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36c3 preroll music
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Herald: Ok, I have to say, I'm always
deeply impressed about how much we already
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learned about space, about the universe
and about our place in the universe,
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our solar system. But the next speakers
will explain us how we can use
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computational methods to simulate the
universe and actually grow planets. The
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speakers will be Anna Penzlin (miosta).
She is PHC student in computational
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astrophysics in Tübingen and Carolin
Kimmich (caro). She is a physics master's
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student at Heidelberg University. And the
talk is entitled "Grow Your Own Planets
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How Simulations Help us understand the
universe." Thank you!
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applause
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caro: So hi, everyone. It's a cool
animation right? And the really cool thing
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is that there's actually physics going on
there. So this object could really be out
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there in space but was created on a
computer. So this is how a star is
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forming, how our solar system could have
looked like in the beginning. Thank you
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for being here and that you're interested
in how we make such an animation. Anna and
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I are researchers in astrophysics. And
we're concentrating on how planets form
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and evolve. She's doing her PHD and in
Tübingen and I'm doing my masters in
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Heidelberg. And in this talk, we want to
show you a little bit of physics and how
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we can translate that in such a way that a
computer can calculate it. So, let's ask a
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question first. What is the universe or
what's in the universe? The most part of
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the universe is something we don't
understand, yet. It's dark matter and dark
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energy and we don't know what it is, yet.
And that's everything we cannot see in
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this picture here. What we can see are
stars and galaxies, and that's what we
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want to concentrate on in this talk. But
if we can see it, why would we want to
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watch a computer? Well, everything in
astronomy takes a long time. So each of
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these tiny specs you see here are galaxies
just like ours. This is how the Milkyway
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looks like. And we are living in this tiny
spot here. And as you all know, our earth
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takes one year to orbit around the sun.
Now, think about how long it takes for the
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sun to orbit around the center of the
galaxy. It's four hundred million years.
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And even the star formation is 10 million
years. We cannot wait 10 million years to
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watch how a star is forming, right? That's
why we need computational methods or
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simulations on a computer to understand
these processes. So, when we watch to the
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night sky, what do we see? Of course we
see stars and those beautiful nebulas.
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They are a gas and dust. And all of these
images are taken with Hubble Space
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Telescope. Oh, so there's one image that
does belong in there. But it looks very
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similar, right? This gives us the idea
that we can describe the gases in the
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universe as a fluid. It's really
complicated to describe the gas in every
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single particle. So, we cannot track every
single molecule in the gas that moves
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around. It's way easier to describe it as
a fluid. So remember that for later, we
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will need that. But first, let's have a
look how stars form. A star forms from a
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giant cloud of dust and gas. Everything
moves in that cloud. So, eventually more
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dense regions occur and they get even
denser. And these clams can eventually
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collapse to one star. So, this is how a
star forms. They collapse due to their own
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gravity. And in this process, a disc
forms. And in this disc, planets can form.
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So why a disc? As I said, everything moves
around in the cloud. So it's likely that
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the cloud has a little bit of an initial
rotation. As it collapses, this rotation
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gets larger and faster. And now you can
think of making a pizza. So when you make
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a pizza and spin your dough on your
finger, you get a flat disc like a star,
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like a disc around a star. That's the same
process, actually. In this disc, we have
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dust and gas. From this dust in the disc
the planet can form. But how do we get
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from tiny little dust particles to a big
planet? Well, it somehow has to grow and
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grow even further and compact until we
have rocks. And even grow further until we
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reach planets. How does it grow? Well,
that dust grows we know that. At least
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that's what I observed when I took those
images in my flat. Well, so dust can grow
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and grow even further and compact. But
when you take two rocks, we're now at this
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in this stage. When you take two rocks and
throw them together, you don't expect them
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to stick, right? You expect them to crash
and crack into a thousand pieces. So,
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we're standing on the proof that planets
exist. How does this happen? And it's not
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quite solved yet in research. So, this is
a process that is really hard to observe
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because planets are very, very tiny
compared to stars. And even stars are only
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small dots in the night sky. Also, as I
said, planets form in a disc. And it's
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hard to look inside the disc. So this is
why we need computation to understand a
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process that how planets form and other
astronomical processes. So let's have a
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look at how this simulated on a computer.
miosta: OK. So, somehow we have seen
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nature. It's beautiful and it's just like
a tank of water and a bubbly fluid we
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already have. So, now we have this bubbly
fluid and here in the middle demonstrated.
