Tag Archives: numerical methods

Dust coorbital to Jupiter

Hi there! You may have heard of the coorbital satellites of Jupiter, or the Trojans, which share its orbit. Actually they are 60° ahead or behind it, which are equilibrium positions. Today we will see that dust is not that attached to these equilibrium. This is the opportunity to present you a study divided into two papers, Dust arcs in the region of Jupiter’s Trojan asteroids and Comparison of the orbital properties of Jupiter Trojan asteroids and Trojan dust, by Xiaodong Liu and Jürgen Schmidt. These two papers have recently been accepted for publication in Astronomy and Astrophysics.

The Trojan asteroids

Jupiter is the largest of the planets of the Solar System, it orbits the Sun in 11.86 years. On pretty the same orbit, asteroids precede and follow Jupiter, with a longitude difference of 60°. These are stable equilibrium, in which Jupiter and every asteroid are locked in a 1:1 mean-motion resonance. This means that they have the same orbital period. These two points, which are ahead and behind Jupiter on its orbit, are the Lagrange points L4 and L5. Why 4 and 5? Because three other equilibrium exist, of course. These other Lagrange points, i.e. L1, L2, and L3, are aligned with the Sun and Jupiter, and are unstable equilibrium. It is anyway possible to have orbits around them, and this is sometimes used in astrodynamics for positioning artificial satellites of the Earth, but this is beyond the scope of our study.

Location of the Lagrange points.
Location of the Lagrange points.

At present, 7,206 Trojan asteroids are list by the JPL Small Body Database, about two thirds orbiting in the L4 region. Surprisingly, no coorbital asteroid is known for Saturn, a few for Uranus, 18 for Neptune, and 8 for Mars. Some of these bodies are on unstable orbits.

Understanding the formation of these bodies is challenging, in particular explaining why Saturn has no coorbital asteroid. However, once an asteroid orbits at such a place, its motion is pretty well understood. But what about dust? This is what the authors investigated.

Production of dust

When a planetary body is hit, it produces ejecta, which size and dynamics depend on the impact, the target, and the impactor. The Solar System is the place for an intense micrometeorite bombardment, from which our atmosphere protects us. Anyway, all of the planetary bodies are impacted by micrometeorites, and the resulting ejecta are micrometeorites themselves. Their typical sizes are between 2 and 50 micrometers, this is why we can call them dust. More specifically, it is zodiacal dust, and we can sometimes see it from the Earth, as it reflects light. We call this light zodiacal light, and it can be confused with light pollution.

It is difficult to estimate the production of dust. The intensity of the micrometeorite bombardment can be estimated by spacecraft. For instance, the spacecraft Cassini around Saturn had on-board the instrument CDA, for Cosmic Dust Analyzer. This instrument not only measured the intensity of this bombardment around Saturn, but also the chemical composition of the micrometeorites.

Imagine you have the intensity of the bombardment (and we don’t have it in the L4 and L5 zones of Jupiter). This does not mean that you have the quantity of ejecta. This depends on a yield parameter, which has been studied in labs, and remains barely constrained. It should depend on the properties of the material and the impact velocity.

The small size of these particles make them sensitive to forces, which do not significantly affect the planetary bodies.

Non-gravitational forces affect the dust

Classical planetary bodies are affected (almost) only by gravitation. Their motion is due to the gravitational action of the Sun, this is why they orbit around it. On top of that, they are perturbed by the planets of the Solar System. The stability of the Lagrange points results of a balance between the gravitational actions of the Sun and of Jupiter.

This is not enough for dusty particles. They are also affected by

  • the Solar radiation pressure,
  • the Poynting-Robertson drag,
  • the Solar wind drag,
  • the magnetic Lorentz force.

The Solar radiation pressure is an exchange of momentum between our particle and the electromagnetic field of the Sun. It depends on the surface over mass ratio of the particle. The Poynting-Robertson drag is a loss of angular momentum due to the tangential radiation pressure. The Solar wind is a stream of charged particles released from the Sun’s corona, and the Lorentz force is the response to the interplanetary magnetic field.

