photometric data set of irregularly shaped asteroids may require inclusion of spin-axis precession in future studies.

Euclid: Identification of asteroid streaks in simulated images using deep learning

The material composition of asteroids is an essential piece of knowledge in the quest to understand the formation and evolution of the Solar System. Visual to near-infrared spectra or multiband photometry is required to constrain the material composition of asteroids, but we currently have such data, especially in the near-infrared wavelengths, for only a limited number of asteroids. This is a significant limitation considering the complex orbital structures of the asteroid populations. Up to 150 000 asteroids will be visible in the images of the upcoming ESA Euclid space telescope, and the instruments of Euclid will offer multiband visual to near-infrared photometry and slitless near-infrared spectra of these objects. Most of the asteroids will appear as streaks in the images. Due to the large number of images and asteroids, automated detection methods are needed. A non-machine-learning approach based on the Streak Det software was previously tested, but the results were not optimal for short and/or faint streaks. We set out to improve the capability to detect asteroid streaks in Euclid images by using deep learning. We built, trained, and tested a three-step machine-learning pipeline with simulated Euclid images. First, a convolutional neural network (CNN) detected streaks and their coordinates in full images, aiming to maximize the completeness (recall) of detections. Then, a recurrent neural network (RNN) merged snippets of long streaks detected in several parts by the CNN. Lastly, gradient-boosted trees (XGBoost) linked detected streaks between different Euclid exposures to reduce the number of false positives and improve the purity (precision) of the sample. The deep-learning pipeline surpasses the completeness and reaches a similar level of purity of a non-machine-learning pipeline based on the StreakDet software. Additionally, the deep-learning pipeline can detect asteroids 0.25–0.5 magnitudes fainter than StreakDet. The deep-learning pipeline could result in a 50% increase in the number of detected asteroids compared to the StreakDet software. There is still scope for further refinement, particularly in improving the accuracy of streak coordinates and enhancing the completeness of the final stage of the pipeline, which involves linking detections across multiple exposures.

A hybrid approach for solving the gravitational N-body problem with Artificial Neural Networks

Simulating the evolution of the gravitational N-body problem becomes extremely computationally expensive as N increases since the problem complexity scales quadratically with the number of bodies. In order to alleviate this problem, we study the use of Artificial Neural Networks (ANNs) to replace expensive parts of the integration of planetary systems. Neural networks that include physical knowledge have rapidly grown in popularity in the last few years, although few attempts have been made to use them to speed up the simulation of the motion of celestial bodies. For this purpose, we study the advantages and limitations of using Hamiltonian Neural Networks to replace computationally expensive parts of the numerical simulation of planetary systems, focusing on realistic configurations found in astrophysics. We compare the results of the numerical integration of a planetary system with asteroids with those obtained by a Hamiltonian Neural Network and a conventional Deep Neural Network, with special attention to understanding the challenges of this specific problem. Due to the non-linear nature of the gravitational equations of motion, errors in the integration propagate, which may lead to divergence from the reference solution. To increase the robustness of a method that uses neural networks, we propose a hybrid integrator that evaluates the prediction of the network and replaces it with the numerical solution if considered inaccurate.Hamiltonian Neural Networks can make predictions that resemble the behavior of symplectic integrators but are challenging to train and in our case fail when the inputs differ ∼7 orders of magnitude. In contrast, Deep Neural Networks are easy to train but fail to conserve energy, leading to fast divergence from the reference solution. The hybrid integrator designed to include the neural networks increases the reliability of the method and prevents large energy errors without increasing the computing cost significantly. For the problem at hand, the use of neural networks results in faster simulations when the number of asteroids is ≳70.

Influence of Planetary Encounters on the Magnitude of the Yarkovsky Effect in Asteroid Dynamics

The influence of the solar radiation pressure and the Yarkovsky effect on the long-term orbital dynamics is estimated for a number of asteroids experiencing successive planetary encounters. The variation in the asteroid’s proper rotation period due to its approach to the planet and its effect on the asteroid’s further orbital dynamics through the Yarkovsky effect is considered. It is shown that close planetary encounters of small asteroids (tens of meters in diameter) with short rotation period (less than 10 h), which change the asteroid’s rotation period by several hours, significantly affect the magnitude of the Yarkovsky effect.

