Asteroid Diameters and Albedos from NEOWISE Reactivation Mission Years Four and Five
Joseph R. Masiero, A.K. Mainzer, J.M. Bauer, R.M. Cutri, T. Grav, E. Kramer, J. Pittichová, S. Sonnett, E.L. Wright
AAsteroid Diameters and Albedos from NEOWISE Reactivation Mission YearsFour and Five
Joseph R. Masiero , A.K. Mainzer , J.M. Bauer , R.M. Cutri , T. Grav , , E. Kramer , J.Pittichov´a , S. Sonnett , E.L. Wright ABSTRACT
The Near-Earth Object Wide-field Infrared Survey Explorer (NEOWISE) spacecrafthas been conducting a two-band thermal infrared survey to detect and characterize as-teroids and comets since its reactivation in Dec 2013. Using the observations collectedduring the fourth and fifth years of the survey, our automated pipeline detected can-didate moving objects which were verified and reported to the Minor Planet Center.Using these detections, we perform thermal modeling of each object from the near-Earth object and Main Belt asteroid populations to constrain their sizes. We presentthermal model fits of asteroid diameters for 189 NEOs and 5831 MBAs detected duringthe fourth year of the survey, and 185 NEOs and 5776 MBAs from the fifth year. Todate, the NEOWISE Reactivation survey has provided thermal model characterizationfor 957 unique NEOs. Including all phases of the original WISE survey brings the totalto 1473 unique NEOs that have been characterized between 2010 and the present.
1. Introduction
The Near Earth Object Wide-field Infrared Survey Explorer (NEOWISE, Mainzer et al. et al. ). The content and characteristicsof NEOWISE data are described in Cutri et al. (2015). Jet Propulsion Laboratory/California Institute of Technology, 4800 Oak Grove Dr., MS 183-301, Pasadena, CA91109, USA,
[email protected] Lunar and Planetary Laboratory, University of Arizona, Tucson, AZ, 85721, USA University of Maryland, College Park, MD, 20742, USA California Institute of Technology, IPAC, 1200 California Blvd, Pasadena, CA 91125 USA Planetary Science Institute, Tucson, AZ 85719 USA University of California, Los Angeles, CA, 90095, USA https://irsa.ipac.caltech.edu a r X i v : . [ a s t r o - ph . E P ] F e b et al. et al. et al. (2015, 2016); Masiero et al. (2017). Thesefits, along with those from previous survey phases, have been archived in the NASA Planetary DataSystem (Mainzer et al.
2. Observations
NEOWISE scans the sky along lines of constant ecliptic longitude, recording images every 11seconds, as the spacecraft orbits the Earth in a 94-minute polar orbit. The spacecraft was origi-nally launched onto a terminator-following orbit. Since then, as expected, the orbit has graduallyprecessed off of the terminator to an average offset of ∼ − ◦ during the survey’s fourth andfifth years . On the evening side of the orbit the spacecraft continues to survey at the zenith pointwith respect to Earth, and thus at larger Solar elongations, but on the morning side the telescopecannot point closer to the Sun and therefore must maintain a pointing at Solar elongation of ∼ ◦ ,away from the local zenith point. This off-zenith pointing results in an increase in the heat loadon the telescope from the Earth that gradually raises the telescope temperature over time. As inthe past, NEOWISE continues to toggle its scan circles to avoid the Moon, speeding and slowingthe progression of the survey to avoid directly scanning over it. NEOWISE collects ∼
12 detec-tions per moving object over a span of ∼
30 hours for objects near the ecliptic. Objects closer tothe ecliptic poles can follow the survey region for long periods of time resulting in longer sets ofobservations, while objects near the detection limit may be detected fewer times as noise and lightcurve variations shift them below the cutoff level.Over the course of six months as the Earth orbits the Sun, NEOWISE obtains images of the An illustration of this precession is shown in Cutri et al. (2015), Sec I.2.b, Figure 8 et al. et al. for publication and archiving.WMOPS requires a minimum of 5 detections at a signal-to-noise ratio of SNR > .
