Tag Archives: Observations

OSSOS discovered 838 Trans-Neptunian Objects

Hi there! Today I will tell you of the survey OSSOS, which I already mentioned in the past. This survey made systematic observations of the sky to detect Trans-Neptunian Objects (TNOs), between 2013 and 2017. It was indeed a success, since it tripled the number of known TNOs. Its results are presented in OSSOS. VII. 800+ Trans-Neptunian Objects — The complete Data Release, led by Michele Bannister. This study is published in The Astrophysical Journal Supplement Series.

Previous surveys

The Trans-Neptunian Objects orbit beyond the orbit of Neptune. As such, observing them is a challenge. Pluto was the only known of them from its discovery in 1930, to the discovery of (15760) Albion in 1992. We now know 1,142 Trans-Neptunian Objects, essentially due to 4 surveys. The most prolific of them is the last one, i.e. OSSOS, but a survey cannot exist without its precursors, which were

  1. Deep Ecliptic Survey (DES),
  2. Canada-France Ecliptic Plane Survey (CFEPS),
  3. Pan-STARRS1.
The Deep Ecliptic Survey (DES)

The Deep Ecliptic Survey has been operating between 1998 and 2003, using two 4-m telescopes of the National Optical Astronomy Observatory: the Mayall telescope at Kitt Peak Observatory (Arizona, USA), and the Blanco telescope at Cerro Tololo Inter-American Observatory (Chile). It discovered 382 TNOs, including some Centaurs, which actually orbit inner to the orbit of Neptune. It covered 550 square degrees with sensitivity of 22.5.

The Canada-France Ecliptic Plane Survey (CFEPS)

This survey operated between early 2003 and early 2007, at the Canada-France-Hawaii Telescope (Hawaii, USA). It covered 321 square degrees with sensitivity of 24.4, and permitted to classify 169 TNOs. By classifying, I do not mean only discover, but also know their orbits with enough accuracy to determine to which dynamical group they belong. I will go back on this point later, but my meaning is that observing an object once is definitely not enough. This survey was limited to the detection of objects with a small inclination with respect to the ecliptic plane, i.e. the orbit of the Earth.

It was then extended by the High Ecliptic Latitude (HiLat) component, which looked for objects with significant inclinations. It examined 701 square degrees of sky ranging from 12° to 85° ecliptic latitude and discovered 24 TNOs, with inclinations between 15° and 104° (from Petit et al., 2017, The Canada-France Ecliptic Plane Survey (CFEPS) — High-latitude component, The Astronomical Journal, 153:5.

The Pan-STARRS1 survey

The Panoramic Survey Telescope and Rapid Response System (Pan-STARRS1) survey operates from Haleakala Observatory, Hawaii, USA since 2010. It is not specifically devoted for TNOs, but for moving objects (asteroids, stars,…), and is particularly known for the discovery of the first known interstellar object, i.e. 1I/’Oumuamua. It discovered 370 new TNOs, but without enough information to securely classify their orbits.

And now comes OSSOS!

The Outer Solar System Origins Survey (OSSOS)

OSSOS operated between 2013 and 2017 from the Canada-France-Hawaii Telescope, taking more than 8,000 images. It covered 155 square degrees with a sensitivity up to 25.2. This coverage has been split into 8 blocks, which avoided the Galactic plane. The study I present today is the complete data release, in which 838 objects are given without ambiguity on their orbital classification. This was an international collaboration, involving Canada, UK, France, Taiwan, USA, Finland, Japan, Slovakia,… but also involving different skills, like orbital characterization, astrometry, chemistry, cometary activity, data mining, etc. In other words, it not only aimed at discovering new objects, but also at understanding their orbital dynamics, their physics, and if possible their origin.

In the previous paragraphs I pointed out the difference between discovering an object, and classifying it following its orbit. Let us see that now.

Characterizing a new TNO

As we will see in the next paragraph, the Trans-Neptunian population is composed of different parts, following the orbits of the objects and the perturbations acting on them, i.e. the gravitational attraction of the giant planets. Classifying a newly discovered object requires some accuracy in the determination of its orbit. The following is a summary of how things work.

For an object to be discovered, it must appear on a triplet of images, which cover a timespan of about 2 hours. From it the relative motion of the object on the sky can be evaluated, which would permit to reobserve it. The new observations permit themselves to better constrain the orbit. The OSSOS team announces that an arc of observations of about 16 months is required to have enough confidence in the orbit. In many cases the arc is longer, actually the team tells us that for the 838 classified objects, astrometric measurements have been made over 2 to 5 oppositions. An opposition is the geometric alignment between the Sun, the Earth, and the object.

