Abstract
The conventional least-squares asteroid mass determination algorithm allows us to solve for the mass of a large subject asteroid that is perturbing the trajectory of a smaller test asteroid. However, this algorithm is necessarily a first approximation, ignoring the possibility that the subject asteroid may itself be perturbed by the test asteroid, or that the encounter's precise geometry may be entangled with encounters involving other asteroids. After reviewing the conventional algorithm, we use it to calculate the masses of 30 main-belt asteroids. Compared to our previous results, we find new mass estimates for eight asteroids (11 Parthenope, 27 Euterpe, 51 Neimausa, 76 Freia, 121 Hermione, 324 Bamberga, 476 Hedwig, and 532 Herculina) and significantly more precise estimates for six others (2 Pallas, 3 Juno, 4 Vesta, 9 Metis, 16 Psyche, and 88 Thisbe). However, we also find that the conventional algorithm yields questionable results in several gravitationally coupled cases. To address such cases, we describe a new algorithm that allows the epoch state vectors of the subject asteroids to be included as solve-for parameters, allowing for the simultaneous solution of the masses and epoch state vectors of multiple subject and test asteroids. We then apply this algorithm to the same 30 main-belt asteroids and conclude that mass determinations resulting from current and future high-precision astrometric sources (such as Gaia) should conduct a thorough search for possible gravitational couplings and account for their effects.
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1. Introduction
In its most basic form (see Sitarski & Todorovic-Juchniewicz 1992 for a more global implementation), astrometric mass determination is a modification of conventional least-squares orbit determination, applied to relatively close encounters between a single large subject asteroid and a single small test asteroid, where precise observations of the test asteroid exist both before and after the encounter. The subject asteroid gravitationally perturbs the trajectory of the test asteroid, and the least-squares solution yields both the epoch state vector of the test asteroid and the mass of the perturbing subject asteroid.
In practice, it is often possible to identify more than one test asteroid that is perturbed by the same large subject asteroid. The least-squares solutions for each such test asteroid yield different masses (and uncertainties); typically, these are combined through a weighted average (as in Viateau & Rapaport 1998, Michalak 2000, and Baer & Chesley 2008).
As noted by Michalak (2001), however, this approach is only a first approximation. It implicitly assumes that each encounter is isolated, and that the subject and test asteroid epoch state vectors are independent of the detailed geometry of any other encounter. This approach also assumes that the mass of the perturbed asteroid is significantly smaller than that of the perturber, thus making it possible to ignore perturbations in the orbit of the subject asteroid due to the test body. While these assumptions hold true in many cases, we will see that there are several important instances in which mutual perturbations and intervening encounters cannot be ignored.
To address these concerns, we implemented a least-squares algorithm that allows the epoch state vector(s) of the subject asteroid(s) to be included as solve-for parameters. Specifically, the algorithm allows for the simultaneous solution of the best-fit masses and epoch state vectors of multiple subject and test bodies, minimizing the rms residuals over the full observation set of all bodies in the solution.
After presenting the conventional algorithm, we use it to calculate masses for 30 main-belt asteroids and find that it yields questionable results for several gravitationally coupled cases. We then introduce the simultaneous algorithm, review its results for these same 30 asteroids, and assess when it should be utilized.
2. The Least-squares Solution
The least-squares orbit determination algorithm relies upon finding the minimum of the cost function
where b(x) is an vector containing the "observed–computed" residuals for each observation, and Λ is the n × n observational covariance matrix. Here, is the total number of data points, and x is the 6 × 1 epoch state vector to be estimated. The elements of Λ can be written as
where is the square root of the covariance (i.e., the uncertainty) of the ith observation, and rij is the correlation between the ith and jth observations.
We would find the minimum by seeking stationary points of Q(x): according to
If we define the "design" matrix , then the equation to be solved reduces to
Assuming that the a priori epoch state vector is close to the optimal solution, the problem can be linearized, and the solution is obtained by iteratively applying a differential correction to x
until convergence.
3. The Conventional Algorithm
In adapting these ideas for astrometric mass determination, the mass of the perturbing subject asteroid is added as a seventh solve-for parameter in the epoch state vector x; otherwise, the principles are identical. To reduce the computational cost, we use a single-sided finite difference algorithm to compute A. Thus, we integrate seven variant trajectories by adding small increments to the nominal epoch state vector and mass. Specifically, we increment each state vector component by , and the mass by , these percentages being determined through trial and error testing of convergence and rms observational error. Noting the resulting change in the predicted R.A. and decl. compared to the nominal trajectory, we use the numerical approximation .
The least-squares solution begins with an a priori epoch state vector from the Minor Planet Center's MPCORB file (Holman 2015). In the initial stage of the iterative loop, all available optical and radar observations of the test asteroid are used. After the first iteration, we compute residuals and begin evaluating the value of each optical observation
where α represents R.A., δ represents decl., the subscripts "o" and "c" refer to "observed" and "calculated" (or predicted) values, and σ is the square root of the covariance (i.e., the uncertainty) in each observation. Optical observations with are excluded (using the outlier rejection strategy described in Carpino et al. 2003), and a new solution is calculated, with the process being repeated until successive epoch state vector solutions converge; in each successive solution, every observation is considered for inclusion, even if it had been excluded in the prior solution. (Note: only four radar observations exist for the asteroids whose masses were calculated. These four delay observations of 7 Iris, 253 Mathilde, and 324 Bamberga were retained in each iteration of their respective solutions and were not used to test for convergence.)
