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this has been a really fun week for
planet news first thanks to artificial
intelligence researchers from nasa and
google announced last week that they
found two new sneaky exoplanets the
first comes from the star system kepler
90. it's around 2 500 light years away
and we used to think it hosted seven
planets surprise there's actually an
eighth planet sneaking around in there
now called kepler-90i the second is from
the star kepler-80 a star that lives
only about 1100 light years away we had
thought there were only five planets
around there but now scientists have
found a sixth called kepler-80g the
reason we missed these before is tied to
how the kepler space telescope which we
use to study these stars looks for
planets it uses the transit method which
measures a star's light intensity to see
if there are any dips in brightness if
you find a regularly timed light dip it
means something is passing in front of
the star and you've probably got
something orbiting in there this method
is really good at detecting planets that
are big or have a really wide orbit or
both thanks to perspective bigger
planets cause bigger dips and if the
planet is farther out from its star
it'll obscure more of it compared to a
similarly sized planet close in but
these new planets were stealthy and
harder to detect kepler-90i is small
only slightly bigger than earth and
closer to its star than mercury is to
the sun meanwhile kepler-80g is probably
lined up with and obscured by other
planets in its neighborhood the
telescope could still detect them but
their signals were too small for our
older programs to flag or for a human to
notice but now thanks to advances in
artificial intelligence computers can
teach themselves how to better recognize
signals and they're getting so good that
they can find planets those other
programs overlooked the scientists who
made the discoveries used machine
learning programs to pick apart the
star's data sets machine learning is
when a computer uses algorithms called
neural networks to detect patterns and
sets of data and to make extrapolations
based on those patterns this is how we
learn too and like us a computer can get
better at this over time before
analyzing the kepler 80 and 90 data the
scientists train their neural networks
using data sets that we already knew
contained transiting planets they wanted
to see how well the computer could tell
the difference between an actual planet
and a false positive based on things
like how its brightness changed over
time and it turns out it could do this
really well like almost 99 of the time
it's correct so then they fed the
network more data from the kepler space
telescope this time from almost 700
systems where we'd already found planets
just in case there were more undetected
ones and by doing this they found
kepler-90i and 80g detecting those tiny
signals that we'd missed of course this
is exciting because they're new planets
and every new planet means that our
vision of the universe has to get more
vast but it also means we're getting
better at processing the absolute
mountain of kepler space telescope data
that exists kepler has been sending data
back to us way faster than we've been
able to get through it so using neural
networks to process all that data makes
a lot of sense and as they get faster
and more powerful we'll have even more
amazing tools for getting to know the
universe and closer to home we're still
learning things about our best friend
mars this wednesday in the journal
nature scientists published a paper that
might help explain where some of mars
water went we've known for years that
our neighboring planet doesn't have a
lot of water even though it used to part
of the reason mars is so dry is because
it no longer has a strong magnetic field
without that mars couldn't retain its
atmosphere so the atmospheric pressure
dropped low enough that water evaporated
but that also isn't the whole story the
magnetic field problem can account for a
lot of the water loss but not all of it
so scientists have been on the hunt for
the rest of that water or whatever made
it disappear and now they think they've
found the culprit spongy rocks billions
of years ago mars had a ton of water and
active volcanoes so the planet's crust
is mostly basalt a volcanic rock that
can form when water and lava meet it
also contains serpentonites a type of
rock that can also form after
interactions with water which all seemed
pretty suspicious so the scientists
built a computer model of the planet's
early geology and geochemistry to
investigate and they found that the
basalt specifically might be responsible
for the missing water their model shows
that when water and lavas reacted to
form the basalt a lot of that water got
incorporated right into the rock mars
basalt has a lot more iron oxides in it
than the kind on earth which creates
different types of minerals in the rock
and that mix of minerals can hold about
25 percent more water so mars's basalt
probably trapped a ton of water like a
sponge that water eventually made its
way down into the mantle the region of a
planet just below the crust probably
because the hydrated basalt got buried
under a bunch of lava flows so that's
where they think the water is deep
underground chilling in mars mantle well
not exactly chilling it's pretty warm
down there now it's still possible that
there are other reasons for mars
disappearing water like it could have
ended up in ice closer to the surface
we'll need more observations to be sure
but we are definitely getting closer to
an answer no machine learning required
if you like exoplanets but machine
learning isn't for you scishows sponsor
brilliant has lessons in their astronomy
unit that cover some of the other ways
we detect and measure exoplanets there's
a lesson about gravitational wobble
which guides you through problems to
show how we know so much about our
nearest exoplanet proxima centauri b
i've always found this area of astronomy
fascinating so i thought i'd give it a
try so this quiz on gravitational wobble
is coming at the end in this world's
beyond earth section on brilliant so it
talks about the goldilocks zone which is
really cool and then exoplanets and
transits and how we find them and then
it jumps into learning about
gravitational wobble so i have to figure
out how fast jupiter orbits the sun in
kilometers per second so in this section
it's actually pretty simple geometry
it's just with huge numbers so if i take
the distance that jupiter is from the
sun
and use that as my radius for its total
orbit that's just you know 2 pi times r
i actually worked this out with paper
and pencil beforehand because
it's really big numbers and i needed a
calculator and to like just map it out
and think it through since it's been a
while since i've done geometry so i know
that the answer is 13.03
and that's right 13.03 kilometers per
second is how fast jupiter orbits the
sun but then it goes on to talk about
how the sun wobbles because jupiter is
affecting the sun with its gravity and
as reed has pointed out before you can
totally view the solution to help you
figure stuff out so i'm going to work my
way through this gravitational wobble
lesson so then i can get to the
interstellar travel lesson so
brilliant.org is really fun because
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