For an astrometric measurement to be accurate, you need to accurately know the positions of the other objects present on the image. These other objects are stars, which are referenced in astrometric catalogues. The astrometric satellite Gaia is currently performing such a survey. Its Data Release 2 has very recently (April 2018) been released, but this was too late for the present study. So, the authors used the Data Release 1, and the Pan-STARRS 1 catalogue when necessary.

In some cases, objects were lost, i.e. the authors were not able to reobserve it. This may have been due to the lack of accuracy of the orbital determination from the discovery arc, or just because the object left a covered zone.

Before giving you the results, I should tell you something on the structure of the outer Solar System. I mentioned orbital classification above, the classes are coming now.

Structure of the outer Solar System

First, we should make a distinction between resonant and non-resonant orbits.

Resonant orbits are in mean-motion resonance with a planet, which is mostly Neptune. For instance, the 2:1 resonance with Neptune means that Neptune accomplishes two revolutions around the Sun while the object makes exactly one. Such a ratio implies amplified dynamical effects on the object, which may excite its eccentricity or its inclination, destabilize or confine its orbit.

Besides these resonant objects are the non-resonant ones (you guessed it, didn’t you?). They are classified following their orbital elements:

  • Centaurs: they orbit inner to the orbit of Neptune, i.e. their semimajor axis is smaller than 30 AU. As such, they are not TNOs strictly speaking,
  • Inner-belt objects: here the belt is the Kuiper Belt, not to be confused with the Main Asteroid Belt between Mars and Jupiter. This objects orbit between the orbit of Neptune and the 3:2 resonance, i.e. the orbit of Pluto, at 39.4 AU.
  • Main-belt objects: between the 3:2 and the 2:1 resonance, i.e. between 39.4 and 47.7 AU.
  • Outer-belt objects: they orbit beyond the 2:1 resonance and have an eccentricity smaller than 0.24.
  • Detached objects: not only they orbit beyond the 2:1 resonance, but also have an eccentricity larger than 0.24. As a consequence, they may have very large semi-major axes, but could be detected since their perihelion distance, i.e. their closest distance to the Sun, is accessible to our terrestrial instruments. This is made possible by their high eccentricity. Among these objects are the eTNOs (e for extreme) mentioned here.

And now the results.

Key results

1,142 TNOs (including Centaurs) are now classified, 838 of them thanks to OSSOS. Among these 838 objects, 313 are resonant, including 132 in the 3:2 resonance, 39 in the 7:4 and 34 in the 2:1, and 525 are non-resonant. 421 of the non-resonant object are in the main belt, i.e. between the 3:2 and the 2:1 resonances.

Among the remarkable other results are

  • There should be about 90,000 detached objects with a diameter larger than 100 km, and probably less than 1,000 so large Centaurs,
  • the inner Kuiper Belt practically starts at 37 AU,
  • the population of low-inclination objects extends to at least 49 AU, but there is a huge concentration of them between 42.5 and 44.5 AU,
  • the inclinations are larger in the 3:2 resonance (the Plutinos) than in the 2:1,
  • securely occupied resonances exist at least up to 130 AU, which is the location of the 9:1 resonance.

The word origins appear in OSSOS. Actually, knowing the distribution of the Kuiper Belt Objects tells us something on the evolution of our Solar System.

Constraining the evolution of the Solar System

A TNO is a small body. This implies that, when perturbed by a giant planet, it just endures the orbital shacking. The consequence is that the giant planets have a strong enough gravitational potential to shape the Kuiper Belt. When perturbed, an object might get inclined, eccentric, be ejected, confined…

There are several competing models of the evolution of the Solar System, which implies migration of the giant planets. When a giant planet migrates, its perturbation migrates as well, and you should see the consequences on the Kuiper Belt. This is how an accurate snapshot of the Kuiper Belt might tell us something on the past of our Solar System, and if you constrain its evolution, then you can be tempted to transpose it to extrasolar systems. Moreover, this could give clues on the Planet Nine…

The OSSOS team provides software, which include a survey simulator, checking the relevance of a predicted model for the Kuiper Belt, when compared to the observations.

The study and its authors

And that’s it for today! Please do not forget to comment. You can also subscribe to the RSS feed, and follow me on Twitter, Facebook, Instagram, and Pinterest.