In our orbit and mass determinations, we do not directly solve the least-squares normal equation
Instead, we utilize the computationally efficient Square Root Information Filtering (SRIF) algorithm (Bierman 1974). However, the SRIF algorithm assumes that the observational covariance matrix Λ is diagonal, and as the observational error model (see Section 3.1) often assumes that the errors between closely spaced observations made by the same observatory have non-zero correlations, Λ is not generally diagonal. Therefore, some preparatory work is necessary before the SRIF algorithm can be applied.
If the observational noise is represented by ν, then we have
where (utilizing the statistical expectation operator)
and Λ, the observational covariance matrix, is positive definite.
We use the outer product Cholesky Square Root algorithm (Golub & Van Loan 1989) to find a matrix G such that . Then, if we pre-multiply Equation (8) by G, we have
If we define , , and , our equation becomes
and we have
as desired.
Next, applying the SRIF algorithm, we use a sequence of Givens rotations (Golub & Van Loan 1989) to construct an orthogonal transformation T such that is upper triangular. We define the matrix R to be the upper 6 × 6 portion of (if we are also solving for the mass of a perturbing subject asteroid, then R is the upper 7 × 7 portion of ). Then if z is a column vector consisting of the first six elements of (first seven elements for mass determination), we have the solution
with covariance
3.1. Preparation and Encounter Selection
The orbit and mass determinations were made using a modified version of the CODES application (Baer 2004), whose integration force model accounts for gravitational perturbations (including first-order relativistic terms), the J2 oblateness terms of the Sun, Earth, and Jupiter, and solar radiation pressure. In calculating gravitational perturbations, CODES uses the JPL DE430 ephemeris, which provides precise positions of the Sun, planets, and Earth's Moon for the period 1550–2650 (Folkner et al. 2014).
All calculations were based upon the 121, 612, 902 observations of the 437, 832 numbered asteroids in the Minor Planet Center's database as of 2015 June 2. Only observations of numbered asteroids were used, so as to ensure that the orbits were sufficiently well-established that residuals were dominated by observational error. Star catalog biases were removed from the optical observations using the algorithm described in Farnocchia et al. (2015).
Our first step was to create an updated observational error model. Specifically, as described in Baer et al. (2011b), we used the conventional least-squares orbit determination algorithm to calculate the orbits of the numbered minor planets, initially assuming that the observational errors were uncorrelated, with canonical uncertainties of 3 arcsec for optical observations prior to 1890, 2 arcsec for observations from 1890 to 1950, 1 arcsec for observations from 1950 to 2000, and 0.5 arcsec for observations after 2000. As a by-product of the orbit determination process, we obtained the "observed–predicted" observational residuals. These residuals were then binned, based on observatory, observation date (each bin initially being 50 days wide), apparent magnitude, location within the galactic disk, and detector technology, and used to create a statistical analysis of the demonstrated performance of each observatory, including the rms residuals in R.A. and decl. for each bin, and the correlations between closely spaced observations. In the later orbit and mass determinations, this statistical error model would allow us to assign uncertainties in R.A. and decl., and model correlations in the errors of closely spaced observations; as a result, we were able to populate the least-squares observational covariance matrix with realistic values.
Next, we used the new observational error model to recalculate the orbits of the 300 large asteroids that appeared in the JPL DE405 planetary ephemeris due to their potential perturbations of the orbits of the major planets (Standish 1998). These newly recalculated epoch state vectors were then integrated over the timespan 1800–2200, with mutual perturbations modeled using the best available published and estimated masses of the 300 asteroids. The resulting BC430 asteroid ephemeris, combined with the DE430 planetary ephemeris, helped improve our gravitational force model for subsequent calculations.
Potential mass determination encounters were identified using Opik's two-body analysis of planetary encounters, as developed by Carusi et al. (1990) and Valsecchi et al. (2003). As noted by Hilton (2002), the magnitude of the ballistic deflection angle (which is proportional to the mass of the subject asteroid and inversely proportional to the relative encounter velocity and the minimum distance) is often used to select candidate encounters. However, while finding encounters with significant deflections is clearly useful, our experience has demonstrated that relying solely upon the magnitude of the deflection angle is insufficient. Indeed, a significant deflection perpendicular to the orbit plane may not yield observable shifts in sky position near the ascending and descending nodes, while a relatively small along-track deflection may yield an easily observable shift if the observational baseline is sufficient. Therefore, we also calculated the predicted change in mean motion (see Galád 2001 for a similar approach). Combined with the elapsed time since the encounter, this allowed us to estimate the along-track deflection, and thus the predicted change in observed sky position.