Assessment of Asteroid Classification Using Deep Convolutional Neural Networks

Near-Earth Asteroids represent potential threats to human life because their trajectories may bring them in the proximity of the Earth. Monitoring these objects could help predict future impact events, but such efforts are hindered by the large numbers of objects that pass in the Earth’s vicinity. Additionally, there is also the problem of distinguishing asteroids from other objects in the night sky, which implies sifting through large sets of telescope image data. Within this context, we believe that employing machine learning techniques could greatly improve the detection process by sorting out the most likely asteroid candidates to be reviewed by human experts. At the moment, the use of machine learning techniques is still limited in the field of astronomy and the main goal of the present paper is to study the effectiveness of deep convolutional neural networks for the classification of astronomical objects, asteroids in this particular case, by comparing some of the well-known deep convolutional neural networks, including InceptionV3, Xception, InceptionResNetV2 and ResNet152V2. We applied transfer learning and fine-tuning on these pre-existing deep convolutional networks, and from the results that we obtained, the potential of using deep convolutional neural networks in the process of asteroid classification can be seen. The InceptionV3 model has the best results in the asteroid class, meaning that by using it, we lose the least number of valid asteroids.

Constraints on the Gamma-Ray Emission from Small Solar System Bodies with the Fermi Large Area Telescope Data

All known small solar system bodies have diameters between a few meters and a few thousands of kilometers. Based on the collisional evolution of solar system bodies, a larger number of asteroids with diameters down to ∼2 m is thought to exist. As all solar system bodies, small bodies can be passive sources of high-energy gamma-rays, produced by the interaction of energetic cosmic rays impinging on their surfaces. Since the majority of known asteroids are in orbits between Mars and Jupiter (in a region known as the Main Belt), we expect them to produce a diffuse emission close to the ecliptic plane. In this work, we have studied the gamma-ray emission coming from the ecliptic using the data collected by the Large Area Telescope (LAT) onboard the Fermi satellite. We have fit the results with simulations of the gamma-ray intensity at the source level (calculated with the software FLUKA) to constrain the small solar system bodies population. Finally, we have proposed a model describing the distribution of asteroid sizes and we have used the LAT data to constrain the gamma-ray emission expected from this model and, in turn, on the model itself.

Evaluation of the asteroid material composition by reflectance spectra using meteorite analogues

The MATLAB program was developed to estimate composition of the asteroid material. The program models reflectance spectra of asteroids using reflectance spectra of meteorite analogues. Modeling results and estimation of the material composition for 10 asteroids (1 Ceres, 4 Vesta, 51 Nemausa, 65 Cybele, 102 Miriam, 250 Bettina, 266 Aline, 379 Huenna, 704 Interamnia, 1474 Beira) are discussed. A good agreement between the model spectra and the asteroids reflectance spectra is achieved for a number of asteroids (1 Ceres, 4 Vesta, 51 Nemausa, 250 Bettina, 704 Interamnia)

Imbalanced classification applied to asteroid resonant dynamics

Introduction: Machine learning (ML) applications for studying asteroid resonant dynamics are a relatively new field of study. Results from several different approaches are currently available for asteroids interacting with the z2, z1, M1:2, and ν6 resonances. However, one challenge when using ML to the databases produced by these studies is that there is often a severe imbalance ratio between the number of asteroids in librating orbits and the rest of the asteroidal population. This imbalance ratio can be as high as 1:270, which can impact the performance of classical ML algorithms, that were not designed for such severe imbalances.Methods: Various techniques have been recently developed to address this problem, including cost-sensitive strategies, methods that oversample the minority class, undersample the majority one, or combinations of both. Here, we investigate the most effective approaches for improving the performance of ML algorithms for known resonant asteroidal databases.Results: Cost-sensitive methods either improved or had not affect the outcome of ML methods and should always be used, when possible. The methods that showed the best performance for the studied databases were SMOTE oversampling plus Tomek undersampling, SMOTE oversampling, and Random oversampling and undersampling.Discussion: Testing these methods first could save significant time and efforts for future studies with imbalanced asteroidal databases.