5, and hasbeen shown to have an efficiency of 85% −
90% for bright objects within our selection requirementson number of detections and motion vectors(Mainzer et al. et al. et al. . µ m(W1) and 4 . µ m (W2) bandpasses. For objects with heliocentric distances near 1 AU, W2 isgenerally dominated by thermal emission while W1 can be thermally dominated or a mixture ofthermal emission and reflected light depending on the temperature of the object and how reflectivethe object is at 3 . µ m. For more distant objects, e.g. Main Belt asteroids (MBAs), W1 is almostalways dominated by reflected light and W2 can range from thermally-dominated to reflected-light-dominated depending on the object’s distance from the Sun and 4 . µ m reflectivity. As a result, forthe majority of detected NEOs we have sufficient information to perform basic thermal modelingusing simplifying assumptions to reduce the number of variable parameters (such as assumingthe value for the beaming parameter and ratio of the infrared albedo to the visible albedo). ForMBAs, conversely, only about half of the objects detected had sufficient thermal emission to allowthermal modeling to set a constraint on the diameter. The remaining objects, which had significantcontributions of reflected light to both NEOWISE bandpasses, are not included in the subsequentanalysis. Astrometric detections of them are still recorded in the Minor Planet Center’s database.For more details on the survey and telescope, refer to the NEOWISE Explanatory Supplement et al.
3. Thermal Modeling Technique
The measured thermal flux from an asteroid depends on the object’s temperature, observinggeometry, and size. When enough astrometric measurements are available to allow for the orbitto be constrained, the distances to the Sun, Earth, and spacecraft as well as the phase angle atthe time of observation will be sufficiently well-known to contribute negligible error to the finalthermal model fit. Thus, by employing a model of the thermal properties of the surface, alongwith the known observational geometries, the diameter of the asteroid can be constrained basedon the measured flux in the thermally dominated bands. Using optical measurements from theliterature (in particular, the absolute H magnitude published along with the orbital information)the albedo of the asteroid can also be constrained, however the uncertainty on this value dependson the uncertainties on the diameter and the H magnitude (cf. Masiero et al. The process for data extraction follows the same method used in Masiero et al. (2017). Toextract the data for use in thermal fitting, we refer to the Minor Planet Center’s ObservationsCatalog , which contains all observations of asteroids and comets submitted by NEOWISE (obser-vatory code C51) that were vetted and published by the MPC. We extracted all observations fromC51 within survey Year 4 and Year 5. By using the MPC-accepted observations, we have a dataset that has initial source rejection done by the WMOPS pipeline as well as subsequent checks onpositional offsets by MPC that can flag the occasional observation that was contaminated by cosmicrays or other artifacts. To obtain the fluxes associated with each detection reported to the MPC weuse the position-time measurements as an input for the search of the NEOWISE Single-Exposuresource database hosted by IRSA, conducting a search for extracted sources within 5 arcsec of theposition and 5 secs of the MJD reported to the MPC.NEOWISE source detection and photometry is carried out using the expected PSF at thatlocation on each detector simultaneously (Cutri et al. χ value for each bandpass. We performeda filtering on the detections prior to using them for thermal modeling based on their reduced χ of the fit of the model PSF to the W2 detection (parameter w rchi w rchi >
5. This cut removes detections that may be contaminated by cosmic rays or otherspurious noise that could potentially bias the fitted diameter. We also remove from considerationany object with an orbital arc shorter than 0.01 years, as these objects received little-to-no ground http://minorplanetcenter.net/iau/ECS/MPCAT-OBS/MPCAT-OBS.html H V absolute magnitude and G slope parameter provided by the Minor Planet Center.When available, we updated the H-G parameters using the values published by Vereˇs et al. (2015)from the Pan-STARRS survey for objects that had phase coverage > ◦ in those data (cf. Masiero et al. H of 0 .
05 mag for the Main Belt and0 . G of 0 . H is appropriate. Assuming a larger uncertainty on H forMBAs can allow a reflected light measurement in W1 to dominate the least-squares fitting of thatcomponent of the model, and result in poor matches to the published H magnitude in some cases. For our fitting, we employ the Near-Earth Asteroid Thermal Model (NEATM, Harris 1998).This model provides a simple description of the behavior of temperature across the surface ofa spherical asteroid, making use of a “beaming parameter” η to consolidate uncertainties in theassumed values of the physical properties and differences between the model and actual temperaturedistribution. Extreme values in the beaming parameter can also provide indications of potentiallyunusual composition (cf. Harris & Drube 2014). In all cases, we used an assumed value for thebeaming parameter based on the distribution of fitted beaming values from the cryogenic NEOWISEmission (Mainzer et al. et al. η = 1 . ± .
5, while forMBAs we assume η = 0 . ± .