Given the need to analyze the mutual encounters between over 440,000 numbered asteroids, we limited consideration to those encounters between a single subject asteroid and a single test asteroid with a relative Minimum Orbital Intersection Distance of 0.05 au or less. This threshold was a trade-off between completeness and processing time; although an exceptionally small relative velocity could yield an observable deflection at a greater distance, such an encounter would have a lengthy duration, thus making it more likely that any signal would be swamped by perturbations from other nearby asteroids. Additionally, we limited the selection to encounters that were within the period of observation of the test asteroid and that resulted in a predicted deflection angle, predicted change in inclination, or predicted change in sky position (accumulated over the test asteroid's period of observation) exceeding 0.1 arcsec, any smaller changes likely being unobservable by current technology. In total, over 31,000 candidate events were identified.
However, many subject/test asteroid pairs had multiple encounters over their shared observation timeframe; as a single mass determination solution applies to every such encounter, redundant events were eliminated. Moreover, the majority of events were due to perturbations by 1 Ceres, 4 Vesta, and 10 Hygiea; after retaining only the most promising such cases, the list was reduced to approximately 5700 candidate subject/test pairs.
3.2. Conventional Algorithm Results and Interpretation
Each of the remaining 5700 candidate pairs was processed by the conventional mass determination algorithm. Approximately 4400 cases were rejected based on their low significance (defined as the ratio of the calculated mass to its uncertainty), while approximately 700 others had unrealistic densities. Finally, only the solutions for 1 Ceres, 4 Vesta, and 10 Hygiea with the highest significances were retained. This yielded 242 solutions with an estimated density between 0.5 and 8.0 g per cubic centimeter and a significance greater than 2.0. (Note: We recognize there are non-trivial uncertainties in the dimensions of most main-belt asteroids. Even so, we feel these uncertainties are unlikely to justify retaining cases where the implied density exceeds 8.0 g per cubic centimeter.)
To further assess the validity of each mass solution, we conducted a variational analysis, repeating the runs with slightly different values for the masses of eight key perturbing bodies (Mars, Jupiter, Saturn, 1 Ceres, 2 Pallas, 3 Juno, 4 Vesta, and 10 Hygiea). In each case, the perturber mass was increased by the magnitude of its published uncertainty, and the resulting variant mass of the subject asteroid was compared to that from the nominal solution to determine if that mass was reliable. In a final validation test, the assumed mass of the subject asteroid used in the first iteration of the least-squares algorithm was cut in half, to assess the sensitivity of the final mass to the initially assumed value.
In all, this variational analysis yielded the 228 valid mass determinations for 30 large subject asteroids listed in Table 1 and illustrated in Figures 1–3. For each subject asteroid, we have illustrated the best-fit mass and uncertainty resulting from each separate test asteroid solution; and in cases where more than one test asteroid exists, the weighted average mass and uncertainty are calculated.
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Subject | Test | Mass | std dev | rms Error | |
---|---|---|---|---|---|
Asteroid | Asteroid | () | () | (arcsec) | Significance |
1 | 5303 | 4.73 × 10−10 | 1.47 × 10−12 | 0.452 | 323.2 |
1 | 79083 | 4.71 × 10−10 | 1.53 × 10−12 | 0.552 | 308.1 |
1 | 348 | 4.68 × 10−10 | 1.59 × 10−12 | 0.406 | 294.8 |
1 | 46938 | 4.69 × 10−10 | 1.64 × 10−12 | 0.490 | 285.2 |
1 | 13801 | 4.76 × 10−10 | 1.83 × 10−12 | 0.452 | 259.9 |
1 | 60592 | 4.76 × 10−10 | 1.85 × 10−12 | 0.477 | 256.9 |
1 | 85128 | 4.73 × 10−10 | 2.75 × 10−12 | 0.454 | 172.4 |
1 | 454 | 4.51 × 10−10 | 2.68 × 10−12 | 0.473 | 168.1 |
1 | 203 | 4.68 × 10−10 | 2.86 × 10−12 | 0.502 | 163.9 |
1 | 79000 | 4.74 × 10−10 | 3.33 × 10−12 | 0.455 | 142.5 |
Only a portion of this table is shown here to demonstrate its form and content. A machine-readable version of the full table is available.
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In comparison to our previous work (Baer et al. 2011a), Figures 1–3 contain new mass estimates for eight asteroids (11 Parthenope, 27 Euterpe, 51 Neimausa, 76 Freia, 121 Hermione, 324 Bamberga, 476 Hedwig, and 532 Herculina) and significantly more precise mass estimates for six others (2 Pallas, 3 Juno, 4 Vesta, 9 Metis, 16 Psyche, and 88 Thisbe). These improvements are likely the result of several factors, including improved star catalog debiasing (Farnocchia et al. 2015), the flood of highly precise astrometric observations from modern surveys like Pan-STARRS, and the addition of almost 400,000 more numbered asteroids to the pool of potential test asteroids.