You can see that some of these effects result in a loss of angular momentum, which means that the orbit of the particle would tend to spiral. Tend to does not mean that it will, maybe the gravitational action of Jupiter, in particular at the coorbital resonance, would compensate this effect… You need to simulate the motion of the particles to know the answer.

Numerical simulations

And this is what the authors did. They launched bunches of numerical simulations of dusty particles, initially located in the L4 region. They simulated the motion of 1,000 particles, which sizes ranged from 0.5 to 32 μm, over more than 15 kyr. And at the end of the simulations, they represented the statistics of the resulting orbital elements.

Some stay, some don’t…

This way, the authors have showed that, for each size of particles, the resulting distribution is bimodal. In other words: the initial cloud has a maximum of members close to the exact semimajor axis of Jupiter. And at the end of the simulation, the distribution has two peaks: one centered on the semimajor axis of Jupiter, and another one slightly smaller, which is a consequence of the non-gravitational forces. This shift depends on the size of the particles. As a consequence, you see this bimodal distribution for every cloud of particles of the same size, but it is visually replaced by a flat if you consider the final distribution of the whole cloud. Just because the location of the second peak depends on the size of the particles.

Moreover, dusty particles have a pericenter which is slightly closer to the one of Jupiter than the asteroids, this effect being once more sensitive to the size of the particles. However, the inclinations are barely affected by the size of the particles.

In addition to those particles, which remain in the coorbital resonance, some escape. Some eventually fall on Jupiter, some are trapped in higher-order resonances, and some even become coorbital to Saturn!

As a conclusion we could say that the cloud of Trojan asteroids is different from the cloud of Trojan dust.

All this results from numerical simulations. It would be interesting to compare with observations…

Lucy is coming

But there are no observations of dust at the Lagrange points… yet. NASA will launch the spacecraft Lucy in October 2021, which will explore Trojan asteroids at the L4 and L5 points. It will also help us to constrain the micrometeorite bombardment in these regions.

The study and its authors

You can find below the two studies:

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.

Forming Pluto’s satellites

Hi there! A team from the University of Hong Kong has recently explored a scenario of formation of the small satellites of Pluto. You know, there are 4 small bodies, named Styx, Nix, Kerberos, and Hydra, which orbit around the binary Trans-Neptunian Object Pluto-Charon. At this time, we don’t know yet how they were formed, and how they ended up at their present locations, despite the data that the spacecraft New Horizons sent us recently. The study I present you today, On the early in situ formation of Pluto’s small satellites, by Jason Man Yin Woo and Man Hoi Lee, simulates the early evolution of the Pluto-Charon system. It has recently been published in The Astronomical Journal.

The satellites of Pluto

The American Clyde W. Tombaugh discovered Pluto in 1930. He examined photographic plates taken at Lowell Observatory at Flagstaff, Arizona, USA, and detected a moving object, which thus could not be a star. The International Astronomical Union considered Pluto to be the ninth planet of the Solar System, until 2006. At that time, numerous discoveries of distant objects motivated the creation of the class of dwarf planets, Pluto being one of the largest of them.

The other American astronomer James W. Christy discovered a companion to Pluto, Charon, in June 1978. Still at Flagstaff.

The existence of far objects in our Solar System motivated the launch of the space missions New Horizons in 2006. New Horizons made a close approach of the system of Pluto in July 2015, and is currently en route to the Trans-Neptunian Object 2014MU69. The closest approach is scheduled for January, 1st 2019.

In parallel to the preparation of New Horizons, the scientific team performed observations of Pluto-Charon with the famous Hubble Space Telescope. And they discovered 4 small satellites: Nix, Hydra, Styx and Kerberos. You can find some of their characteristics below, which are due to New Horizons.