2. This 1 σ uncertainty is used when conducting our Monte Carloanalysis to propagate to the final uncertainty on the fitted parameters diameter and albedo and isassumed to be normally distributed around the mean value.We note that in previous analyses (e.g. Nugent et al. et al. . et al. et al. et al. et al. σ diameter uncertainty for the population of objectsobserved with W1 and W2 and fit with NEATM is ∼ et al. et al. et al. scipy package(Jones et al. < .
25 mag(SNR ∼
4) in a WISE band for it to be used in fitting. We only use an additional band forfitting if the number of detections is more than 40% of the number in the band with the largestnumber of detections. This requirement is designed to remove potential contamination from cosmicrays and background objects that may have been missed by other filters. It also results in arequirement that there are at least 3 detections for a second band to be used in the minimum caseof a 5-detection tracklet (the lower limit produced by WMOPS). The published H and G visiblephotometric parameters are also included as a measurement to be fitted by the least-squares fitter.The asteroid’s orbit is used to determine Sun-to-object and object-to-spacecraft distances as wellas phase angle at each observation time, which is used by NEATM to determine the temperaturedistribution across the surface. Specifically, we use a faceted sphere made up of 288 facets in bandsspaced at 15 degrees in latitude and calculate the temperature on each facet as well as the resultingemission that would be observed.Reflected light at visible wavelengths is constrained by the H magnitude measurement. Toconstrain the reflected light in the NEOWISE bandpasses, we assume a ratio of albedos between 7 –the infrared and visible of 1 . ± . . ± . et al. et al. ν region.) In cases where the W1 bandis dominated by reflected light and has a very high SNR, the assumed infrared-to-visible albedoratio can result in the least-squares minimizer finding a best fit solution where the predicted H magnitude (based on the fitted diameter and optical albedo) does not match the measured valueexactly. Fits with large deviations between the model and measured H magnitudes are checked toensure the solutions are physically plausible. In addition, fits with visible albedos below p V < . p V = 0 . et al. σ uncertainty.These quoted uncertainties will only represent the statistical component of the model fit, and donot account for systematic offsets of the NEATM model with respect to reality.
4. Results
We present our model fits for NEOs and MBAs observed during Year 4 in Table 1 and Ta-ble 2 respectively. Fits for NEOs and MBAs observed during Year 5 are given in Tables 3 and 4respectively. Year 4 contains 214 fits of 189 unique NEOs, and 6658 fits of 5831 unique MBAs.Year 5 contains 215 fits for 185 unique NEOs, and 6600 fits of 5776 unique MBAs. Each table givesthe object’s name (in MPC-packed format), the measured H and G values used in the process offitting, the number of observations used in W1 and W2, the orbital phase angle at the midpoint ofthe observations, along with the best-fit diameter, the visible albedo, and beaming parameter, withtheir associated uncertainties. As we held beaming fixed for all fits in this work, the beaming flagin the tables are all set to 0, but the flag is retained for easy comparison to previously publishedresults. For objects that were seen at multiple epochs in a given year, we present each fit as aseparate entry in the tables. For objects that have non-spherical shapes, different epochs can helpconstrain the true spherical equivalent diameter instead of the projection-dependent results froma single epoch. Alternately, different epochs can provide insight into the thermal behavior of thesurface. Thus, different diameter constraints from different epochs of observation could be due tochanging physical parameters, or simply be a result of statistical noise.We note that one object in the Year 5 NEO table, 2018 KK , has a best-fit albedo p V < .
01 8 –despite our attempts at filtering or changing assumed parameters. This Amor-class NEO has anorbital arc spanning ∼ ∼ ◦ of phase, however the scatter inthe photometry means that the published H value is not necessarily well-constrained (see Figure 1).The NEOWISE observations of this object occurred at a phase of α = 30 ◦ , so a poorly constrainedG value won’t have as large an effect on the predicted brightness at the time of our observations. Anunderestimated brightness from an H value that was too large would drive the albedo to artificiallylow values. The unphysically low albedo is then likely the result of a combination of poor H fitand statistical uncertainty on the size measurement, possibly combined with light curve variations.We include the best fit as reported by our model in the results table. While the diameter shouldbe reliable to the quoted errors, caution should be used regarding the interpretation of the albedofor this object. This highlights the impact that uncertainty on the optical measurements has onour ability to determine albedos, and shows the need for improved H and G determinations for allobjects from a photometrically calibrated survey (e.g. Juri´c et al. et al. V m a g ( d i s t a n c e c o rr e c t e d ) Fig. 1.— Distance-corrected magnitude measurements for asteroid 2018 KK from the Minor PlanetCenter observation database are shown with black points. The dashed line is the expected photo-metric behavior of an object with H = 18 . G = 0 .
