New Moon System Around Uranus

An anonymous reader writes "Astronomers have discovered two of the smallest moons yet found around Uranus. The new moons, uncovered by NASA's Hubble Space Telescope, are about 8 to 10 miles across (12 to 16 km) -- about the size of San Francisco. The two moons are so faint they eluded detection by the Voyager 2 spacecraft, which discovered 10 small satellites when it flew by the gas giant planet in 1986. The newly detected moons are orbiting even closer to the planet than the five major Uranian satellites, which are several hundred miles wide. The two new satellites are the first inner moons of Uranus discovered from an Earth-based telescope in more than 50 years. "It's a testament to how much our Earth-based instruments have improved in 20 plus years that we can now see such faint objects 1.7 billion miles (2.8 billion km) away," says Mark Showalter, a senior research associate at Stanford University. 'The inner swarm of 13 satellites is unlike any other system of planetary moons,' says co-investigator Jack Lissauer. 'The larger moons must be gravitationally perturbing the smaller moons. The region is so crowded that these moons could be gravitationally unstable. So, we are trying to understand how the moons can coexist with each other.'"

Comments

They're wrong. Links here to solution.

[MickLinux]

We all know how complication three-body motion is, so with the number of objects affected by various gravitational fields out there, it would be incredibly hard to predict any movement at all.

What they said was correct at one time. It is no longer correct.

It actually isn't all that hard to predict their motion. There's a new mathematical tool, the Parker-Sochacki solution to the Picard Iteration, that has made great strides in the ability to predict this.

What's even better, this solution method is incredibly easy, conceptually simple, ideal for initial value problems, yields exact functional solutions, involves simple algebra [yes, that's right: simple algebra solutions to almost any set of partial differential equations] and turns out doubling precision for every iteration.

Oh, yes: there is a version out for Maple, too.

The solution that it turns out is a MacLauren series [functionally equal to the Taylor Series] dependant on as many variables as you need. However, for this you'd have everything dependent on time.

Also, this method *has* been used to predict planetary, moon, and asteroid motion. It works.

[PS: That last link has code for you code monkeys]