Impacts on Jupiter

Hi there! Today is a little different. I present you a study of the impacts on Jupiter. This study, Small impacts on the giant planet Jupiter, by Hueso et al., has recently been accepted for publication in Astronomy and Astrophysics.
This is something different from usual by the implication of amateur astronomers. The professional scientific community sometimes needs their help, because they permit to tend to a global coverage of an expected event, like a stellar occultation. This is here pretty different since impacts on Jupiter are not predicted, so they are observed by chance. And the more observations, the more chance.
Thanks to these data, the authors derived an estimation of the impact rate on Jupiter.

The fall of Shoemaker-Levy 9

Before getting to the point, let me tell you the story of the comet Shoemaker-Levy 9. This comet has been discovered around Jupiter in March 1993 by Carolyn and Eugene Shoemaker, David Levy, and Philippe Bendjoya. Yes, this was discovered as a satellite of Jupiter, but on an unstable orbit. This comet was originally not a satellite of Jupiter, and when passing by Jupiter captured it. And finally, Shoemaker-Levy 9 crashed on Jupiter between July, 16 and July, 22 1994. Why during 6 days? Because the comet got fragmented. 23 fragments have been detected, which crashed close to the South Pole of Jupiter in 1994. This resulted in flashes more visible than the Red Spot, and scars which could be seen during several months. Moreover, Shoemaker-Levy 9 polluted the atmosphere of Jupiter with water.

Impacting Jupiter

Shoemaker-Levy 9 is a spectacular and well-known example of impact on Jupiter. But Jupiter is in fact regularly impacted. Cassini even mentioned a black dot on Jupiter in 1690, which could result from an impact. This is how things work.

Jupiter attracts the impactors

As you know, Jupiter is the most massive body in the Solar System, beside the Sun of course. As such, it attracts the small objects passing by, i.e. it tends to focus the trajectories of the impactors. So, the impactors are caught in the gravitational field of Jupiter, but usually on a hyperbolic orbit, since they come from very far away. As a consequence their orbits are unstable, and they usually will be ejected, or crash onto Jupiter. Let us assume we crash on Jupiter.

Jupiter destroys the impactors

Before the crash, the distance to Jupiter decreases, of course, and its gravitational action becomes stronger and stronger. A consequence is that the differential action of Jupiter on different parts of a given body, even a small one, gets stronger, and tends to disrupt it (tidal disruption). This is why Shoemaker-Levy 9 has been fragmented.

The impactors do not leave any crater

When the fragments reach Jupiter, they reach in fact its upper atmosphere. Since this atmosphere is very large and thick, the impactors do not create visible craters, but only perturbations in the atmosphere. We see at least a flash (a bright fireball), and then we may see kind of clouds, which are signatures of the atmospheric pollution due to the impactors. I mentioned a flash, actually they may be several of them, because the impactor is fragmented.

Let us now discuss on the observations of such events.

Observing an impact

Jupiter is usually easy to observe from the Earth, but only 9 months each year. It is too close to the Sun during the remaining time. While visible, everybody is free to point a telescope at it, and record the images. Actually amateur astronomers do it, and some impacts were detected by them. Once you have recorded a movie, then you should watch it slowly and carefully to detect an impact. Such an event lasts a few seconds, which is pretty tough to detect on a movie which lasts several hours.

The authors studied 5 events, at the following dates:

  1. June 3, 2010, detected twice, in Australia and in the Philippines,
  2. August 20, 2010, detected thrice, in Japan,
  3. September 9, 2012, detected twice, in the USA
  4. March 17, 2016, detected twice, in Austria and Ireland,
  5. May 26, 2017, detected thrice, in France and in Germany.

Once an observer detects such an event, he/she posts the information on an astronomy forum, to let everybody know about it. This is how several observers can get in touch. If you are interested, you can also consult the page of the Jupiter bolides detection project.

The detection of impacts can be improved in observing Jupiter through blue filters and wide filters centered on the methane absorption band at 890 nm, because Jupiter is pretty dark at these wavelengths, making the flash more visible. Moreover, one of the authors, Marc Delcroix, made an open-source software, DeTeCt, which automatically detects the flashes from observations of Jupiter.

All of these events were discovered by amateurs, and professionals exploited the data to characterize the impactors.