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But now we have to teach our computer to
deal with the bubbly fluid. And that's way
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too much single molecules to simulate
them, as we already said. So there are two
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ways to discretize it in a way that we
just look at smaller pieces. One is the
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Lagrangian description, just like taking
small bubbles or balls of material that
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have a fixed mass. They have a certain
velocity that varies between each particle
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and they have, of course, a momentum
because they have a velocity and a mass.
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And we've created a number of those
particles and then just see how they move
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around and how they collide with each
other. That would be one way. And that was
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described last year in a very good talk. I
can highly recommend to hear this talk if
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you're interested in this method. However,
there's a second way to also describe
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this. Not just going with the flow of the
particles, but we are a bit lazy, we just
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box it. So we create a grid. And as you
see down here in this grid, you have the
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certain filling level, a bit of a slope.
So, what's the trend there? And then we
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just look for each box, what flows in what
flows out through the surfaces of this
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box. And then we have a volume or a mass
filled within this box. And this is how we
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discretize what is going on in the disc.
And actually, since we are usually in the
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system of a disc, we do not do it in this
nice box way like this. But we use boxes
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like those because they are already almost
like a disc and we just keep exactly the
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same boxes all the time and you just
measure what goes through the surface in
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these boxes. So, this is how these two
methods look like if you compute with both
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of them. So, one was done by me. I'm
usually using this boxing method and the
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other was done by my colleague. You see
this like when you look at them, at the
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colors, at the structure here, you have
the slope inwards, you have the same slope
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inwards here. You have even this silly
structure here. The same here. But what
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you notice is you have this enlarge dots
that are really the mass particles we saw
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before, these bubbles. And here you have
this inner cutout. This is because when
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you create this grid, you have the very
region at the inner part of the disc where
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the boxes become tiny and tinier. And
well, we can't compute that. So, we have
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to cut out at some point in inner part So, here
when you go to low densities, these
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bubbles blow up and distribute their mass
over a larger area. So, it's not very
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accurate for these areas. And here we have
the problem we can't calculate the inner
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area. So both methods have their pros and
cons. And are valid. But now, for most we
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will focus on this one. Just so we have
this nice stream features. So, again,
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going back to the boxes, we have to
measure the flow between the boxes. This
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flow, in physics we call it flux, and we
have a density row one, density row too.
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And the flux is the description of what
mass moves through the surface here from
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one box to the next. So, if we write this
in math terms, it looks like this. This
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says the time derivative of the density,
meaning the change over time. So how much
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faster or slower, the velocity would be a
change in time. And then this weird
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triangle symbol it's called nabla is a
positional derivative. So, it's like a
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slope. So, how do we change our position,
actually. So, if we change, look at the
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density over time, it should correlate to
what inflow we have over position. That is
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what that says. So and then we have in
physics a few principles that we have
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always to obey because that is just almost
common sense. One of them is, well, if we
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have mass in a box. Well, like this, the
mass should not go anywhere unless someone
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takes it out. So, if we have a closed box
and mass in that box, nothing should
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disappear magically. It should all stay in
this box. So, even if these particles jump
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around in our box with a certain velocity,
it's the same number of particles in the
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end. That's again, the same equation just
told in math. So, a second very
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rudimentary principle is if we have energy
in it, in a completely closed box. So, for
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example, this nice chemicals here and we
have a certain temperature. So, in this
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case, our temperature is low, maybe like
outside of around zero degree Celsius. And
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then we have this nice chemicals down here
and at some point they react very heavily.