Charon Styx Nix Kerberos Hydra
Discovery 1978 2012 2005 2011 2005
Semimajor axis 17,181 km 42,656 km 48,694 km 57,783 km 64,738 km
Eccentricity 0 0.006 0 0.003 0.006
Inclination 0.8° 0.1° 0.4° 0.2°
Orbital period 6.39 d 20.16 d 24.85 d 32.17 d 38.20 d
Spin period 6.39 d 3.24 d 1.829 d 5.31 d 0.43 d
Mean diameter 1,214 km 10.5 km 39 km 12 km 42 km
Styx seen by New Horizons © NASA / Johns Hopkins University Applied Physics Laboratory / Southwest Research Institute
Styx seen by New Horizons © NASA / Johns Hopkins University Applied Physics Laboratory / Southwest Research Institute
Nix seen by New Horizons © NASA / Johns Hopkins University Applied Physics Laboratory / Southwest Research Institute
Nix seen by New Horizons © NASA / Johns Hopkins University Applied Physics Laboratory / Southwest Research Institute
Kerberos seen by New Horizons © NASA / Johns Hopkins University Applied Physics Laboratory / Southwest Research Institute
Kerberos seen by New Horizons © NASA / Johns Hopkins University Applied Physics Laboratory / Southwest Research Institute

Hydra seen by New Horizons © NASA / Johns Hopkins University Applied Physics Laboratory / Southwest Research Institute
Hydra seen by New Horizons © NASA / Johns Hopkins University Applied Physics Laboratory / Southwest Research Institute

We should compare these numbers to the ones of Pluto: a mean diameter of 2370 km, and a spin period of 6.39 d. This implies that:

  • Pluto and Charon are two large objects, with respect to the other satellites. So, Pluto-Charon should be seen as a binary TNO, and the other four objects are satellites of the binary.
  • Pluto and Charon are in a state of double synchronous spin-orbite resonance: their rotation rate is the same, and is the same that their mutual orbital motion. If you are on the surface of Pluto, facing a friend of yours on the surface of Charon, you will always face her. This is probably the most stable dynamical equilibrium, reached after dissipation of energy over the ages.

And the four small satellites orbit outside the mutual orbits of Pluto and Charon.

Proximity of Mean-Motion Resonances

We can notice that:

  • the orbital period of Styx is close to three times the one of Charon,
  • the orbital period of Nix is close to four times the one of Charon,
  • the orbital period of Kerberos is close to five times the one of Charon,
  • the orbital period of Hydra is close to six times the one of Charon.

Close to, but not exactly. This suggests the influence of mean-motion resonances of their orbital motion, i.e. the closest distance between Charon and Styx will happen every 3 orbits of Charon at the same place, so you can have a cumulative effect on the orbit. And the same thing would happen for the other objects. But this is actually not that clear whether that cumulative effect would be significant or not, and if yes, how it would affect the orbits. Previous studies suggest that it translates into a tiny zone of stability for Kerberos, provided that Nix and Hydra are not too massive.

Anyway, the authors wondered why these four satellites are currently at their present location.

Testing a scenario of formation

They addressed this question in testing the following scenario: Charon initially impacted Pluto, and the debris resulting from the impact created the four small satellites. To test this scenario, they ran long-term numerical simulations of small, test particles, perturbed by Pluto and Charon. Pluto and Charon were not in the current state, but in a presumed early one, before the establishment of the two synchronous rotations, and with and without a significant initial eccentricity for Charon. The authors simulated the orbital evolution, the system evolving over the action of gravitational mutual interactions, and tides.

The long-term evolution is ruled by tides

The tides are basically the dissipation of energy in a planetary body, due to the difference of force exerted at different points of the body. This results in stress, and is modeled as a tidal bulge, which points to the direction of the perturber. The dissipation of energy is due to the small angular shift between the orientation of the bulge and the direction of the perturber. The equilibrium configuration of Pluto-Charon, i.e. the two synchronous rotations, suggest that the binary is tidally evolved.

The authors applied tides only on Pluto and Charon, and considered two tidal models:

  1. A constant time delay between the tidal excitation and the response of the tidal bulge,
  2. A constant angular shift between the tidal bulge and the direction of the perturber.

The tidal models actually depend on the properties of the material, and the frequency of the excitation. In such a case, the frequency of the excitation depends on the two rotation rates of Pluto and Charon, and on their orbital motions. The properties of the material, in particular the rigidity and the viscosity, are ruled by the temperatures of the objects, which are not necessarily constant in space and in time, since tidal stress tend to heat the object. Here the authors did not consider a time variation of the tidal parameters.