Treating the data

Once the impacts have been detected, the information and images reach the professionals. In order to characterize the impactor, they estimate the intensity and duration of the flash by differential photometry between images during the event and images before and after, to subtract the luminosity of Jupiter. Then they plot a lightcurve of the event, which could show several maximums if we are lucky enough. From the intensity and duration they get to the energy of the impact. And since they can estimate the velocity of the impact, i.e. 60 km/s, which is a little larger than the escape velocity of Jupiter (imagine you want to send a rocket from Jupiter… you should send it with a velocity of at least 60 km/s, otherwise it will fall back on the planet), they get to the size of the impactor.

A 45-m impactor every year

The most frequent impacts are probably the ones by micrometeorites, as on Earth, but we will never be able to observe them. They can only be estimated by dynamical models, i.e. numerical simulations, or by on-site measurements by spacecrafts.

The authors showed that the diameters of the impactors, which were involved in the detected events, could be from the meter to 20 meters, depending on their density, which is unknown. Moreover, they estimate that events by impactors of 45 m should occur and could be detectable every year, but that impacts from impactors of 380 meters would be detectable every 6 to 30 years… if observed of course. And this is why the authors insist that many amateurs participate to such surveys, use the DeTeCt software, report their observations, and share their images.

The study and its authors

And that’s it for today! Please do not forget to comment. You can also subscribe to the RSS feed, and follow me on Twitter, Facebook, Instagram, and Pinterest.

The rotation of ‘Oumuamua

Hi there! Today we go back to ‘Oumuamua, you know, this interstellar object discovered last Fall. Its visit to our Solar system was the opportunity to observe it, and here we discuss on an analysis of the variations of its luminosity. I present you The excited spin state of 1I/2017 U1 ‘Oumuamua, by Michael J.S. Belton and collaborators. This study tells us that its rotation state might be complex, and that affects the way we figure out its shape. It has recently been published in The Astrophysical Journal Letters.

Remember 1I/’Oumuamua?

I already told you about ‘Oumuamua. This is the first identified object, which has been found in our Solar System but which undoubtedly originates from another System. In other words, it was formed around another star.
The Pan-STARRS survey identified ‘Oumuamua in October 2017, and the determination of its orbit proved it to be unusually eccentric. With an eccentricity close to 1.2, its orbit is a branch of a hyperbola rather than an ellipse. This means that it comes from very far, passes by while the Sun deviates it, and leaves us for ever.
This is the highest eccentricity ever recorded in the Solar System so far. Other objects had an eccentricity larger than 1, but which could have been caused by the gravitational perturbation of a planet. Not for ‘Oumuamua.
Its full name is actually 1I/2017 U1 (ʻOumuamua). 2017 because it was discovered in 2017, 1I as the first Interstellar object ever discovered (by the way, the International Astronomical Union has created this category for ‘Oumuamua), and the name ‘Oumuamua means scout in Hawaiian.

The announcement of its discovery motivated the observers all around the world to try to observe it and make photometric measurements. Here we discuss what these measurements tell us on the rotation and the shape. But before that, let me tell you something on the rotation.

Different modes of rotation

We will consider that our object is an ellipsoid. This is actually unsure, but let us assume it. We have 3 different axes, and we could imagine different configurations for its rotation:

  1. Tumbling rotation: the object rotates around its 3 axes, and basically this is a mess. We could be in a situation of dynamical chaos, like for the moon of Saturn Hyperion.
  2. Short-axis mode (SAM): the rotation is strongly dominated by a motion around the shortest axis. This is the case for many bodies in the Solar System, like the planets, our Moon… This does not mean that the rotation is strictly around one axis, but we will see that a little later.
  3. Long-axis mode (LAM): the rotation is strongly dominated by a motion around the longest axis.
The LAM and SAM modes.
The LAM and SAM modes.

These last two modes can actually cohabit with tumbling, i.e. a tumbling rotation may favor rotation around one axis.

If the rotation were strictly around one axis, then the body would look like a top. But this rotation axis may move with respect to the figure axis. This motion is named precession-nutation. The precession is the averaged path of the figure axis around the angular momentum, while the nutation contains the oscillations around it.

Now, imagine that you look at an object, which has such a rotation. How can you estimate it? There are ways.

Observing the rotation

Actually the brightness of a body not only depends on the distance from it, or on the insolation angle, but also on the surface facing you. This means that from the brightness, you can deduce something on the rotation state of the object. In particular, this surface brightness depends on its location with respect to the principal axis. If the object has the shape of a cigar, the reflected light from the long axis and from the short one will be different, and the lightcurve will present periodic variations. And the period of these variations is the rotation period. Easy, isn’t it?