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We suddenly end up with much less chemical
energy and a lot more thermal energy. But
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overall, the complete energy summed up
here, like the thermal and the chemical
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energy, also the energy of the movement
and the energy of potential added up to
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this variable "U". That should not change
over time if you sum up everything.
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Because our energy is conserved within our
clothed box. And then the third thing is I
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think you all know this. If you have like
a small mass with a certain velocity, a
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very high velocity in this case and it
bumps into someone very large, what
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happens? Well, you get a very small
velocity in this large body and the
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smaller mass stops. And the principle here
is that momentum is conserved, meaning
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that the velocity times the mass of one
object is the same as then later for the
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other one. But since it's larger, this
product has to be the same. That doesn't
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change. And we have also in our
simulations to obey these rules and we
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have to code that in so that we have
physics in them. So you say, ok, this is
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really simple, these rules, right? But
actually, well, it's not quite as simple.
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So, this is the Navier-Stokes equation, a
very complicated equation is not
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completely solved. And we have here all
that is marked red are derivatives. Here
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we have our conservation law that was the
nice and simple part. But now we have to
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take other physical things into accounting
for pressure, accounting for viscosity,
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for compression. So squeezing. And like
how sticky is our fluid? And also gravity.
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So, we have a lot of additional factors,
additional physics we also have to get in
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somehow. And all of these also depend
somehow on the change of position or the
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change of time. And these derivatives
aren't really nice for our computers
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because they well, they don't understand
this triangle. So, we need to find a way
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to write an algorithm so that it can
somehow relate with these math formula in
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a way that the computer likes. And one of
the way to do this is, well, the simplest
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solution actually is just we say, OK, we
have now this nasty derivatives and we
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want to get rid of them. So, if we look
just at one box now and we say that in
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this box, the new value for the density in
this box would be the previous density,
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plus the flux in and out times the time
stepover which we measure this flux,
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right? So, and we have to somehow get to
this flux and we just say, OK, this flux
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now is if we start here and the slope of
this curve, the trends so to say, where
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this curve is going right now, it would
look like this. So, in our next step, time
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step, we would have a density down here.
And well, then we do this again. We again
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look at this point, where's the trend
going, where's the line going? And then we
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end up here. Same here. So, again, we just
try to find this flax and this is the
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trend at this position in time. So, this
goes up here. And then if we are here now,
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look at this point, it should go up here.
So this is what our next trend would be.
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And we do this over all the times. And
this is how our simulation then would
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calculate the density for one box over a
different time steps. So, that kind of
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works. So, the blue curve is the
analytical one, the red curve, well it
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kind of similar, it works. But can we do
better? It's not perfect, yet, right? So,
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what we can do is we refine this a bit,
taking a few more steps, making it a bit
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more computationally heavy, but trying to
get a better resolution. So, first we
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start with the same thing as before. We go
to this point, find the trend in this
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point. That point like the line would go
in this direction from this point. And
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then we go just half a step now. Sorry!
And now we look at this half a step to
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this point now. And again, the same
saying, OK, where's the trend going now?
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And then we take where this point would go
and added to this trend. So that would be
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that. The average of this trend, of this
exact point and this trend, this dark
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orange curve. And then we go back to the
beginning with this trend now and say this
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is a better trend than the one we had
before. We now use that and go again and
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search the point for half a time step. And
then again, we do the same thing. Now we
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again try to find actually the trend and
average it with the arrow before. So it's
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not exactly the trend. It's a bit below
the trend because we averaged it with the
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arrow before. And now we take this
averaging trend from the beginning to the
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top like this. Okay. This is already quite
good, but we can still do a little bit
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better if we averaged with our ending
point. So, we go here, look, where is the
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trend going that would go quite up like
this and we average this and this together
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and then we end up with a line like this.
This is so much better than what we had
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before. It's a bit more complicated, to be
fair. But actually it's almost on the
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line. So, this is what we wanted. So, if
you compare both of them, we have here our
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analytical curve. So, over time in one
box, this is how the densities should
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increase. And now with it both of the
numerical method, the difference looks
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like this. So, if we have smaller and
smaller time steps, even the Euler gets
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closer and closer to the curve. But
actually the Runge Kutta this four step process
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works much better and much faster.
