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Subsections

  
3 Correlation with orbital parameters and size

In this section, we search for correlation between the color or reddening distributions and the orbital parameters, i.e. a, the semi-major axis, e, the eccentricity and i, the inclination. We also consider the "excitation'' $\cal E$ of an object's orbit, defined as

 \begin{displaymath}{\cal E} = \sqrt{e^2 + \sin^2(i)},
\end{displaymath} (9)

$\sin(i)$ is related to the object's velocity perpendicular to the ecliptic, and e to its radial velocity. Therefore, $\cal E$ is an estimate of the velocity of the object with respect to another object that would be at the same distance on a circular ecliptic orbit, it is therefore also related to the probability of collision, as well as the velocity of the impacts. The color vs. $\cal E$ plots therefore explore possible effect of collisions. The colors are also plotted as functions of M(1,1), the absolute magnitude (cf. Sect. 2.2 and Eq. (3)).

3.1 Plots

Figure 3 displays some of the color indexes and the reddening slope $\cal S$ as a function of the orbital parameters and absolute magnitude. In each figure, each object is represented using the symbol of its class (cf. Fig. 2). The complete set of diagrams is available on the MBOSS web site; only some examples are reproduced here.

Results:

  
3.2 Correlation

In order to quantify possible correlations between the colors (and gradient) and the various orbital elements and absolute magnitude, we computed the correlation coefficient for each "Color'' versus "orbital element'' distribution. The test itself is described in Appendix B. As a reminder, while the correlation coefficient indicates how strong the correlation is (large absolute values), there is no way to quantify the significance of that correlation. The correlation coefficients were computed for the complete MBOSS population (i.e. all objects) and for the Plutinos, Cubewanos and Centaurs/Scattered objects separately. The numerical results of the tests are listed in Table C.1.

Results:

3.3 Are there some more subtle effects

In order to test for more subtle effects than a simple correlation between the colors (or gradient) and the orbital elements (and M(1,1)), each population is divided in two sub-samples, i.e. the object having the considered element smaller than a given value, and those having that element larger. The boundary value is chosen as the median of the sample, i.e. to split the population in sub-samples of similar sizes. The median value is probably not the best choice on physical bases, but a physically better choice might lead to samples of fairly different sizes, which could cause asymmetry artifacts. The cut-off values are listed in Table C.1 with the results of the test described below.

The two samples are then compared using Student's t-test and f-test, which are described in Appendix B. In summary, small values of the probability associated to the t-test, indicate that both sub-populations have significantly different mean of the considered color (Prob is the probability that both subsumes are randomly drawn from a similar population), while small values of the probability associated to the f-test reveal that the sub-samples have different variances. Each test was performed on the whole MBOSS population and on the Plutinos and Cubewanos only. The numeric results of the tests and the cut values are listed in Appendix, in Table C.1.

Results: $\mathsfsl{t}$-test

Results: $\mathsfsl{f}$-test


 

 
Table 4: Average colors of the various classes of objects. For each color, the table lists the number of objects included in the statistics, as well as the average color and the square root of the corresponding variance (which is undefined and set to 0 in case only one object is available).
Color Plutinos Cubewanos Centaurs Scattered Comets
U-B 0 -- -- 1 1.000 $\pm$ 0.000 0 -- -- 1 0.970 $\pm$ 0.000 0 -- --
U-V 0 -- -- 1 1.720 $\pm$ 0.000 0 -- -- 1 1.710 $\pm$ 0.000 0 -- --
U-R 0 -- -- 1 2.120 $\pm$ 0.000 0 -- -- 1 2.150 $\pm$ 0.000 0 -- --
U-I 0 -- -- 1 2.500 $\pm$ 0.000 0 -- -- 1 2.410 $\pm$ 0.000 0 -- --
                     
B-V 20 0.886 $\pm$ 0.176 33 0.946 $\pm$ 0.185 15 0.930 $\pm$ 0.219 8 0.863 $\pm$ 0.126 2 0.795 $\pm$ 0.035
B-R 20 1.464 $\pm$ 0.261 30 1.561 $\pm$ 0.249 15 1.513 $\pm$ 0.349 8 1.376 $\pm$ 0.262 2 1.355 $\pm$ 0.064
B-I 17 1.977 $\pm$ 0.412 25 2.131 $\pm$ 0.329 14 2.119 $\pm$ 0.489 7 1.914 $\pm$ 0.412 2 1.860 $\pm$ 0.141
B-J 0 -- -- 0 -- -- 5 2.800 $\pm$ 0.807 0 -- -- 0 -- --
B-H 0 -- -- 0 -- -- 4 3.395 $\pm$ 0.679 0 -- -- 0 -- --
B-K 0 -- -- 0 -- -- 4 3.428 $\pm$ 0.623 0 -- -- 0 -- --
                     