Actually, not that easy. First, you assume that the surface has a constant albedo, i.e. that the ratio between the incident and the reflected lights is constant. But you do not know that. In particular, an icy surface has a higher albedo than a carbonaceous one. Another difficulty: a tumbling object, or even one with a precessional component in its rotation, will present a combination of different frequencies. Of course, this complicates the analysis.

However, you simplify the analysis in adding observations to your dataset. The authors used 818 observations over almost one month, spanning from Oct, 25 to Nov, 23, 2017. This includes observations from the Hubble Space Telescope, from the Magellan-Baade telescope at Las Campanas Observatory (Chile), from the Canada-France-Hawaii Telescope, from Pan-NSTARRS (these last facilities being based in Hawaii)…

Once the observations are obtained as raw data, they must be treated to correct from atmospheric and instrumental problems. And then it is not done yet, since the authors need an absolute luminosity of ‘Oumuamua, i.e. as if its distance to the observer were constant. The motion of ‘Oumuamua actually induced a trend in its distance to the Earth, and a trend in its luminosity, which the authors fitted before subtracting it the measured lightflux.

Once this is done, the authors get a lightcurve, which is constant on average, but presents variations around its mean value. Unfortunately, the required treatment induced an uncertainty in the measurements, which the authors had to consider. But fortunately, these practical difficulties are well-known, and algorithms exist to extract information from such data.

2 numerical algorithms

Basically, you need to extract periods from the variations of the lightflux. For that, we dispose of the classical tool of Fourier Transforms, which in principle requires equally spaced data. But the recorded data are not equally spaced, and remember that you must consider the uncertainties as well.

Specific algorithms exist for such a purpose. The authors used CLEAN and ANOVA, to double-check their results. These algorithms allow in particular to remove the aliasing effect, i.e. a wrong measurement of a period, because of an appropriate spacing of the data. And now, the results!

A cigar or a pancake?

The authors found two fundamental periods in the lightcurves, which are 8.67±0.34 and 3.74±0.11 hours. Interestingly, they connected these measurements to the possible dynamics of rotation, and they found two possible solutions:

  1. Long-Axis Mode: In that case, the possible rotation periods are 6.58, 13.15 and 54.48 hours, the latter being the most probable one.
  2. Short-Axis Mode: Here, ‘Oumuamua would be rotating with respect to the short-axis, but also with oscillations around the long axis of periods 13.15 or 54.48 hours.

In both axis, the long axis would also precess around the angular momentum in 8.67 ± 0.34 hours. Moreover, the authors found constraints on its shape. Previous studies already told us that ‘Oumuamua is highly elongated, this study confirms this fact, and tells us that ‘Oumuamua could be somewhere between the cigar and the pancake. But once more, this result could be weakened by variations of the surface albedo of ‘Oumuamua.

The study and its authors

And that’s it for today! Please do not forget to comment. You can also subscribe to the RSS feed, and follow me on Twitter, Facebook, Instagram, and Pinterest.

Analyzing a crater of Ceres

Hi there! The space mission Dawn has recently visited the small planets Ceres and Vesta, and the use of its different instruments permits to characterize their composition and constrain their formation. Today we focus on the crater Haulani on Ceres, which proves to be pretty young. This is the opportunity for me to present you Mineralogy and temperature of crater Haulani on Ceres by Federico Tosi et al. This paper has recently been published in Meteoritics and Planetary Science.

Ceres’s facts

Ceres is the largest asteroid of the Solar System, and the smallest dwarf planet. A dwarf planet is a planetary body that is large enough, to have been shaped by the hydrostatic equilibrium. In other words, this is a rocky body which is kind of spherical. You can anyway expect some polar flattening, due to its rotation. However, many asteroids look pretty much like potatoes. But a dwarf planet should also be small enough to not clear its vicinity. This means that if a small body orbits not too far from Ceres, it should anyway not be ejected.

Ceres, or (1)Ceres, has been discovered in 1801 by the Italian astronomer Giuseppe Piazzi, and is visited by the spacecraft Dawn since March 2015. The composition of Ceres is close to the one of C-Type (carbonaceous) asteroids, but with hydrated material as well. This reveals the presence of water ice, and maybe a subsurface ocean. You can find below its main characteristics.