Other models, which are probably more physically realistic but more complex, exist in the literature. Let me cite the Maxwell model, which assumes two regimes for the response of the planetary body: elastic for slow excitations, i.e. not dissipative, and dissipative for fast excitations. The limit between fast and slow is indicated by the Maxwell time, which depends on the viscosity and the rigidity of the object.

Anyway, the authors ran different numerical simulations, with the two tidal models (constant angular shift and constant time delay), with different numbers and different initial eccentricities for Charon. And in all of these simulations, they monitored the fate of independent test particles orbiting in the area.

Possible scenario, but…

The authors seem disappointed by their results. Actually, some of the particles are affected by mean-motion resonances, some other are ejected, but the simulations show that particles may end up at the current locations of Styx, Nix, Kerberos, and Hydra. However, their current locations, i.e. close to mean-motion resonances, do not appear to be preferred places for formation. This means that we still do not know why the satellites are where they currently are, and not somewhere else.

What’s next?

The next target of New Horizons is 2014MU69, which we will be the first object explored by a spacecraft, which had been launched before the object was known to us. We should expect many data.

The study and its authors

You can find here

  • The study, made freely available by the authors on arXiv, thanks to them for sharing!
  • and the homepage of Man Hoi Lee.

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:

Camilla
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.

Origin and fate of a binary TNO

Hi there! I have already told you about these Trans-Neptunian Objects, which orbit beyond the orbit of Neptune. It appears that some of them, i.e. 81 as far as we know, are binaries. As far as we know actually means that there are probably many more. These are in fact systems of 2 objects, which orbit together.

The study I present you today, The journey of Typhon-Echidna as a binary system through the planetary region, by Rosana Araujo, Mattia Galiazzo, Othon Winter and Rafael Sfair, simulates the past and future orbital motion of such a system, to investigate its origin and its fate. This study has recently been accepted for publication in The Monthly Notices of the Royal Astronomical Society.

Binary objects

Imagine two bodies, which are so close to each other that they interact gravitationally. You can say, OK, this is the case for the Sun and the planets, for the Earth and the Moon, for Jupiter and its satellites… Very well, but in all of those cases, one body, which we will name the primary, is much heavier than the other ones. This results as small bodies orbiting around the primary. But what happens when the mass ratio between these two bodies is rather close to unity, i.e. when two bodies of similar mass interact? Well, in that case, what we call the barycenter of the system, or the gravity center, is not close to the center of the primary, it is in fact somewhere between the two bodies. And the two bodies orbit around it. We call such a system a binary.

Binary systems may exist at every size. I am not aware of known binary giant planets, and certainly not in the Solar System, but we have binary asteroids, binary stars… and theory even predicts the existence of binary black holes! We will here restrict to binary asteroids (in the present case, binary minor planets may be more appropriate… please forgive me that).

So, you have these two similar bodies, of roughly the same size, which orbit together… their system orbiting around the Sun. A well-known example is the binary Pluto-Charon, which itself has small satellites. Currently some approximately 300 binary asteroids are known, 81 of them in the Trans-Neptunian region. The other ones are in the Main Belt and among the Near-Earth Asteroids. This last population could be the most populated by binaries, not only thanks to an observational bias (they are the easiest ones to observe, aren’t they?), but also because the YORP effect favors the fission of these Near-Earth Asteroids.

Anyway, the binary system we are interested in is located in what the authors call the TNO-Centaurs region.

The TNOs-Centaurs region

The name of that region of the Solar System may seem odd, it is due to a lack of consistency in the literature. Basically, the Trans-Neptunian region is the one beyond the orbit of Neptune. However, the Centaurs are the asteroids orbiting between the orbits of Jupiter and Neptune. This would be very clear if the orbit of Neptune was a legal border… but it is not. What happens when the asteroid orbits on average beyond Neptune, but is sometimes inside? You have it: some call these bodies TNO-Centaurs. Actually they are determined following two conditions:

  1. The semimajor axis must be larger than the one of Neptune, i.e. 30.110387 astronomical units (AU),
  2. and the distance between the Sun and the perihelion should be below that number, the perihelion being the point of the orbit, which is the closest to the Sun.

