First Results from the Rapid-response Spectrophotometric Characterization of Near-Earth Objects Using RATIR

Navarro-Meza, S.; Mommert, Michael; Trilling, David E.; Butler, N.; Reyes-Ruiz, M.; Pichardo, B.; Axelrod, T. S.; Jedicke, Robert; Moskovitz, N.

doi:10.3847/1538-3881/ab1138

Cited by 5 publications

(7 citation statements)

References 26 publications

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“…DeMeo et al (2019) investigated A-type candidates extracted from the SDSS catalog. Spectrophotometric characterization is also often used to constrain the composition of near-Earth objects Mommert et al (2016);Navarro-Meza et al (2019); Erasmus et al (2017); Harris and Davies (1999); Bolin et al (2020);De León et al (2010). discussed the distribution of very red D-type asteroids located in the main belt (typically found among Jupiter trojans and in the outer main belt) and their potential origins.…”

Section: Introductionmentioning

confidence: 99%

Predicting Asteroid Types: Importance of Individual and Combined Features

Klimczak

Kotłowski

Oszkiewicz

et al. 2021

Front. Astron. Space Sci.

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Asteroid taxonomies provide a link to surface composition and mineralogy of those objects, although that connection is not fully unique. Currently, one of the most commonly used asteroid taxonomies is that of Bus-DeMeo. The spectral range covering 0.45–2.45 μm is used to assign a taxonomic class in that scheme. Such observations are only available for a few hundreds of asteroids (out of over one million). On the other hand, a growing amount of space and ground-based surveys delivers multi-filter photometry, which is often used in predicting asteroid types. Those surveys are typically dedicated to studying other astronomical objects, and thus not optimized for asteroid taxonomic classifications. The goal of this study was to quantify the importance and performance of different asteroid spectral features, parameterizations, and methods in predicting the asteroid types. Furthermore, we aimed to identify the key spectral features that can be used to optimize future surveys toward asteroid characterization. Those broad surveys typically are restricted to a few bands; therefore, selecting those that best link them to asteroid taxonomy is crucial in light of maximizing the science output for solar system studies. First, we verified that with the increased number of asteroid spectra, the Bus–DeMeo procedure to create taxonomy still produces the same overall scheme. Second, we confirmed that machine learning methods such as naive Bayes, support vector machine (SVM), gradient boosting, and multilayer networks can reproduce that taxonomic classification at a high rate of over 81% balanced accuracy for types and 93% for complexes. We found that multilayer perceptron with three layers of 32 neurons and stochastic gradient descent solver, batch size of 32, and adaptive learning performed the best in the classification task. Furthermore, the top five features (spectral slope and reflectance at 1.05, 0.9, 0.65, and 1.1 μm) are enough to obtain a balanced accuracy of 93% for the prediction of complexes and six features (spectral slope and reflectance at 1.4, 1.05, 0.9, 0.95, and 0.65 μm) to obtain 81% balanced accuracy for taxonomic types. Thus, to optimize future surveys toward asteroid classification, we recommend using filters that cover those features.

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Section: Introductionmentioning

confidence: 99%

Predicting Asteroid Types: Importance of Individual and Combined Features

Klimczak

Kotłowski

Oszkiewicz

et al. 2021

Front. Astron. Space Sci.

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“…Krugly et al 2002;Chang et al 2015), spectrophotometry (e.g. Mommert et al 2016;Erasmus et al 2017;Navarro-Meza et al 2019), spectroscopy (e.g Binzel et al 2004Binzel et al , 2019, radar techniques (e.g. Ostro et al 2006), andpolarimetry (e.g.…”

Section: Introductionmentioning

confidence: 99%

Visible Spectroscopy from the Mission Accessible Near-Earth Object Survey (MANOS): Taxonomic Dependence on Asteroid Size