15. Magnitudes were converted from the ob-served G and R bands assuming Solar colors of V − R = 0 .
36 and G − V = − .
14 (Ram´ırez et al. http://gea.esac.esa.int/archive/documentation/GDR2/ )), com-patible with a flat-spectral slope expected for low-albedo C-type objects.We show a plot of diameter and albedo for all near-Earth objects detected by NEOWISE fromDec 2013 to Dec 2018 in Figure 2. Objects discovered by NEOWISE show a preference for beinglow albedo, with many of them being larger than 200 m in diameter. This population of objects ismore likely to be missed by the visible light ground-based surveys due to albedo-dependent selectioneffects inherent in those systems. Thus, while NEOWISE is primarily a NEO-characterization 9 –mission, it fills an important part of phase space in the current suite of near-Earth object discoverysurveys.Table 1: Thermal model fits for NEOs detected in the fourth year of the NEOWISE survey. Table 1is published in its entirety in the electronic edition; a portion is shown here for guidance regardingits form and content.Name H † G Diameter p †† V beaming ††† n W n W phase Fitted(mag) (km) (deg) Beaming?01864 14.85 0.15 2.73 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± † Measured H used as input for the modeling; the model-output H value can be found using theoutput diameter, albedo, and the equation D = 1329 ∗ H/ − / √ p V †† Albedo uncertainties are symmetric in log-space as the error is dominated by the uncertainty on H ; the asymmetric linear equivalents of the 1 σ log-space uncertainties are presented here. ††† Assumed constant value; not fit. 10 –Table 2: Thermal model fits for MBAs detected in the fourth year of the NEOWISE survey. Table2 is published in its entirety in the electronic edition; a portion is shown here for guidance regardingits form and content.Name H † G Diameter p †† V beaming ††† n W n W phase Fitted(mag) (km) (deg) Beaming?00010 5.43 0.15 438.31 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± † Measured H used as input for the modeling; the model-output H value can be found using theoutput diameter, albedo, and the equation D = 1329 ∗ H/ − / √ p V †† Albedo uncertainties are symmetric in log-space as the error is dominated by the uncertainty on H ; the asymmetric linear equivalents of the 1 σ log-space uncertainties are presented here. ††† Assumed constant value; not fit. 11 –Table 3: Thermal model fits for NEOs detected in the fifth year of the NEOWISE survey. Table 3is published in its entirety in the electronic edition; a portion is shown here for guidance regardingits form and content.Name H † G Diameter p †† V beaming ††† n W n W phase Fitted(mag) (km) (deg) Beaming?00719 15.50 0.15 2.59 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± † Measured H used as input for the modeling; the model-output H value can be found using theoutput diameter, albedo, and the equation D = 1329 ∗ H/ − / √ p V †† Albedo uncertainties are symmetric in log-space as the error is dominated by the uncertainty on H ; the asymmetric linear equivalents of the 1 σ log-space uncertainties are presented here. ††† Assumed constant value; not fit. 12 –Table 4: Thermal model fits for MBAs detected in the fifth year of the NEOWISE survey. Table 4is published in its entirety in the electronic edition; a portion is shown here for guidance regardingits form and content.Name H † G Diameter p †† V beaming ††† n W n W phase Fitted(mag) (km) (deg) Beaming?00013 6.74 0.15 219.07 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± † Measured H used as input for the modeling; the model-output H value can be found using theoutput diameter, albedo, and the equation D = 1329 ∗ H/ − / √ p V †† Albedo uncertainties are symmetric in log-space as the error is dominated by the uncertainty on H ; the asymmetric linear equivalents of the 1 σ log-space uncertainties are presented here. ††† Assumed constant value; not fit. 13 – Diameter (km) v i s i b l e a l b e d o Fig. 2.— Comparison of fitted diameters and albedos for all near-Earth objects observed (cyancircles) and discovered (black squares) by NEOWISE during the first five years of the reactivationsurvey (Dec 2013 to Dec 2018) by the WMOPS pipeline. The majority of objects discovered byNEOWISE tend to have albedos below 10% and diameters larger than a few hundred meters, fillingin a region of phase space missed by other surveys (cf. Mainzer et al.