We first note that the weighted average mass for 4 Vesta () differs from the definitive value () obtained by the Dawn space mission (Russell et al. 2012) by approximately (calculated using this paper's uncertainty). This is clearly unacceptable, and suggests that something is amiss. Next, we point out the significant disagreement in the individual masses for 6 Hebe. Specifically, the mass estimates for test asteroids 136568 () and 1700 () differ from one another by approximately (based upon the weighted mass uncertainty), despite the two mass estimates having nearly identical significance. The other mass estimates continue this same pattern, clustering around two distinct values, such that the weighted average uncertainty is unrealistically smaller than the variation in the individual mass estimates themselves. Significant disagreements can also be found in the individual mass estimates for 7 Iris, 9 Metis, 11 Parthenope, 20 Massalia, 29 Amphitrite, 39 Laetitia, 52 Europa, 88 Thisbe, and 511 Davida.
A potential explanation emerges from a review of our two-body encounter modeling, which shows that the large asteroids 7 Iris and 88 Thisbe actually encountered one another eight times within the observational baseline (see Table 2). These eight encounters yielded a mass for 88 Thisbe of high significance, implying that 7 Iris was significantly perturbed by the cumulative encounters; and because 7 Iris and 88 Thisbe are of similar size, it is likely that 88 Thisbe was also significantly perturbed by these encounters.
Table 2. Gravitationally Coupled Mass Determination Events
Relative | |||||
---|---|---|---|---|---|
Subject | Test | MOID | Distance | Speed | |
Asteroid | Asteroid | (au) | Event Date | (au) | (km s−1) |
88 | 7 | 0.01696 | 1879 Apr 15 | 0.04537 | 4.542 |
88 | 7 | 0.01696 | 1897 Sep 14 | 0.02959 | 4.672 |
88 | 7 | 0.01696 | 1916 Feb 15 | 0.02088 | 4.762 |
88 | 7 | 0.01696 | 1934 Jul 23 | 0.01748 | 4.868 |
88 | 7 | 0.01696 | 1952 Dec 27 | 0.01705 | 4.874 |
88 | 7 | 0.01696 | 1971 May 31 | 0.01965 | 4.963 |
88 | 7 | 0.01696 | 1989 Nov 5 | 0.04695 | 5.137 |
88 | 7 | 0.01696 | 2008 Apr 14 | 0.03526 | 5.056 |
51 | 6 | 0.02250 | 1981 Apr 14 | 0.06923 | 6.462 |
39 | 29 | 0.02236 | 1872 May 25 | 0.00878 | 5.660 |
39 | 52 | 0.01378 | 1875 Feb 13 | 0.02679 | 2.807 |
511 | 532 | 0.00016 | 1963 Apr 3 | 0.03050 | 4.234 |
11 | 17 | 0.00027 | 1968 Feb 18 | 0.00162 | 2.296 |
4 | 17 | 0.00635 | 1996 Jun 16 | 0.01938 | 1.181 |
11 | 17 | 0.00027 | 1997 Jan 3 | 0.00536 | 2.358 |
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Both 7 Iris and 88 Thisbe are included in the gravitational force model. However, their masses and epoch state vectors were determined sequentially. That is, our previously published masses were used to calculate their epoch state vectors and BC430 ephemerides; and the resulting BC430 ephemeris was then used to model the perturbations in calculating the new weighted average masses in Table 1. No attempt was made to simultaneously solve for the combination of epoch state vectors and masses that minimized the rms errors over the full observational data set. Indeed, many of the encounters that 7 Iris and 88 Thisbe experienced with their individual test asteroids lay within the same 1879–2008 timeframe as their encounters with one another; so if the trajectories of 7 Iris and 88 Thisbe were sub-optimal, the resulting test asteroid deflection geometries might also be modeled imperfectly, thus explaining the puzzlingly inconsistent mass estimates.
In general, we would describe two or more subject asteroids (like 7 Iris and 88 Thisbe) as being gravitationally coupled if their mutual perturbations alter the subsequent encounter geometries with their own test asteroids. Inconsistencies in their individual mass determinations may be a signature, suggesting the need for a simultaneous least-squares orbit/mass solution involving as many of the subject and test asteroids as feasible, in which the epoch state vectors of the subject asteroids would be included as solve-for parameters.
A review of our two-body encounter modeling also showed that 6 Hebe passed within 0.069 au of 51 Nemausa in 1981. Although 51 Nemausa is only about one-third the mass of 6 Hebe, given the long observational baseline of each asteroid, we suspected that 6 Hebe might have been sufficiently perturbed by the encounter that the geometries of subsequent test asteroid encounters may not have been modeled with adequate precision. Similar remarks apply to asteroids 29 Amphitrite, 39 Laetitia, and 52 Europa, as well as to asteroids 511 Davida and 532 Herculina.
Finally, both 4 Vesta and 11 Parthenope experienced close encounters with 17 Thetis that yielded masses of high significance, suggesting that 17 Thetis was significantly perturbed by each encounter. Specifically, Table 2 shows that 11 Parthenope and 17 Thetis passed within 0.0016 au in 1968; 17 Thetis subsequently passed within 0.0194 au of 4 Vesta in 1996 June and then passed within 0.0054 au of 11 Parthenope seven months later. Additionally, the orbits of 11 Parthenope and 17 Thetis are near 1:1 resonance, which may further enhance their mutual perturbations. Thus, the trajectories of these three large asteroids appear entangled, and given the poor agreement of 4 Vesta's weighted average mass with the Dawn space mission value, as well as the significant variation in calculated masses for 11 Parthenope, we felt that a simultaneous least-squares orbit/mass determination involving all three asteroids was likely needed.