Dynamical evolution of basaltic asteroids outside the Vesta family in the inner main belt

Context. Basaltic V-type asteroids are leftovers from the formation and evolution of differentiated planetesimals. They are thought to originate from mantles and crusts of multiple different parent bodies. Identifying the links between individual V-type asteroids and multiple planetesimals is challenging, especially in the inner part of the main asteroid belt, where the majority of V-type asteroids are expected to have originated from a single planetesimal, namely, (4) Vesta. Aims. In this work, we aim to trace the origin of a number of individual V-type asteroids from the inner part of the main asteroid belt. The main goal is to identify asteroids that may not be traced back to (4) Vesta and may therefore originate from other differentiated planetesimals. Methods. We performed a 2 Gyr backward numerical integration of the orbits of the selected V-type asteroids. For each asteroid, we used 1001 clones to map the effect of orbital uncertainties. In the integration, we use information on physical properties of the considered V-type asteroids such as pole orientation, rotational period, and thermal parameters. Results. The majority of the studied objects can be traced back to the Vesta family within 2 Gyr of integration. The number of objects of the low-inclination V-types did not reach the boundary of the Vesta family during the integration time. Two asteroids, namely, (3307) Athabasca and (17028) 1999 FJ5, do not show a dynamic link to (4) Vesta. Increasing the integration time for these objects leads to further separation from (4) Vesta. Conclusions. The majority of V-types in the inner main belt outside the Vesta family are clearly Vesta fugitives. Two objects, namely, (3307) Athabasca and (17028) 1999 FJ5, show no clear dynamical link to (4) Vesta. Together with (809) Lundia (from our previous work), these objects could represent the parent bodies of anomalous HED meteorites such as the Banbura Rockhole. Furthermore, some objects of the low-inclination population cannot be traced back to (4) Vesta within the 2 Gyr integration.

Comparison of Machine Learning Strategies in Hazardous Asteroids Prediction

The purpose of this study is to use multiple classification algorithm from machine learning to predict hazardous asteroids that orbit Earth. Seven models are Logistic Regression, K-Nearest Neighbor Classifier, Random Forest Classifier, Decision Tree Classifier, Multinomial Naïve Bayes Classifier, Gradient Boosting Classifier, and Voting Classifier. Confusion matrix is used to evaluate those models. Evaluation metrics include accuracy, precision, recall, and f1-score. The result shows that random forest classifier has the greatest overall performance with highest accuracy. Decision Tree classifier, Gradient Boosting classifier, and Voting classifier also perform well. Gradient Boosting classifier is capable of greatly reducing the risk of hazardous asteroid, which is, reduce the number of hazardous asteroids that is predicted as non-hazardous. Because of assumptions of some models like Logistic Regression, data used in the experiment do not follow them, so the overall performance of those models are not well. It would be better to select data for fitting the model. The result shows that combined classifiers perform better. Voting Classifier can be used to assemble those accurate models and get a more accurate result by offsetting disadvantages of each model.

Lifted particles from the fast spinning primary of the Near-Earth Asteroid (65803) Didymos

An increasing number of Near Earth Asteroids (NEAs) in the range of a few hundred metres to a few kilometres in size have relatively high spin rates, from less than 4 h, down to ∼2.2 h, depending on spectral type. For some of these bodies, local acceleration near the equator may be directed outwards so that lift off of near-equatorial material is possible. In particular, this may be the case for asteroid Didymos, the primary of the (65803) Didymos binary system, which is the target of the DART (NASA) and Hera (ESA) space missions. The study of the dynamics of particles in such an environment has been carried out – in the frame of the Hera mission and the EC-H2020 NEO-MAPP project – according to the available shape model, known physical parameters and orbital information available before the DART impact. The presence of orbiting particles in the system is likely for most of the estimated range of values for mass and volume. The spatial mass density of ejected material is calculated for different particle sizes and at different heliocentric orbit epochs, revealing that large particles dominate the mass density distribution and that small particle abundance depends on observation epoch. Estimates of take off and landing areas on Didymos are also reported. Available estimates of the system mass and primary extents, after the DART mission, confirm that the main conclusions of this study are valid in the context of current knowledge.