The distance between the Sun and the asteroid varies when the orbit is not circular, i.e. has a non-null eccentricity, making it elliptic.

When I speak of the orbit of an asteroid, that should be understood as the orbit of the barycenter, for a binary. And the authors recall us that there are two known binary systems in this TNOs-Centaurs region: (42355) Typhon-Echidna, and (65489) Ceto-Phorcys. Today we are interested by (42355) Typhon-Echidna.

(42355) Typhon-Echidna

(42355) Typhon has been discovered in February 2002 by the NEAT program (Near-Earth Asteroid Tracking). This was a survey operating between 1995 and 2007 at Palomar Observatory in California. It was jointly run by the NASA and the Jet Propulsion Laboratory. You can find below some orbital and characteristics of the binary around the Sun, from the JPL Small-Body Database Browser:

Typhon-Echidna
Semimajor axis 38.19 AU
Eccentricity 0.54
Perihelion 17.57 AU
Inclination 2.43°
Orbital period 236.04 yr

As you can see, the orbit is very eccentric, which explains why the binary is considered to be in this gray zone at the border between the Centaurs and the TNOs.

Discovery of Typhon in Feb. 2002, then known as 2002 CR<sub>46</sub>. © NEAT
Discovery of Typhon in Feb. 2002, then known as 2002 CR<sub>46</sub>. © NEAT

And you can find below the orbital characteristics of the orbit of Echidna, which was discovered in 2006:

Semimajor axis 1580 ± 20 km
Eccentricity 0.507 ± 0.009
Inclination 42° ± 2°
Orbital period 18.982 ± 0.001 d

These data have been taken from Johnston’s Archive. Once more, you can see a very eccentric orbit. Such high eccentricities do not look good for the future stability of the object… and this will be confirmed by this study.

In addition to these data, let me add that the diameters of these two bodies are 162 ± 7 and 89 ±6 km, respectively, Typhon being the largest one. Moreover, water ice has been detected on Typhon, which means that it could present some cometary activity if it gets closer to the Sun.

The remarkable orbit of the binary, which is almost unique since only two binaries are known in the TNOs-Centaurs region, supplemented by the fact it is a binary, motivated the authors to specifically study its long-term orbital migration in the Solar System. In other words, its journey from its past to its death.

It should originate from the TNOs-Centaurs region

For investigating this, the authors started from the known initial conditions of the binary, seen as a point mass. In other words, they considered only one object in each simulation, with initial orbital elements very close to the current ones. They ran in fact 100 backward numerical simulations, differing by the initial conditions, provided they were consistent with our knowledge of them. They had to be in the confidence interval.

In all of these trajectories, the gravitational influence of the planets from Venus to Neptune, and of Pluto, was included. They ran these 100 backward simulations over 100 Myr, in using an adaptive time-step algorithm from the integrator Mercury. I do not want to go too deep in the specific, but keep in mind that this algorithm is symplectic, which implies that it should remain accurate for long-term integrations. An important point is the adaptive time-step: when you run numerical integrations, you express the positions and velocities at given dates. The separation between these dates, i.e. the time-step, depends on the variability of the force you apply. The specificity of the dynamics of such eccentric bodies is that they are very sensitive to close encounters with planets, especially (but not only) the giant ones. In that case, you need a pretty short time-step, but only when you are close to the planet. When you are far, it is more advisable to use a larger time-step. Not only to go faster, but also to prevent the accumulation of round-off errors.

It results from these backward simulations that most of the clones of Typhon are still in the TNOs-Centaurs regions 100 Myr ago.

But the authors also investigated the fate of Typhon!

It should be destroyed before 200 Myr

For that, they used the same algorithm to run 500 forward trajectories. And this is where things may become dramatic: Typhon should not survive. In none of them. The best survivor is destroyed after 163 Myr, which is pretty short with respect to the age of the Solar System… but actually very optimistic.

Only 20% of the clones survive after 20 Myr, and the authors estimate the median survival time to be 5.2 Myr. Typhon is doomed! And the reason for that is the close encounters with the planets. The most efficient killer is unsurprisingly Jupiter, because of its large mass.