4. The Simultaneous Algorithm
The simultaneous algorithm is designed to solve for the best-fit epoch state vectors of N1 test asteroids, the best-fit masses and epoch state vectors of N2 subject/test asteroids, and the best-fit masses of N3 subject asteroids, by minimizing the rms residuals of the astrometric observations of the test and subject/test asteroids. In general, we obviously try to include as many test asteroids as possible. As will be seen, however, as more asteroids (and thus astrometric observations) are added to the solution, the processing time increases dramatically; so the selection of test asteroids must be judicious.
At the start of the simultaneous algorithm, the nominal trajectories of the subject/test and subject asteroids (modeled using their a priori masses) are taken from the BC430 asteroid ephemeris. The astrometric observations of the test and subject/test asteroids are arranged chronologically, from earliest to most recent; and the a priori masses and epoch state vectors are used to calculate the nominal residual vector b.
We then begin an iterative loop to refine the epoch state vectors and masses. Any optical observations with are excluded from the current iteration (although they may be reconsidered for inclusion in subsequent iterations).
For each of the test and subject/test asteroids, single-sided finite difference partial derivatives were used to obtain the entries of , as described in Section 3.
Similarly, for each of the subject/test and subject asteroids, a small increment is added to the a priori mass. The BC430 ephemerides of these asteroids are then recalculated, and the resulting ephemeris is used to calculate variant residuals for the observations of each test and subject/test asteroid. The differences between the nominal and variant residuals, divided by the added mass increment, are then used to populate the corresponding entries of , which therefore has columns and rows. Here, ni is the number of measurements to be fit for the ith object.
The simultaneous algorithm then utilizes the observational error model to populate Λ and solves for corrections to the epoch state vectors and masses using the Cholesky Square Root and SRIF algorithms, as described in Section 3 for the conventional case. Once the new epoch state vectors and masses have been obtained, the nominal residuals are recalculated. If the rms residuals have not converged, the loop is repeated.
In practice, we have found that the Cholesky algorithm sometimes fails. As detailed in Baer et al. (2011b), the error model's use of estimated pairwise correlations, also known as polychoric correlations, can lead to non-positive definite covariance matrices, because the correlations are not obtained en masse, and therefore may not be statistically consistent. A straightforward (if numerically brutal) solution is to multiply all of the off-diagonal elements of the covariance matrix by 0.9; this procedure is repeated until the covariance matrix is positive definite, and the Cholesky algorithm converges. Consequently, for cases involving large numbers of observations and test asteroids, the total processing time is dominated by the Cholesky Square Root algorithm; specifically, the number of operations required is proportional to . Numbered asteroids frequently have a great many observations; so while we would obviously like to include as many test asteroids as possible in the simultaneous solution, we are compelled to only select those with relatively high significances. This restriction is unfortunate, but our numerical studies demonstrate that omitting the correlations between closely spaced observations made by the same observatory can result in changes to the resulting masses.
If the algorithm produces a mass estimate with a significance greater than two and an estimated density between 0.5 and 8.0 g per cubic centimeter, the same validation procedure described in Section 3.2 is utilized to determine if it is reliable.
4.1. Results
Our mass determinations using the simultaneous algorithm are presented in Table 3, along with the corresponding weighted averages from the conventional algorithm. We calculated simultaneous mass estimates for each subject asteroid in Figures 1–3, utilizing as many test asteroids as possible in each solution. In some instances, additional solutions were run in which the subject asteroid was instead a subject/test asteroid, so that we could evaluate the extent to which including its epoch state vector as a solve-for parameter impacted its mass estimate.