A new graph parameter to measure linearity

AbstractConsider a sequence of Lexicographic Breadth‐First‐Search vertex orderings where each ordering is used to break ties for . Since the total number of vertex orderings of a finite graph is finite, this sequence must end in a cycle of vertex orderings. The possible length of this cycle is the main subject of this work. Intuitively, we prove for graphs with a known notion of linearity (e.g., interval graphs with their interval representation on the real line), this cycle cannot be too big, no matter which vertex ordering we start with. More precisely, it was conjectured by Dusart and Habib that for cocomparability graphs, the size of this cycle is always 2, independent of the starting order. Furthermore Stacho asked whether for arbitrary graphs, the size of such a cycle is always bounded by the asteroidal number of the graph. In this work, while we answer this latter question negatively, we provide support for the conjecture on cocomparability graphs by proving it for the subclass of domino‐free cocomparability graphs. This subclass contains cographs, proper interval, interval and cobipartite graphs. We also provide simpler independent proofs for each of these cases which lead to stronger results on this subclasses.

Spectrophotometry and Other Remote-Sensing Methods to Study Asteroids: Achievements and New Approaches

Physical parameters and characteristics of asteroids as solid atmosphereless celestial bodies are traditionally studied with the same methods as those used for investigating most of the other celestial objects, though they have certain specific features. The main attention is paid to spectrophotometry, as the most effective tool to study remotely the composition, evolution, and origin of asteroids. However, very important information about asteroids was also obtained by other observational methods, such as photometry, polarimetry, radiometry, and radar. Because of this, in addition to spectrophotometry, we discuss here photometry, polarimetry, and radiometry, which, on the one hand, are very close in methodology and, on the other hand, there has been a trend to their integrated use. In connection with the discovery of sublimation–dust activity on a number of asteroids and the periodic formation of a dust exosphere around these asteroids near perihe lion (see, e.g., Busarev et al., 2021), we also consider a methodologically new approach to estimating the chemical and mineralogical composition of particles in the exosphere of these asteroids and, indirectly, of their surface material.

Fast asteroidal period inversion by parallel acceleration-based three-step reduced voting

Asteroids, especially near-Earth asteroids, have become a popular focus of research in the field of deep space exploration because they retain historical relics of the early formation and evolution of the Solar System. Rotational periods play an important role in elucidating the characteristics of asteroids, such as the rubble-pile internal structure and the spin barrier. Generally, commonly used periodogram methods, such as Fourier-type methods, can produce only a rough estimate of the rotational period, and it is difficult to obtain other essential parameters, such as the pole, shape, and scattering parameters. To alleviate this problem, this article presents a three-step reduced voting (TRV) algorithm based on the Cellinoid model to accurately and efficiently invert asteroidal periods from lightcurves. The proposed TRV algorithm can realize this inversion process to derive the high-precision period, as well as a roughly estimated pole orientation and overall shape of an asteroid. Numerical experiments confirm that the TRV algorithm can obtain accurate periods and near-accurate poles from synthetic lightcurves. Besides, this algorithm is applied to invert the rotational periods of the 61 real asteroids, and the derived periods are consistent with those reported in other publications. It is also demonstrated that more observations collected in various viewing geometries can improve the accuracy in searching the pole orientation of an asteroid. For further improving the efficiency of TRV, parallel versions of this algorithm implemented with OpenMP and CUDA C schemes are provided with environments of Hygon C86 7185 CPUs and a Tesla V100-SXM3 GPU, respectively. The maximum speedup ratio of the OpenMP scheme is 79.567x, while that of the CUDA C scheme is 110.906x. The results show that the proposed parallel acceleration schemes can greatly improve the inversion efficiency of the TRV algorithm, and can be widely used in searching the parameters of a large number of asteroids.