5. Accuracy of the NEATM Thermal Modeling
As discussed in Wright et al. (2019), the diameters derived by NEOWISE have a characteristic1 σ uncertainty in effective spherical diameter of ∼
10% for objects with sufficient data to fit multiplethermal bands. This was found through comparisons between diameter fits from NEOWISE anddiameters determined by the IRAS satellite (Tedesco et al. et al. (2014) found a similarresult for comparisons between the cryogenic NEOWISE fits and AKARI. These works focused ondata from the cryogenic mission, so an independent check of the fits based on 2-band Reactivationdata is appropriate. We show the comparison between the NEOWISE Reactivation survey years 4and 5 diameters and the diameters from the IRAS and AKARI data (for objects with more than5 detections to reduce selection effect biases) in Figure 3. AKARI Diameter (km)10 Y e a r / D i a m e t e r ( k m ) (c) 10 AKARI Diameter (km)1.000.750.500.250.000.250.500.751.00 F r a c t i o n a l D i a m e t e r D i ff e r e n c e
17% with systematic offsets of no more than a few percent. The comparison to the NEOWISEcryogenic diameters shows a ∼
5% offset for the population, with a comparable offset seen in theAKARI and IRAS comparisons. This offset is not seen in the comparison to the earlier NEOWISEreactivation diameters, so indicates a shift between the cryogenic and reactivation fits. This offset,however, is within the 10% minimum systematic uncertainty we assume for our implementation ofour thermal model (Mainzer et al. et al. et al. ∼ − et al. (2018). We do not fit a Gaussian to the comparison betweenNEOs and non-infrared diameter sources due to the small number of measurements in this dataset( N = 8). 16 – Sat+Radar+Occ Diameter (km)10 Y e a r / D i a m e t e r ( k m ) (a) 10 Sat+Radar+Occ Diameter (km)1.000.750.500.250.000.250.500.751.00 F r a c t i o n a l D i a m e t e r D i ff e r e n c e
6. Conclusions
We present thermal model fits to near-Earth objects and Main Belt asteroids detected duringthe fourth and fifth years of the reactivated NEOWISE survey. Included are 214 fits of 189 uniqueNEOs and 6658 fits of 5831 MBAs from Year 4, and 215 fits of 185 unique NEOs and 6600 fits of5776 MBAs from Year 5. We follow the data quality restrictions used for the fits to the NEOWISEYear 3 data (Masiero et al. >
10% modeled reflected light inthe W2 band as unstable solutions. This results in a large number of detected MBAs being rejectedfrom the thermal fit results, but improves the fit reliability. This cut will introduce a strong biasagainst high albedo objects in the list of Main Belt objects characterized.We find that the diameter fits for Main Belt asteroids have a characteristic 1 σ uncertainty of ∼
15% compared to other data sets (assuming a Gaussian distribution), while NEOs show a largeruncertainty of ∼ − Acknowledgments
The authors would like to thank the two anonymous referees for their helpful comments thatimproved this manuscript. This publication makes use of data products from the Wide-field InfraredSurvey Explorer, which is a joint project of the University of California, Los Angeles, and the JetPropulsion Laboratory/California Institute of Technology, funded by the National Aeronauticsand Space Administration. This publication also makes use of data products from NEOWISE,which is a project of the Jet Propulsion Laboratory/California Institute of Technology, fundedby the Planetary Science Division of the National Aeronautics and Space Administration. Theresearch was carried out at the Jet Propulsion Laboratory, California Institute of Technology,under a contract with the National Aeronautics and Space Administration (80NM0018D004). Thisresearch has made use of data and services provided by the International Astronomical Union’sMinor Planet Center. This publication uses data obtained from the NASA Planetary Data System(PDS). This research has made use of the NASA/IPAC Infrared Science Archive,which is funded 19 –by the National Aeronautics and Space Administration and operated by the California Instituteof Technology. This research has made extensive use of the numpy , scipy , and matplotlib Pythonpackages. Based on observations obtained at the Gemini Observatory, which is operated by theAssociation of Universities for Research in Astronomy, Inc., under a cooperative agreement withthe NSF on behalf of the Gemini partnership: the National Science Foundation (United States),the National Research Council (Canada), CONICYT (Chile), Ministerio de Ciencia, Tecnolog´ıa eInnovaci´on Productiva (Argentina), and Minist´erio da Ciˆencia, Tecnologia e Inova¸c˜ao (Brazil). Theauthors also acknowledge the efforts of worldwide NEO followup observers who provide time-criticalastrometric measurements of newly discovered NEOs, enabling object recovery and computation oforbital elements. Many of these efforts would not be possible without the financial support of theNASA Near-Earth Object Observations Program, for which we are grateful.
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