The Gaia-FUN-SSO observation campaign of 99942 Apophis: A preliminary test for the network
D. Bancelin, W. Thuillot, A. Ivantsov, J. Desmars, M. Assafin, S. Eggl, D. Hestroffer, P. Rocher, B. Carry, P. David, Gaia-FUN-SSO team
TThe Gaia-FUN-SSO observation campaign of 99942 Apophis: A preliminarytest for the network
D. Bancelin , , W. Thuillot , A. Ivantsov , J. Desmars , , M. Assafin , S. Eggl , D. Hestroffer , P.Rocher , B. Carry , P. David and the Gaia-FUN-SSO team1. Institute of Astrophysics, University of Vienna, Austria; [email protected]. IMCCE, Paris observatory, 75014 Paris, France3. Faculty of Aerospace Engineering, Haifa, Isra¨el4. Observatorio National, Rio de Janeiro, Brazil5. Observatorio do Valongo, Rio de Janeiro, Brazil In order to test the coordination and evaluate the overall performance of the Gaia-FUN-SSO,an observation campaign on the Potentially Hazardous Asteroid (99 942) Apophis was conductedfrom 12/21/2012 to 5/2/2013 providing 2732 high quality astrometric observations. We showthat a consistent reduction of astrometric campaigns with reliable stellar catalogs substantiallyimproves the quality of astrometric results. We present evidence that the new data will help toreduce the orbit uncertainty of Apophis during its close approach in 2029.
In the framework of the Gaia mission, an alert mode (a ground-based follow-up network[Thuillot, 2011]), has been set up in order to identify newly detected objects and trigger comple-mentary observations from the ground, since the satellite cannot keep monitoring its discoveries.Specific training campaigns have been organized during the past three years. In particular, theobservation campaign of Apophis from 12/21/2012 to 5/2/2013, providing 2732 valuable astro-metric measurements among the collection of extensive observations. Some of the observationsperformed, already submitted to the MPC, have been reduced by the observers themselves, usingtheir preferred tools and astrometric catalogs. However, we decided to conduct a complementaryhomogeneous reduction, with all CCD images recorded during this campaign using the PRAIAreduction pipeline [Assafin et al., 2011] and the UCAC4 astrometric catalog [Zacharias et al.,2013]. This yields to consistent set of 2732 astrometric measurements of Apophis. In the followingwe will discuss data analysis of the observations acquired by the Gaia-FUN-SSO. We will showthat a consistent analysis can decrease systematic errors and boost the quality of astrometricpositions.
Among the 2732 astrometric measurements, 629 had already been sent ot the MPC by theobservers. This gives us an unique opportunity to compare the consistency of these observationsaccording to the catalog used for the data reduction. We thus define:– D
MPC as the 629 duplicated Gaia-FUN-SSO astrometric measurements already sent tothe MPC by the observers. The corresponding observations were reduced with variousastrometric software packages and catalogs.– D
PRAIA as the same 629 Gaia-FUN-SSO observations, but re-reduced with PRAIA usingthe UCAC4 astrometric catalog.– S
NEW as the 2109 unsent observations. 1 a r X i v : . [ a s t r o - ph . E P ] A ug .1 Alert and recovery process Using a similar approach as Bancelin et al. [2012], we aim to assess how far the predictedposition can drift from the real one in a given amount of time. Let us consider a hypotheticaldiscovery of an asteroid during the Gaia-FUN-SSO campaign. We will use the observational dataof Apophis, but we shall assume its orbit was previously unknown. Furthermore, we assumethat the hypothetical discovery has happened on the first night recorded in the duplicatedmeasurements D
PRAIA and D
MPC . This first night set is used to determine the orbit and orbitalelements covariance matrix of the new object. We then propagated the orbit solutions anduncertainties obtained from both sets up to six days after the discovery. One week after thediscovery the coordinate differences ∆ α and ∆ δ between D PRAIA , D
MPC and the ”true” positionof Apophis (obtained with the 2004-2014 optical and radar data) are evaluated. Figure 1 showshow the differences in astrometric coordinates evolve for both sets of measurements during thesix days following the discovery. The opposing orientation of the (∆ α ,∆ δ ) MPC and (∆ α ,∆ δ ) PRAIA curves is due to the different preliminary orbital elements found using D
P RAIA and D
MPC . Onecan see that (∆ α ,∆ δ ) MPC and (∆ α ,∆ δ ) PRAIA are of the same order of magnitude. Consequently,the method of data reduction is unlikely to have a significant impact on the recovery processwithin the network. -0.25-0.2-0.15-0.1-0.05 0 0.05 0.1 0.15 0.2 0.25 1 2 3 4 5 6
Coordinates difference[arcdeg]
Day after discovery ∆α MPC ∆δ MPC ∆α PRAIA ∆δ PRAIA
Fig.