Table 3. Conventional vs. Simultaneous Mass Determinations
Measured | Mass | ||||
---|---|---|---|---|---|
Subject | Mass | Uncertainty | |||
Asteroid | Method | (in ) | (in ) | Difference | Test Asteroids |
1 | Mean | 4.718 × 10−10 | 6.66 × 10−13 | 5303, 79083, 348, 46938, 13801, 60592, 85128, 454, | |
203, 79000, 91, 23352, 73504, 70051, 44867, 58 | |||||
1 | Simult. | 4.724 × 10−10 | 6.6 × 10−13 | 0.69σ | 5303, 79083, 348, 46938, 13801, 60592 |
2 | Mean | 1.06 × 10−10 | 3.26 × 10−12 | 106329, 582, 36741, 48343, 66300, 69508, 4971, | |
16527, 52863, 18067, 5634, 5930, 3131, 381606, | |||||
102850, 1391, 84676, 131629, 124006, 241751, 24314, | |||||
44087, 2505, 5019, 66875 | |||||
2 | Simult. | 1.05 × 10−10 | 4.25 × 10−12 | 0.23σ | 106329, 582, 36741, 48343, 66300, 69508, 4971, |
16527, 52863 | |||||
3 | Mean | 1.41 × 10−11 | 8.71 × 10−13 | 7201, 960, 64587, 61235, 20199, 12614, 17715, | |
61232, 10383 | |||||
3 | Simult. | 1.61 × 10−11 | 1.17 × 10−12 | 1.35σ | 7201, 960, 64587, 61235, 20199, 12614, 17715, |
61232, 10383 | |||||
4 | Mean | 1.322 × 10−10 | 2.36 × 10−13 | 17, 197, 8331, 125655, 5205, 67, 56483, 6333, 408741, | |
77, 234504, 486, 234479, 157127, 33427, 112237, 3057, | |||||
109, 6027 | |||||
4 | Simult. | 1.291 × 10−10 | 6.54 × 10−13 | 4.40σ | 197, 8331, 125655, 5205, 67, 56483 |
4 | Simult. | 1.300 × 10−10 | 3.46 × 10−13 | 5.24σ | 4*, 11*, 17* |
6 | Mean | 7.09 × 10−12 | 7.15 × 10−13 | 136568, 1700, 5295, 13152, 4497, 1150 | |
6 | Simult. | 6.26 × 10−12 | 3.46 × 10−13 | 1.04σ | 6*, 136568, 1700, 5295, 13152 |
6 | Simult. | 6.14 × 10−12 | 2.19 × 10−13 | 1.27σ | 136568, 1700, 5295, 13152, 4497, 1150 |
6 | Simult. | 5.98 × 10−12 | 4.00 × 10−13 | 1.36σ | 6*, 51*, 136568, 1700, 287 |
7 | Mean | 8.34 × 10−12 | 4.17 × 10−13 | 571, 52443, 1188, 46529, 17186, 6791, 1879, 56, | |
273287, 253028, 836, 1651, 269649 | |||||
7 | Simult. | 8.28 × 10−12 | 4.64 × 10−13 | 0.10σ | 571, 52443, 1188, 46529, 17186 |
7 | Simult. | 8.38 × 10−12 | 6.00 × 10−13 | 0.04σ | 7*, 88*, 571, 52443, 7629 |
8 | Mean | 4.75 × 10−12 | 3.63 × 10−13 | 967, 330 | |
8 | Simult. | 5.04 × 10−12 | 4.82 × 10−13 | 0.48σ | 967, 330 |
9 | Mean | 3.91 × 10−12 | 3.24 × 10−13 | 36653, 29818, 343, 7365, 8232, 94355, 29663, 20 | |
9 | Simult. | 3.87 × 10−12 | 3.34 × 10−13 | 0.07σ | 36653, 29818, 343, 7365, 94355, 29663 |
10 | Mean | 4.38 × 10−11 | 6.95 × 10−13 | 3946, 24433, 192839, 15187, 6143, 11215, 283315, | |
75794, 111, 17109, 45496, 209, 230964, 10380, | |||||
492, 48499, 5941, 169965, 13266, 32086, 245317, | |||||
1287, 109507, 57493, 1259, 28872, 820, 22236, 55251, | |||||
20905, 2619, 2824, 579 | |||||
10 | Simult. | 4.12 × 10−11 | 8.13 × 10−13 | 2.40σ | 3946, 24433, 192839, 15187, 6143, 11215 |
11 | Mean | 2.40 × 10−12 | 7.37 × 10−14 | 17, 85371, 113, 153608, 8964 | |
11 | Simult. | 2.78 × 10−12 | 6.07 × 10−14 | 3.93σ | 4*, 11*, 17* |
11 | Simult. | 2.92 × 10−12 | 3.07 × 10−13 | 1.64σ | 85371, 113, 153608, 8964 |
15 | Mean | 1.53 × 10−11 | 2.56 × 10−13 | 411232, 50278, 1284, 14401, 19524, 48551, 16693, | |
136560, 1313, 45690 | |||||
15 | Simult. | 1.56 × 10−11 | 1.47 × 10−13 | 1.12σ | 411232, 50278, 1284, 14401 |
16 | Mean | 1.15 × 10−11 | 3.07 × 10−13 | 13206, 211012, 39054, 91495, 156553, 151878, 94, | |
62211 | |||||
16 | Simult. | 1.15 × 10−11 | 3.50 × 10−13 | 0.02σ | 13206, 211012, 39054 |
17 | Indiv. | 5.60 × 10−13 | 4.58 × 10−14 | 11 | |
17 | Simult. | 4.52 × 10−13 | 4.72 × 10−14 | 1.65σ | 4*, 11*, 17* |
19 | Mean | 5.53 × 10−12 | 2.79 × 10−13 | 135, 3486, 114525, 27799, 228485, 113990 | |