However, it's a bit more computationally
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and difficult.
caro: When we simulate objects in
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astronomy, we always want to compare that
to objects that are really out there. So,
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this is a giant telescope, well consisting
of a lot of small telescopes. But they can
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be connected and used as a giant telescope
and it takes photos of dust in the sky.
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And this is used to take images of discs
around stars. And these discs look like
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this. So, these images were taken last
year and they are really cool. Before we
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had those images, we only had images with
less resolution. So, they were just
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blurred blobs. And we could say, yeah,
that might be a disc. But now we really
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see the discs and we see rings here, thin
rings and we see thicker rings over here.
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And even some spiraly structures here. And
also some features that are not really
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radial symmetric like this arc here. And
it's not completely solved how these
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structures formed. And to find that out a
colleague of mine took this little object
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with the asymmetry here. And so, this is
image we just saw. And this is his
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simulation. So, this is how the disc
looked like in the beginning, probably.
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And we put in three planets and let the
simulation run. And so, what we see here
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is that the star is cut out as Anna said.
So, the grid cells in the inner part are
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very, very small. And it would take a long
time to compute them all. So, that's why
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we're leaving out that spot in the middle.
And what we see here is three planets
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interacting with the material in the disc.
And we can see that these planets can make
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this thing here appear so that in the end
we have something looking very similar to
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what we want to have or what we really
observe. So, we can say three planets
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could explain how these structures formed
in this disc. It's a little bit
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elliptical, you see that. That's because
it's tilted from our side of line. It
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would be round if you watched at it face
on. But it's a little bit tilted. That's
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why it looks elliptical.
miosta: So, we already saw we can put
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planets in the gas and then we create
structures. One very exciting thing that
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we found in the last year - or two years
ago it started but then we found more - is
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this system PDS 70. In this system, for
the very first time, we found a planet
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that was still embedded completely within
the disc. So, the gas and dust. Usually,
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because the gas and dust is the main thing
that creates this signal of some radiation
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because of heat. We only observe that and
then we can't observe the planet embedded.
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But in this case, the planet was large
enough. And in the right position that we
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actually were able to observe some
signature of accretion on this planet that
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was brighter than the rest of the disc.
And then later, just this year, just a few
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months ago, we actually found out well,
this is not the only object here. This is
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very clearly a planet. But actually,
like this spot here is also something. So,
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we can see it in different grains. Every
picture here is a different set of grains
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observed. And we can see
this in five different kinds of
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observations. So, there is a planet here.
And then there is also something we don't
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know what it is yet, but its point like
and actually creates the feature that we
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reproduce in different kinds of
observational bands or different kinds of
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signals here. This is very interesting.
For the first time, we actually see a
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planet forming right now within the disc.
And so a colleague of mine also is very
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interested in the system and started to
simulate how do two planets in a disc
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change the dynamics of a disc? So here we
have, of course, this disc is again tilted
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because it's not phase on, it's like 45
degrees tilted, not like this, but like
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this. And so he had it face on. This is
what a simulation looks like. So, there
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are two planets: these blobs here, again,
as in this simulation. Here we have a
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close up. You can actually see this little
boxes are actually our simulation boxes in
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which we have our own densities. And then
he just looked at how the planets would
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change the structure and the gas and also
how the gas would interact with the
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planets, shifting them around. And it's
interesting. So, the planets tend to clear
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out an area, open a gap, and within the
disk, that block has a lot of gas around
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here. So, you have the brighter ring here
again and then clearing out more and more.
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And at some point in the simulation you
saw they get a bit jumpy. So it's very nice.