The graph shows the time evolution of the coordinate differences ( ∆ α , ∆ δ ) MPC and( ∆ α , ∆ δ ) PRAIA between orbit solutions derived from different data sets with respect to the nomi-nal solution (obtained using all the optical and radar data available)
We are now interested in how the position uncertainty evolves when more observationsbecome available during the nights following an asteroid’s discovery. As we assume the asteroidto be newly discovered, a preliminary orbit determination is conducted after the first night of thesets D
PRAIA and D
MPC and an orbital improvement is performed. Uncertainties on the geocentricposition is then calculated. This allows us to compare the impact of the reduction pipeline onthe uncertainty evolution of a newly found object. Figure 2 shows that at the discovery night(first night), uncertainties are large for both sets. However, it is only after the 10 th night thatthe difference D MPC - D
PRAIA drops permanently below 10 km. Since between the first and the10 th night span an arc of 26 days, there is a real advantage in consistent reduction regarding theposition uncertainty propagation of follow up campaigns.2 Position uncertainty [km]
Night number D
MPC D PRAIA D MPC -D PRAIA
Fig.
Geocentric position uncertainty evolution as a function of the number of observation nights forthe duplicated measurement. The difference between the sets D
MPC - D
PRAIA is also indicated
We will now proceed to study whether orbits and initial uncertainties constructed fromdifferent sets of observations can cause a significant change in the propagated uncertainties ofApophis’ orbit. The process then works as follows. After an initial orbit determination, an orbitadjustment based on a differential correction is performed. This results in the uncertainties of theasteroids orbit in form of an orbital element covariance matrix. The resulting uncertainties canthen be propagated to the 2029 b-plane and its long axis was used to indicate the 1 σ uncertaintyvalue. A quick first check can be performed using the duplicated measurement sets D MPC andD
PRAIA . The propagated uncertainty with D
PRAIA improves the 1 σ uncertainty obtaines withD MPC by ∼
14% which is non negligible for the impact probability assessment with short arcdata.
Our aim is to investigate whether the consistent data produced during the Gaia-FUN-SSOcampaign can impact orbital solutions and b-plane uncertainties through the example of Apo-phis. To this end we compare orbits and uncertainties derived from five observational data sets:– S = [2004-2014] MPC + radar– S = [2004-2014] MPC - D
MPC + D
PRAIA + radar– S = S + S NEW – S = S + S NEW – S = S NEW + D
PRAIA + radarwhere [2004-2014]
MPC refers to the 4138 optical data as present in the MPC database. Wepropagated each nominal orbit resulting from the individual sets of observations together withits covariances up to 2029 where we evaluated the position uncertainties projected onto theb-plane. Table 1 summarizes the quality of the orbital fit and the 2029 b-plane uncertaintyresulting from the orbit propagation. The presented results suggests the sets containing D
PRAIA instead of D
MPC result in smaller uncertainties in Apophis’ positions in the 2029 b-plane. Indeed,even for a well-known orbit (with a 10-years arc data length), both optical and radar χ valuesshow better results when D PRAIA measurements are used. Hence, we speculate that currentorbit solutions of NEAs can be improved using consistent data. Furthermore, consistent datareduction with a good astrometric catalog can also result in smaller uncertainties in the b-plane3 ab.
Orbital accuracy information – fit residuals and b-plane uncertainty – computed with differentsets of observations. We also computed the difference in b-plane distance ∆ i for each set withrespect to the distance ∆ obtained from S χ opt χ rad σ ξ ∆ i - ∆ [km] [km]S ) suffice to produce b-plane uncertainty valuesthat are very close to those sets that contain all available observations. A large amount of astrometric data was collected during the latest period of observabilityof Apophis in 2012-2013 and processed in a homogeneous fashion using the PRAIA reductionsoftware and the UCAC4 catalog data. Using the 629 duplicated data from the 2732 preciseastrometric measurements provided by 19 observatories, we could show that the recovery processof new objects when their observational data arcs span less than one night won’t be impact whenconsidering MPC or PRAIA data. However, a consistent data reduction of a newly discoveredasteroids during this observation campaign would have led to a greater reduction of NEO positionuncertainties. Finally, the example of Apophis reveals that, even for well-known orbits, the useof consistent data can improve the current χ of both optical and radar data. R´ef´erences
M. Assafin, R. Vieira Martins, J. I. B. Camargo, A. H. Andrei, D. N. Da Silva Neto, andF. Braga-Ribas. PRAIA - Platform for Reduction of Astronomical Images Automatically. InP. Tanga and W. Thuillot, editors,
Gaia follow-up network for the solar system objects : GaiaFUN-SSO workshop proceedings, held at IMCCE -Paris Observatory, France, November 29 -December 1, 2010 / edited by Paolo Tanga, William Thuillot.- ISBN 2-910015-63-7, p. 85-88 ,June 2011.D. Bancelin, D. Hestroffer, and W. Thuillot. Dynamics of asteroids and near-Earth objects fromGaia astrometry.
Planet. Space Sci. , 73, December 2012.W. Thuillot. Objectives and Management of the Gaia-FUN-SSO Network. In P. Tanga andW. Thuillot, editors,