19 | Simult. | 5.54 × 10−12 | 3.18 × 10−13 | 0.02σ | 135, 3486, 114525 |
20 | Mean | 2.48 × 10−12 | 3.88 × 10−13 | 44, 60658, 49248, 253970, 3175 | |
20 | Simult. | 2.69 × 10−12 | 4.16 × 10−13 | 0.36σ | 44, 60658, 49248, 253970, 3175 |
27 | Indiv. | 2.17 × 10−12 | 6.08 × 10−13 | 63625 | |
27 | Simult. | 1.92 × 10−12 | 6.99 × 10−13 | 0.27σ | 63625 |
29 | Mean | 6.97 × 10−12 | 2.77 × 10−13 | 987, 6904, 43142, 77424, 359, 1551, 236858, 48350, | |
321197, 48464 | |||||
29 | Simult. | 7.10 × 10−12 | 3.07 × 10−13 | 0.31σ | 987, 6904, 43142, 77424, 359, 1551 |
29 | Simult. | 6.77 × 10−12 | 3.24 × 10−13 | 0.48σ | 29*, 39*, 52*, 124, 306, 987, 6904, 7060, 311771 |
39 | Mean | 4.58 × 10−12 | 1.09 × 10−12 | 7060, 311771 | |
39 | Simult. | 3.54 × 10−12 | 1.33 × 10−12 | 0.61σ | 7060, 311771 |
39 | Simult. | 4.30 × 10−12 | 9.30 × 10−13 | 0.20σ | 29*, 39*, 52*, 124, 306, 987, 6904, 7060, 311771 |
51 | Mean | 2.07 × 10−12 | 3.05 × 10−13 | 287, 53824, 33850 | |
51 | Simult. | 2.41 × 10−12 | 4.24 × 10−13 | 0.65σ | 287, 53824 |
51 | Simult. | 2.12 × 10−12 | 3.79 × 10−13 | 0.09σ | 6*, 51*, 136568, 1700, 287 |
52 | Mean | 1.53 × 10−11 | 7.80 × 10−13 | 124, 306, 1023, 993 | |
52 | Simult. | 1.46 × 10−11 | 7.88 × 10−13 | 0.60σ | 124, 306 |
52 | Simult. | 1.48 × 10−11 | 7.73 × 10−13 | 0.48σ | 52*, 124, 306 |
52 | Simult. | 1.45 × 10−11 | 7.80 × 10−13 | 0.69σ | 29*, 39*, 52*, 124, 306, 987, 6904, 7060, 311771 |
65 | Mean | 8.05 × 10−12 | 1.12 × 10−12 | 526, 70954, 1668, 226534 | |
65 | Simult. | 7.52 × 10−12 | 9.02 × 10−13 | 0.37σ | 65*, 526, 70954, 1668 |
65 | Simult. | 7.83 × 10−12 | 2.61 × 10−13 | 0.19σ | 526, 70954, 1668, 226534 |
76 | Indiv. | 2.13 × 10−12 | 7.50 × 10−13 | 10383 | |
76 | Simult. | 2.23 × 10−12 | 8.29 × 10−13 | 0.09σ | 10383 |
88 | Mean | 5.24 × 10−12 | 9.06 × 10−14 | 7, 7629, 142429, 11701 | |
88 | Simult. | 6.91 × 10−12 | 8.43 × 10−13 | 1.98σ | 7*, 88*, 571, 52443, 7629 |
121 | Mean | 2.73 × 10−12 | 4.89 × 10−13 | 278, 5750 | |
121 | Simult. | 2.78 × 10−12 | 5.25 × 10−13 | 0.07σ | 121*, 278, 5750 |
324 | Mean | 6.02 × 10−12 | 7.72 × 10−13 | 15402, 31560, 310585, 1939, 24553, 158472 | |
324 | Simult. | 7.00 × 10−12 | 4.25 × 10−13 | 1.11σ | 324*, 15402, 31560, 310585 |
324 | Simult. | 6.54 × 10−12 | 2.95 × 10−13 | 0.62σ | 324*, 15402, 310585 |
476 | Indiv. | 9.67 × 10−13 | 2.91 × 10−13 | 187901 | |
476 | Simult. | 9.30 × 10−13 | 1.96 × 10−13 | 0.10σ | 476*, 187901 |
511 | Mean | 2.19 × 10−11 | 1.15 × 10−12 | 1550, 532, 50529, 203, 17311, 55696, 508 | |
511 | Simult. | 1.81 × 10−11 | 1.09 × 10−12 | 2.38σ | 511*, 532*, 1550, 50529, 203, 191878, 17006 |
532 | Mean | 1.72 × 10−11 | 3.11 × 10−12 | 191878, 17006 | |
532 | Simult. | 1.62 × 10−11 | 1.80 × 10−12 | 0.29σ | 511*, 532*, 1550, 50529, 203, |
191878, 17006 | |||||
704 | Mean | 2.21 × 10−11 | 1.03 × 10−12 | 1467, 95, 10034, 48500, 7461, 253,8624, 242001, | |
43993, 340622, 101416,51293, 15856, 79476 | |||||
704 | Simult. | 2.20 × 10−11 | 1.19 × 10−12 | 0.06σ | 1467, 95, 10034, 48500, 7461, 253 |
804 | Indiv. | 2.53 × 10−12 | 6.21 × 10−13 | 1002 | |
804 | Simult. | 1.89 × 10−12 | 6.03 × 10−13 | 0.74σ | 804*, 1002 |
804 | Simult. | 1.90 × 10−12 | 6.04 × 10−13 | 0.73σ | 1002 |
Note. The differences in measured masses are for the simultaneous solution relative to the mean solution for the subject asteroid. The final column lists the test asteroids in each solution; those with asterisks were subject/test asteroids, which also had their masses included as solve-for parameters.