Discovery 1801
Semimajor axis 2.7675 AU
Eccentricity 0.075
Inclination 10.6°
Orbital period 4.60 yr
Spin period 9h 4m 27s
Dimensions 965.2 × 961.2 × 891.2 km
Mean density 2.161 g/cm3

The orbital motion is very well known thanks to Earth-based astrometric observations. However, we know the physical characteristics with such accuracy thanks to Dawn. We can see in particular that the equatorial section is pretty circular, and that the density is 2.161 g/cm3, which we should compare to 1 for the water and to 3.3 for dry silicates. This another proof that Ceres is hydrated. For comparison, the other target of Dawn, i.e. Vesta, has a mean density of 3.4 g/cm3.

It appears that Ceres is highly craterized, as shown on the following map. Today, we focus on Haulani.

Topographic map of Ceres, due to Dawn. Click to enlarge. © NASA/JPL-Caltech/UCLA/MPS/DLR/IDA
Topographic map of Ceres, due to Dawn. Click to enlarge. © NASA/JPL-Caltech/UCLA/MPS/DLR/IDA

The crater Haulani

The 5 largest craters found on Ceres are named Kerwan, Yalode, Urvara, Duginavi, and Vinotonus. Their diameters range from 280 to 140 km, and you can find them pretty easily on the map above. However, our crater of interest, Haulani, is only 34 km wide. You can find it at 5.8°N, 10.77°E, or on the image below.

The crater Haulani, seen by <i>Dawn</i>. © NASA / JPL-Caltech / UCLA / Max Planck Institute for Solar System Studies / German Aerospace Center / IDA / Planetary Science Institute
The crater Haulani, seen by Dawn. © NASA / JPL-Caltech / UCLA / Max Planck Institute for Solar System Studies / German Aerospace Center / IDA / Planetary Science Institute

The reason why it is interesting is that it is supposed to be one of the youngest, i.e. the impact creating it occurred less than 6 Myr ago. This can give clues on the response of the material to the impact, and hence on the composition of the subsurface.
Nothing would have been possible without Dawn. Let us talk about it!

Dawn at Ceres

The NASA mission Dawn has been launched from Cape Canaveral in September 2007. Since then, it made a fly-by of Mars in February 2009, it orbited the minor planet (4)Vesta between July 2011 and September 2012, and orbits Ceres since March 2015.

This orbit consists of several phases, aiming at observing Ceres at different altitudes, i.e. at different resolutions:

  1. RC3 (Rotation Characterization 3) phase between April 23, 2015 and May 9, 2015, at the altitude of 13,500 km (resolution: 1.3 km/pixel),
  2. Survey phase between June 6 and June 30, 2015, at the altitude of 4,400 km (resolution: 410 m /pixel),
  3. HAMO (High Altitude Mapping Orbit) phase between August 17 and October 23, 2015, at the altitude of 1,450 km (resolution: 140 m /pixel),
  4. LAMO (Low Altitude Mapping Orbit) / XMO1 phase between December 16, 2015 and September 2, 2016, at the altitude of 375 km (resolution: 35 m /pixel),
  5. XMO2 phase between October 5 and November 4, 2016, at the altitude of 1,480 km (resolution: 140 m / pixel),
  6. XMO3 phase between December 5, 2016 and February 22, 2017, at the altitude varying between 7,520 and 9,350 km, the resolution varying as well, between
  7. and is in the XMO4 phase since April 24, 2017, with a much higher altitude, i.e. between 13,830 and 52,800 km.

The XMOs phases are extensions of the nominal mission. Dawn is now on a stable orbit, to avoid contamination of Ceres even after the completion of the mission. The mission will end when Dawn will run out of fuel, which should happen this year.

The interest of having these different phases is to observe Ceres at different resolutions. The HAMO phase is suitable for a global view of the region of Haulani, however the LAMO phase is more appropriate for the study of specific structures. Before looking into the data, let us review the indicators used by the team to understand the composition of Haulani.

Different indicators

The authors used both topographic and spectral data, i.e. the light reflected by the surface at different wavelengths, to get numbers for the following indicators:

  1. color composite maps,
  2. reflectance at specific wavelengths,
  3. spectral slopes,
  4. band centers,
  5. band depths.

Color maps are used for instance to determine the geometry of the crater, and the location of the ejecta, i.e. excavated material. The reflectance is the effectiveness of the material to reflect radiant energy. The spectral slope is a linear interpolation of a spectral profile by two given wavelengths, and band centers and band depths are characteristics of the spectrum of material, which are compared to the ones obtained in lab experiments. With all this, you can infer the composition of the material.

This requires a proper treatment of the data, since the observations are affected by the geometry of the observation and of the insolation, which is known as the phase effect. The light reflection will depend on where is the Sun, and from where you observe the surface (the phase). The treatment requires to model the light reflection with respect to the phase. The authors use the popular Hapke’s law. This is an empirical model, developed by Bruce Hapke for the regolith of atmosphereless bodies.