Interestingly, 42 of these clones entered the inner Solar System. This is why we cannot exclude a future cometary activity of Typhon: in getting closer to the Sun, it will warm, and the water ice may sublimate.

All of these simulations have considered the binary to be a point-mass. Investigating whether it will remain a binary requires other, dedicated simulations.

Will it remain a binary?

The relevant time-step for a binary is much shorter than for a point mass, just because the orbital period of Typhon around the Sun is 236 years, while the one of Echidna around Typhon is only 19 days! This also implies that a full trajectory, over 200 Myr, will require so many iterations that it should suffer from numerical approximations. The authors by-passed this problem in restricting to the close encounters with planets. When they detected a close encounter in an orbital simulation of Typhon, they ran 12,960 simulations of the orbit of Echidna over one year. Once more, these simulations differ by the initial conditions, here the initial orbital elements of Echidna around Typhon.

The authors concluded that it is highly probable that the binary survived close encounters with planets, as a binary. In other words, if Typhon survives, then Echidna should survive.

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.

New chaos indicators

Hi there! Today it is a little bit different. I will not tell you about something that has been observed but rather of a more general concept, which is the chaos in the Solar System. This is the opportunity to present you Second-order chaos indicators MEGNO2 and OMEGNO2: Theory, by Vladimir A. Shefer. This study has been originally published in Russian, but you can find an English translation in the Russian Physics Journal.

To present you this theoretical study, I need to define some useful notions related to chaos. First is the sensitivity to the initial conditions.

Sensitivity to the initial conditions

Imagine you are a planetary body. I put you somewhere in the Solar System. This somewhere is your initial condition, actually composed of 6 elements: 3 for the position, and 3 for the velocity. So, I put you there, and you evolve, under the gravitational interaction of the other guys, basically the Sun and the planets of the Solar System. You then have a trajectory, which should be an orbit around the Sun, with some disturbances of the planets. What would have happened if your initial condition would have been slightly different? Well, you expect your trajectory to have been slightly different, i.e. pretty close.

Does it always happen this way? Actually, not always. Sometimes yes, but sometimes… imagine you have a close encounter with a planet (hopefully not the Earth). During the encounter, you are very sensitive to the gravitational perturbation of that planet. And if you arrive a little closer, or a little further, then that may change your trajectory a lot, since the perturbation depends on the distance to the planet. In such a case, you are very sensitive to the initial conditions.

What does that mean? It actually means that if you are not accurate enough on the initial condition, then your predicted trajectory will lack of accuracy. And beyond a certain point, predicting will just be pointless. This point can be somehow quantified with the Lyapunov time, see a little later.

An example of body likely to have close encounters with the Earth is the asteroid (99942) Apophis, which was discovered in 2004, and has sometimes close encounters with the Earth. There was one in 2013, there will be another one in 2029, and then in 2036. But risks of impact are ruled out, don’t worry. 🙂

Let us talk now about the problem of stability.

Stability

A stable orbit is an orbit which stays around the central body. A famous and recent example of unstable orbit is 1I/’Oumuamua, you know, our interstellar visitor. It comes from another planetary system, and passes by, on a hyperbolic orbit. No chaos in that case.

But sometimes, an initially stable orbit may become unstable because of an accumulation of gravitational interactions, which raise its eccentricity, which then exceeds 1. And this is where you may connect instability with sensitivity to initial conditions, and chaos. But this is not the same. And you can even be stable while chaotic.

Now, let us define a related (but different) notion, which is the diffusion of the fundamental frequencies.

Diffusion of the Fundamental Frequencies

Imagine you are on a stable, classical orbit, i.e. an ellipse. The Sun lies at one of its foci, and you have an orbital frequency, a precessional frequency of your pericenter, and a frequency related to the motion of your ascending node. All of these points have a motion around the Sun, with constant velocities. So, the orbit can be described with 3 fundamental frequencies. If your orbit is perturbed by other bodies, which have their own fundamental frequencies, then you will find them as additional frequencies in your trajectory. Very well. If the trajectories remain constant, then it can be topologically said that your trajectories lies on tori.

Things become more complicated when you have a drift of these fundamental frequencies. It is very often related to chaos, and sometimes considered as an indicator of it. In such a case, the tori are said to be destroyed. And we have theorems, which address the survival of these tori.