Most importantly, however, we also calculated simultaneous mass estimates for the gravitationally coupled cases noted in Table 2. Because our encounter analysis indicated that the subject asteroids perturbed one another, their masses and epoch state vectors were included as solve-for parameters, in addition to the epoch state vectors of the most sensitive test asteroids. As explained above, these cases were the most computationally challenging, and we were not always able to include as many test asteroids as desired.
For 14 of the 18 non-gravitationally coupled asteroids in Table 3, the simultaneous algorithm yielded masses that were within 1σ of the conventional weighted averages. Moreover, in two cases (asteroids 65 Cybele and 804 Hispania), adding the subject asteroid's epoch state vector as a solve-for parameter in the simultaneous solution yielded little apparent benefit. Indeed, in the case of 65 Cybele, adding the epoch state vector as a solve-for parameter more than tripled the mass uncertainty.
However, for 7 of the 12 asteroids in the gravitationally coupled groupings listed in Table 2 (asteroids 4 Vesta, 6 Hebe, 11 Parthenope, 17 Thetis, 88 Thisbe, and 511 Davida), the difference between the simultaneous and weighted average mass estimates was 1σ or greater. Without ground truth measurements of the actual masses of these asteroids, we are unable to conclude that the simultaneous solutions are uniformly superior. Nevertheless, as Table 4 illustrates for the 29-39-52 case, the value for each subject/test asteroid in the simultaneous solution is smaller, and the sum of for the test particles is markedly lower than for the conventional solution, indicating that the simultaneous solution for these three asteroids is more consistent with the observational data.
Table 4. Values for the Simultaneous and Conventional 29-39-52 Solutions
Asteroid | Simultaneous | Conventional | (Sim–Con) |
---|---|---|---|
29 | 2696.35 | 2697.14 | −0.79 |
39 | 6365.14 | 6366.86 | −1.72 |
52 | 3521.21 | 3521.28 | −0.06 |
124 | 4312.93 | 4288.24 | 24.69 |
306 | 3327.86 | 3484.94 | −157.08 |
987 | 2606.41 | 2530.30 | 76.11 |
6904 | 1145.77 | 1143.35 | 2.42 |
7060 | 2059.90 | 2373.24 | −313.34 |
311771 | 144.67 | 145.98 | −1.31 |
Download table as: ASCIITypeset image
We also believe it is significant that the simultaneous solution for the mass of 1 Ceres () matches the Dawn space mission value (Preusker et al. 2016) to better than , while the weighted conventional value is off by approximately . In this instance, the availability of high-precision ground truth appears to demonstrate the advantage of a true least-squares solution that minimizes the rms residuals over the observations of all asteroids in the solution, as compared to a simple weighted average.
In the case of 4 Vesta, two simultaneous solutions were performed. The first nearly duplicated the conventional solution, except that 17 Thetis was excluded as a test asteroid. By contrast, the second solution focused on the gravitational coupling between 4 Vesta, 11 Parthenope, and 17 Thetis, simultaneously solving for both the epoch state vector and mass of all three asteroids. Significantly, this 4-11-17 solution yielded a mass for 4 Vesta considerably closer (0.94σ) to the Dawn space mission value than either the weighted conventional value (9.58σ) or the first simultaneous estimate (1.81σ).
To summarize, the simultaneous mass determination algorithm appears to provide significant advantages over the conventional algorithm when asteroids are gravitationally coupled, or in cases where especially high precision is required.
5. Conclusion
As noted above, the conventional mass determination algorithm described in Section 3 has been understood to be a first approximation. Asteroids clearly interact with one another gravitationally; and it was only a matter of time before observational accuracy and precision improved to the point that these mutual perturbations could no longer be ignored.
We would therefore expect that, as the accuracy and precision of astrometric observations continue to improve, the effects of gravitational coupling will become evident for even smaller asteroids. This will be especially true for the Gaia mission, whose astrometric observations are expected to have a precision of 1.5 mas or better (Tanga et al. 2016). Indeed, a conceptually similar simultaneous algorithm has been used to model expected results from the Gaia mission (Mouret et al. 2007). Thus, any asteroid mass determination efforts based upon Gaia observations should include a thorough search for possible gravitational couplings and account for their effects.
Going forward, mass determinations will also require ever more accurate force and observational error models. In particular, orbit and mass solutions must be calculated based upon realistic observational uncertainties, ephemerides must include as many large asteroids as possible, and their integrated trajectories must account for even small perturbative forces. As a step toward this goal, the observational error model and BC430 asteroid ephemeris developed in this paper are offered for download.3
This research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.