VIR and FC data

The authors used data from two Dawn instruments: the Visible and InfraRed spectrometer (VIR), and the Framing Camera (FC). VIR makes the spectral analysis in the range 0.5 µm to 5 µm (remember: the visible spectrum is between 0.39 and 0.71 μm, higher wavelengths are in the infrared spectrum), and FC makes the topographical maps.
The combination of these two datasets allows to correlate the values given by the indicators given above, from the spectrum, with the surface features.

A young and bright region

And here are the conclusions: yes, Haulani is a young crater. One of the clues is that the thermal signature shows a locally slower response to the instantaneous variations of the insolation, with respect to other regions of Ceres. This shows that the material is pretty bright, i.e. it has been less polluted and so has been excavated recently. Moreover, the spectral slopes are bluish, this should be understood as a jargony just meaning that on a global map of Ceres, which is colored according to the spectral reflectance, Haulani appears pretty blue. Thus is due to spectral slopes that are more negative than anywhere else on Ceres, and once more this reveals bright material.
Moreover, the bright material reveals hydrothermal processes, which are consequences of the heating due to the impact. For them to be recent, the impact must be recent. Morever, this region appears to be calcium-rich instead of magnesium-rich like anywhere else, which reveals a recent heating. The paper gives many more details and explanations.

Possible thanks to lab experiments

I would like to conclude this post by pointing out the miracle of such a study. We know the composition of the surface without actually touching it! This is possible thanks to lab experiments. In a lab, you know which material you work on, and you record its spectral properties. And after that, you compare with the spectrum you observe in space.
And this is not an easy task, because you need to make a proper treatment of the observations, and once you have done it you see that the match is not perfect. This requires you to find a best fit, in which you adjust the relative abundances of the elements and the photometric properties of the material, you have to consider the uncertainties of the observations… well, definitely not an easy task.

The study and its authors

And that’s it for today! Please do not forget to comment. You can also subscribe to the RSS feed, and follow me on Twitter, Facebook, Instagram, and Pinterest.

The system of (107) Camilla

Hi there! I will present you today a fascinating paper. It aims at a comprehensive understanding of the system composed of an asteroid, (107) Camilla, and its two satellites. For that, the authors acquired, processed and used 5 different types of observations, from all over the world. A consequence is that this paper has many authors, i.e. 27. Its title is Physical, spectral, and dynamical properties of asteroid (107) Camilla and its satellites, by Myriam Pajuelo and 26 colleagues, and it has recently been published in Icarus. This paper gives us the shape of Camilla and its main satellites, their orbits, the mass of Camilla, its composition, its spin period,… I give you these results below.

The system of Camilla

The asteroid (107) Camilla has been discovered in 1868 by Norman Pogson at Madras Observatory, India. It is located in the
outer Main-Belt, and more precisely it is a member of the Cybele group. This is a group of asteroids, named after the largest of them (65) Cybele, which is thought to have a common origin. They probably originate from the disruption of a single progenitor. I show you below some Camilla’s facts, taken from the JPL Small-Body Database Browser:

Discovery 1868
Semimajor axis 3.49 AU
Eccentricity 0.066
Perihelion 3.26 AU
Inclination 10.0°
Orbital period 6.52 yr

We have of course other data, which have been improved by the present study. Please by a little patient.

In 2001 the Hubble Space Telescope revealed a satellite of Camilla, S1, while the second satellite, S2, and has been discovered in 2016 from images acquired by the Very Large Telescope of Cerro Paranal, Chile. This makes (107) Camilla a ternary system. Interesting fact, there is at least another ternary system in the Cybele group: the one formed by (87) Sylvia, and its two satellites Romulus and Remus.

Since their discoveries, these bodies have been re-observed when possible. This resulted in a accumulation of different data, all of them having been used in this study.

5 different types of data

The authors acquired and used:

  • optical lightcurves,
  • high-angular-resolution images,
  • high-angular-resolution spectrum,
  • stellar occultations,
  • near-infrared spectroscopy.

You record optical lightcurves in measuring the variations of the solar flux, which is reflected by the object. This results in a curve exhibiting periodic variations. You can link their period to the spin period of the asteroid, and their amplitudes to its shape. I show you an example of lightcurve here.