Devogèle

Moskovitz

Thirouin

et al. 2019

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The Mission Accessible Near-Earth Object Survey (MANOS) aims to observe and characterize small (mean absolute magnitude H ∼ 25 mag) Near-Earth Objects (NEOs) that are accessible by spacecraft (mean ∆v ∼ 5.7 km/s) and that make close approaches with the Earth (mean Minimum Orbital Intersection Distance MOID ∼ 0.03 AU). We present here the first results of the MANOS visible spectroscopic survey. The spectra were obtained from August 2013 to March 2018 at Lowell Observatory's Discovery Channel 4.3 meter telescope, and both Gemini North and South facilities. In total, 210 NEOs have been observed and taxonomically classified. Our taxonomic distribution shows significant variations with respect to surveys of larger objects. We suspect these to be due to a dependence of Main Belt source regions on object size. Compared to previous surveys of larger objects (Binzel et al. 2019Perna et al. 2018), we report a lower fraction of S+Q-complex asteroids of 43.8 ± 4.6%. We associate this decrease with a lack of Phocaea family members at very small size. We also report higher fractions of X-complex and A-type asteroids of 23.8 ± 3.3% and 3.8 ± 1.3% respectively due to an increase of Hungaria family objects at small size. We find a strong correlation between the Q/S ratio and perihelion distance. We suggest this correlation is due to planetary close encounters with Venus playing a major role in turning asteroids from S to Q-type. This hypothesis is supported by a similar correlation between the Q/S ratio and Venus MOID.

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“…Observations with visible-only data (Set 3) incorporate data from two bands (one color, thus 1D) and it is not possible to perform a robust analysis like the one described above. For these data, we use a modification of the model presented in Navarro-Meza et al (2019). The mathematical description is below, but in plain words, all the objects from Set 3 are analyzed in bulk: we build a distribution using the measured ri color of each object and the error; then, using synthetic samples of asteroids, we find the most likely classification (C or S type) of our distribution.…”

Section: Monte Carlo Simulations With Synthetic Objectsmentioning

confidence: 99%

“…Recent observations of asteroids in near-Earth space (Mommert et al 2016;Erasmus et al 2017;Ieva et al 2018;Lin et al 2018;Perna et al 2018;Binzel et al 2019;Devogèle et al 2019;Navarro-Meza et al 2019) have shown that the taxonomy of NEOs is size dependent and different from the objects in the MB. Currently, we are unable to observe subkilometer objects in the MB, so a comparison between these and small NEOs is not possible.…”

Section: Introductionmentioning

confidence: 99%

“…Here we present a combination of spectrophotometry and rapid-response observations, i.e., observations that are obtained shortly after the discovery of the target, when it is still relatively bright. This study is part of a worldwide systematic survey of NEO compositions (see Mommert et al 2016;Erasmus et al 2017;Navarro-Meza et al 2019, for our previous results), aimed to increase the number of small NEOs with physical information, which is of interest for science, industry, and planetary safety. The rapid-response approach is generally not feasible through classical observing proposals due to heavily oversubscribed classically scheduled major research facilities.…”

Section: Introductionmentioning

confidence: 99%

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Taxonomy of Subkilometer Near-Earth Objects from Multiwavelength Photometry with RATIR

Navarro-Meza,

Trilling,

Mommert

et al. 2024

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We present results from observations of 238 near-Earth objects (NEOs) obtained with the RATIR instrument on the 1.5 m robotic telescope at San Pedro Martir’s National Observatory in Mexico, in the frame of our multiobservatory, multifilter campaign. Our project is focused on rapid response photometric observations of NEOs with absolute magnitudes in the range 18.1–27.1 (diameter ≈ 600 and 10 m, respectively). Data with coverage in the near-infrared and visible range were analyzed with a nonparametric classification algorithm, while visible-only data were independently analyzed via Monte Carlo simulations and a 1-Nearest Neighbor method. The rapid response and the use of spectrophotometry allows us to obtain taxonomic classifications of subkilometer objects with small telescopes, representing a convenient characterization strategy. We present taxonomic classifications of the 87 objects observed in the visible and near-infrared. We also present the taxonomic distribution of an additional 151 objects observed in the visible. Our most accurate method suggests a nonfeatured-to-featured ratio of ≈0.75, which is consistent with the value found by the Mission Accessible Near-Earth Object Survey, which conducted a similar study using a spectral analysis. The results from the Monte Carlo method suggest a ratio of ≈0.8, although this method has some limitations. The 1-Nearest Neighbor method showed to be not suitable for NEO classifications.

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First Results from the Rapid-response Spectrophotometric Characterization of Near-Earth Objects Using RATIR

Cited by 5 publications

References 26 publications

Predicting Asteroid Types: Importance of Individual and Combined Features

Predicting Asteroid Types: Importance of Individual and Combined Features

Visible Spectroscopy from the Mission Accessible Near-Earth Object Survey (MANOS): Taxonomic Dependence on Asteroid Size

Taxonomy of Subkilometer Near-Earth Objects from Multiwavelength Photometry with RATIR

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