V-R 20 0.580 $\pm$ 0.091 40 0.629 $\pm$ 0.132 15 0.590 $\pm$ 0.136 9 0.528 $\pm$ 0.116 13 0.430 $\pm$ 0.140
V-I 17 1.118 $\pm$ 0.239 30 1.206 $\pm$ 0.225 13 1.169 $\pm$ 0.270 9 1.031 $\pm$ 0.242 4 0.964 $\pm$ 0.136
V-J 4 2.345 $\pm$ 0.213 5 1.795 $\pm$ 0.495 6 1.801 $\pm$ 0.552 1 1.452 $\pm$ 0.000 0 -- --
V-H 0 -- -- 0 -- -- 5 2.245 $\pm$ 0.555 0 -- -- 0 -- --
V-K 0 -- -- 0 -- -- 5 2.299 $\pm$ 0.506 0 -- -- 0 -- --
                     
R-I 17 0.542 $\pm$ 0.161 30 0.613 $\pm$ 0.137 14 0.582 $\pm$ 0.134 9 0.509 $\pm$ 0.138 4 0.465 $\pm$ 0.066
R-J 0 -- -- 0 -- -- 6 1.243 $\pm$ 0.382 0 -- -- 0 -- --
R-H 0 -- -- 0 -- -- 5 1.658 $\pm$ 0.400 0 -- -- 0 -- --
R-K 0 -- -- 0 -- -- 5 1.695 $\pm$ 0.367 0 -- -- 0 -- --
                     
I-J 0 -- -- 0 -- -- 6 0.685 $\pm$ 0.233 0 -- -- 0 -- --
I-H 0 -- -- 0 -- -- 5 1.087 $\pm$ 0.234 0 -- -- 0 -- --
I-K 0 -- -- 0 -- -- 5 1.124 $\pm$ 0.209 0 -- -- 0 -- --
                     
J-H 2 0.800 $\pm$ 0.566 4 0.228 $\pm$ 0.355 5 0.340 $\pm$ 0.051 1 0.350 $\pm$ 0.000 0 -- --
J-K 1 0.360 $\pm$ 0.000 3 0.330 $\pm$ 0.234 5 0.383 $\pm$ 0.076 1 0.310 $\pm$ 0.000 0 -- --
H-K 1 -0.040 $\pm$ 0.000 3 0.243 $\pm$ 0.494 5 0.025 $\pm$ 0.083 1 -0.040 $\pm$ 0.000 0 -- --
                     
Grt (%/100 nm) 20 21.760 $\pm$ 12.305 35 26.537 $\pm$ 14.100 15 24.316 $\pm$ 15.086 9 16.948 $\pm$ 11.906 4 12.894 $\pm$ 7.192


  
3.4 Broadening of the $\mathsfsl{M(1,1)}$distributions?

As mentioned earlier, neutral-bluish objects could have their surface covered with fresh ice (resulting from a recent re-surfacing), or, on the contrary, with extremely ancient, extremely irradiated ice (with doses of 1010 erg cm-2), whose color is also expected to be neutral (cf. laboratory spectra published by Thompson et al. 1987). The albedo of the ancient ice is expected to be significantly lower than that of the fresh ice. On the other hand, very red objects are expected to be covered with highly irradiated ice (corresponding to the laboratory samples that received doses of 109 erg cm-2Thompson et al. 1987), and would have a much narrower range of albedo. If we assume that all these objects have a similar radius distribution, the resulting M(1,1) distribution should be significantly broader for the neutral objects than for the red ones (cf. Eq. (4)).

In order to test this hypothesis, we consider the M(1,1)distribution as function of the colors (i.e. the reverse of the previous section). We split the observed sample in two, i.e. those with colors redder than a limit, and the others. The cut-off value is set at the mid-point between the minimum and maximum values of the considered color. The average values of M(1,1) and their variances are computed for each sub-samples, and are compared using the f-test (cf. Sect. B), which evaluates whether the two variances are compatible. This test was performed for all the colors and the gradient distributions, for the complete MBOSS population, and for the Plutinos, Cubewanos and Centaurs/Scattered TNOs only. The numerical results of these tests are listed in Table C.2.

Results:

Combining this with the results of correlations (Sect. 3.2), it implies that the objects with a bighter M(1,1), i.e. the redder Plutinos and the bluer Cubewanos, cover a broader M(1,1) range than the fainter ones. This is an effect of the steep luminosity function: there are much fewer objects per unit magnitude brighter than the cut-off magnitude (therefore the sample covers a broad range of M), while the number of objects per unit magnitude is much larger for those fainter than the cut-off. As the samples have roughly the same size, the faint ones cover a smaller magnitude range than the bright ones.


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