High-angular-resolution imaging requires high-performance facilities. The authors used data from the Hubble Space Telescope (HST), and of 3 ground-based telescopes, equipped with adaptive optics: Gemini North, European Southern Observatory Very Large Telescope (VLT), and Keck. Adaptive optics permits to correct the images from atmospheric distortion, while the HST, as a space telescope, is not hampered by our atmosphere. In other words, our atmosphere bothers the accurate observations of such small objects.

A spectrum is the amplitude of the reflected Solar light, with respect to its wavelength. This permits to infer the composition of the surface of the body. The high-angular-resolution spectrum were made at the VLT, the resulting data also permitting astrometry of the smallest of the satellites, S2. These spectrum were supplemented by near-infrared spectroscopy, made with a dedicated facility, i.e. the SpeX spectrograph of the NASA InfraRed Telescope Facility (IRTF), based on Mauna Kea, Hawaii. Infrared is very sensitive to the temperature, this is why their observations require dedicated instruments, which need a dedicated cooling system.

Finally, stellar occultations consist to record the light of a star, which as some point is occulted by the asteroid you study. This is particularly interesting for a faint body, which you cannot directly observe. Such observations can be made by volunteers, who use their own telescopes. You can deduce clues on the shape, and sometimes on the presence of a satellite, from the duration of the occultation. In comparing the durations of the same occultation, recorded at different locations, you may even reconstruct the shape (actually a 2-D shape, which is projected on the celestial sphere). See here.

And from all this, you can infer the orbits of the satellites, and the composition of the primary (Camilla) and its main satellite (S1), and the spin and shape of Camilla.

The orbits of the satellites

All of these observations permit astrometry, i.e. they give you the relative location of the satellites with respect to Camilla, at given dates. From all of these observations, you fit orbits, i.e. you numerically determine the orbits, which have the smallest distances (residuals), with the data.

This is a very tough task, given the uncertainty of the recorded positions. For that, the authors used their own genetic-based algorithm, Genoid, for GENetic Orbit IDentification, which relies on a metaheuristic method to minimize the residuals. Many trajectories are challenged in this iterative approach, and only the best ones are kept. These remaining trajectories, designed as parents, are used to generate new trajectories which improve the residuals. This algorithm has proven its efficiency for other systems, like the binary asteroid (22) Kalliope-Linus. In such cases, the observations lack of accuracy and many parameters are involved.

You can find the results below.

S/2001 (107) 1
Semimajor axis 1247.8±3.8 km
Eccentricity <0.013
Inclination (16.0±2.3)°
Orbital period 3.71234±0.00004 d
S/2016 (107) 2
Semimajor axis 643.8±3.9 km
Eccentricity ~0.18 (<0.23)
Inclination (27.7±21.8)°
Orbital period 1.376±0.016 d

You can deduce the mass of (107) Camilla from these numbers, i.e. (1.12±0.01)x1019 kg. The ratio of two orbital periods probably rule out any significant mean-motion resonance between these two satellites.

Spin and shape

The authors used their homemade algorithm KOALA (Knitted Occultation, Adaptive-optics, and Lightcurve Analysis) to determine the best-fit solution (once more, minimization of the residuals) for spin period, orientation of the rotation pole, and 3-D shape model, from lightcurves, adaptive optics images, and stellar occultations. And you can find the solution below:

Diameter 254±36 km
a 340±36 km
b 249±36 km
c 197±36 km
Spin period 4.843927±0.00004 h

This table gives two solutions for the shape: a spherical one, and an ellipsoid. In this last solution, a, b, and c are the three diameters. We can see in particular that Camilla is highly elongated. Actually a comparison between the data and this ellipsoid, named the reference ellipsoid, revealed two deep and circular basins at the surface of Camilla.

Moreover, a comparison of the relative magnitudes of Camilla and its two satellites, and the use of the diameter of Camilla as a reference, give an estimation of the diameters of the two satellites. These are 12.7±3.5 km for S1 and 4.0±1.2 km for S2. These numbers assume that S1 and S2 have the same albedo. This assumption is supported for S1 by the comparison of its spectrum from the one of Camilla.

The composition of these objects

In combining the shape of Camilla with its mass, the authors deduce its density, which is 1,280±130 kg/m3. This is slightly larger than water, while silicates should dominate the composition. As the authors point out, there might be some water ice in Camilla, but this pretty small density is probably due to the porosity of the asteroid.

The study and its authors

And that’s it for today! Please do not forget to comment. You can also subscribe to the RSS feed, and follow me on Twitter, Facebook, Instagram, and Pinterest.