Spectral analysis of basaltic asteroids observed by the Gaia space mission

ABSTRACT There is a great deal of scientific interest in characterizing the basaltic asteroids (spectrally classified as V-types), as they are the key to understanding planetesimal formation and evolution in the early Solar system. These have long been recognized as parts of the crusts of fully differentiated planetesimals. Thus, their multiplicity, distribution, and physical characteristics are crucial for providing context for and constraining the theoretical evolution models of the Solar system. In this work, we perform spectral analysis with an extended data set of spectral measurements from the ESA Gaia mission Data Release 3, thus increasing the sample size of the analysed V-types by more than three times as compared to the literature. Using the data provided by Gaia, we identified ∼2000 possible V-type asteroids. About 350 of them successfully pass our data validation criteria. This sample includes 31 new V-type asteroids beyond 2.5 au and 6 in the Phocaea region. We confirm that the V-type asteroids in the middle and outer part of the main belt show distinct spectral properties compared to typical vestoids. In the inner main belt, we found a great diversity of spectral parameters among the V-types in all populations. Number of asteroids show band depths even greater than that of (1459) Magnya. Furthermore, some objects present 0.9 μm band-centres more than one standard deviation away from the typical value for vestoids. However since the DR3 band centres are often overestimated, those findings are to be confirmed. Overall our results indicate that the inner main belt may contain remnants of multiple differentiated planetesimals, not just (4) Vesta.

The Nature of Low-albedo Small Bodies from 3 μm Spectroscopy: One Group that Formed within the Ammonia Snow Line and One that Formed beyond It

We present evidence, via a large survey of 191 new spectra along with previously published spectra, of a divide in the 3 μm spectral properties of the low-albedo asteroid population. One group (“sharp types,” or STs, with band centers <3 μm) has a spectral shape consistent with carbonaceous chondrite meteorites, while the other group (“not sharp types,” or NSTs, with bands centered >3 μm) is not represented in the meteorite literature but is as abundant as the STs among large objects. Both groups are present in most low-albedo asteroid taxonomic classes, and, except in limited cases, taxonomic classifications based on 0.5–2.5 μm data alone cannot predict whether an asteroid is an ST or NST. Statistical tests show that the STs and NSTs differ in average band depth, semimajor axis, and perihelion at confidence levels ≥98% while not showing significant differences in albedo. We also show that many NSTs have a 3 μm absorption band shape like comet 67P and likely represent an important small-body composition throughout the solar system. A simple explanation for the origin of these groups is formation on opposite sides of the ammonia snow line, with the NST group accreting H2O and NH3 and the ST group only accreting H2O, with subsequent thermal and chemical evolution resulting in the minerals seen today. Such an explanation is consistent with recent dynamical modeling of planetesimal formation and delivery and suggests that much more outer solar system material was delivered to the main asteroid belt than would be thought based on the number of D-class asteroids found today.

Radar and Optical Characterization of Near-Earth Asteroid 2019 OK

We conducted radar observations of near-Earth asteroid 2019 OK on 2019 July 25 using the Arecibo Observatory S-band (2380 MHz, 12.6 cm) planetary radar system. Based on Arecibo and optical observations the apparent diameter is between 70 and 130 m. Combined with an absolute magnitude of H = 23.3 ± 0.3, the optical albedo of 2019 OK is likely between 0.05 and 0.17. Our measured radar circular polarization ratio of μ C = 0.33 ± 0.03 indicates 2019 OK is likely not a V- or E-type asteroid and is most likely a C- or S-type. The measured radar echo bandwidth of 39 ± 2 Hz restricts the apparent rotation period to be approximately between 3 minutes (0.049 hr, D = 70 m) and 5 minutes (0.091 h, D = 130 m). Together, the apparent diameter and rotation period suggest that 2019 OK is likely not a rubble-pile body bound only by gravity. 2019 OK is one of a growing number of fast-rotating near-Earth asteroids that require some internal strength to keep them from breaking apart.