The KAM and the Nekhoroshev theorems

The most two famous of them are the KAM and the Nekhoroshev theorems.

KAM stands for Kolmogorov-Arnold-Moser, which were 3 famous mathematicians, specialists of dynamical systems. These problems are indeed not specific to astronomy or planetology, but to any physical system, in which we neglect the dissipation.

The KAM theorem says that, for a slightly perturbed integrable system (allow me not to develop this point… just keep in mind that the 2-body problem is integrable), some tori survive, which means that you can have regular (non chaotic) orbits anyway. But some of them may be not. This theorem needs several assumptions, which may be difficult to fulfill when you have too many bodies.

The Nekhoroshev theory addresses the effective stability of destroyed tori. If the perturbation is small enough, then the trajectories, even not exactly on tori, will remain close enough to them over an exponentially long time, i.e. longer than the age of the Solar System. So, you may be chaotic, unstable… but remain anyway where you are.

Chaos is related to all of these notions, actually there are several definitions of chaos in the literature. Consider it as a mixture of all the elements I gave you. In particular the sensitivity to the initial conditions.

Chaos in the Solar System

Chaos has been observed in the Solar System. The first observation is the tumbling rotation of the satellite of Saturn Hyperion (see featured image). So, not an orbital case. Chaos has also been characterized in the motion of asteroids, for instance the Main-Belt asteroid (522) Helga has been proven to be in stable chaos in 1992 (see here). It is in fact swinging between two mean-motion resonances with Jupiter (Chirikov criterion), which confine its motion, but make it difficult to predict anyway. The associated Lyapunov time is 6.9 kyr.

There are also chaotic features in the rings of Saturn, which are due to the accumulation of resonances with satellites so close to the planet. These effects are even raised by the non-linear self-dynamics of the rings, in which the particles interact and collide. And the inner planets of the Solar System are chaotic over some 10s of Myr, this has been proven by long-term numerical integrations of their orbits.

To quantify this chaos, you need the Lyapunov time.

The maximal Lyapunov exponent

The Lyapunov time is the invert of the Lyapunov exponent. To estimate the Lyapunov exponent, you numerically integrate the trajectory, and its tangent vector. When the orbit is chaotic, the norm of this vector will grow exponentially, and the Lyapunov exponent is the asymptotic limit of the divergence rate of this exponential growth. It is strictly positive in case of chaos. Easy, isn’t it?

Not that easy, actually. The exponential growth makes that this norm might be too large and generate numerical errors, but this can be fixed in regularly, i.e. at equally spaced time intervals, renormalizing the tangent vector. Another problem is in the asymptotic limit: you may have to integrate over a verrrrrry long time to reach it. To bypass this problem of convergence, other indicators have been invented.

To go faster: FLI and MEGNO

FLI stands for Fast Lyapunov Indicators. There are several variants, the most basic one consists in stopping the integration at a given time. So, you give up the asymptotic limit, and you give up the Lyapunov time, but you can efficiently distinguish the regular orbits from the chaotic ones. This is a good point.

Another chaos detector is the MEGNO, for Mean Exponential Growth of Nearby Orbits. This consists to integrate the norm of the time derivative of the tangent vector divided by the norm of the tangent vector. The result tends to a straight line, which slope is half the maximal Lyapunov exponent. And this tool converges very fast. The author of the study I present you wishes to improve that tool.

This study presents MEGNO2

And for that, he presents us MEGNO2. This works like MEGNO, but with an osculating vector instead of a tangent one. Tangent means that this vector fits to a line tangent to the trajectory, while osculating means that it fits to its curvature as well, i.e. second order derivative. In other words, it is more accurate.

From this, the author shows that, like MEGNO, MEGNO2 tends to a straight line, but with a larger slope. As a consequence, he argues that it permits a more efficient detection of the chaotic orbits with respect to the regular ones. However, he does not address the link between this new slope and the Lyapunov time.

Something that my writing does not render, is that this paper is full of equations. Fair enough, for what I could call mathematical planetology.

The study and its author

As it often happens for purely theoretical studies, this one has only one author.

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.