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You also see that planets induce in the
whole disc some kind of features like
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spiral features. And so a single planet
will change the symmetry and the
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appearance of a whole disc.
caro: So, the reason why the planet is
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staying at this point is because we're
rotating with the planet. So it's actually
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going around the disc, but the like camera
is rotating with the planet. So, it's
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staying at that fixed place we put it in.
miosta: Exactly. But there's more because
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as I already said, in the Navier-Stokes
equation, we have a lot of different kinds
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of physics that we all have to include in
our simulations. One of the things, of
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course, is we maybe don't have just a star
and a disc. We have planets in there and
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maybe two stars in there. And all of these
larger bodies have also an interaction
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between each other. So, if we have the
star, every planet will have an
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interaction with the star, of course. But
then also the planets between each other,
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they have also an interaction, right? So,
in the end, you have to take into account
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all of these interactions. And then also
we have accretion just looking like this.
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So, accretion means that the gas is bound
by some objects. It can be the disc, the
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planet or the star that takes up the mass,
the dust or the gas and bounce it to this
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object. And then it's lost to the disc or
the other structures because it's
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completely bound to that. So, the
principle of this would be the simulation
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I did last year and published, we have
here a binary star. So, these two dots are
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stars. I kind of kept them in the same
spot. But every picture will be one orbit
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of this binary, but since we have
interactions, you actually see them
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rotating because of the interactions, with
each other. And then also we have here a
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planet and here a planet. And the
interesting thing was that these two
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planets interact in such a way that they
end up on exactly the same orbit. So, one
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star's further out, the orange one, and then
very fast they go in. And they end up on
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exactly the same orbit. If it now play nicely.
So, another thing is with the accretion here,
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we actually see clouds from above dropping
down onto the new forming star here. So,
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all of this, what you see here would be
gas, hydrogen. And it's a very early phase
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so that disc is not completely flat. It
has a lot of material. And then we
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actually have this infall from above
towards the star and then the star keeps
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the mass. And we have to take this also
into account in our simulations. Another
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thing we have to take into account up till
now, we just cared about masses and
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densities. But of course what we actually
see is that stars are kind of warm,
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hopefully. Otherwise, temperatures here
would also not be nice. And different
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chemicals have different condensation
points. And this is also true in a system.
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So, we start with the start temperature at
the surface of the star. We have a
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temperature around 4.000 Kelvin. And then
we go a bit into the disc. And there is a
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point where we for the first time reach a
point where we have any material at all.
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Because it starts to condensate and we
actually have something solid like iron.
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For example, at a 1500 Kelvin. And then if
we go further in, we reach a point where
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we have solid water and this is at 200
Kelvin. This is what we then would need
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actually to have a planet that also has
water on it. Because if we don't get the
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water in the solid state, it will not fall
onto a terrestrial planet and be bound
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there, right? So, this is important for
our Earth, actually. And then if we go
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even further out, we have also other gases
condensating to solids like CO2 or methane
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or things like that. And since we only get
water on a planet when we have a
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temperature that is low enough so that the
water actually forms is solid and it's
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important for us to think about where that
is in our forming disc. Where do we start?
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We have a planet like Earth that could
have some water, right? But it's not just
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the simple picture, where we have all these
nice ring structures, where we have a clear
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line. Actually, it gets more complicated
because we have pressure and shocks. And
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thermodynamics is a lot like pogo dancing,
right? You crash into each other. And it's
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all about collisions. So, the gas
temperature is determined by the speed of
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your gas molecules. Like you bouncing and
crashing into each other, exchanging
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momentum. So, there's two ways to heat up
such dance. First thing is you get a large
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amount of velocity from the outside like a
huge kick, a shock into your system. A
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second way would be if we have a higher
pressure, like more molecules, then also
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you of course have more collisions and
then a higher temperature. So, if you
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change - because you have a planet now in
the system - the pressure at some point,
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you actually get a higher temperature. So,
that is not then we lose this nice line
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because suddenly we have different
pressures at different locations. And a
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colleague of mine also simulated this.
So, this is the initial condition we
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just assumed: OK, if we have no
disturbance whatsoever, we have our nice
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planet here at 1au. So, same distance as
earth to the sun. Here, too. But here we
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assume that less heat gets transferred
from the surface of the disc. And here we
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have the planet far out like Jupiter or
something. And now we actually let this
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planet change the structure of the disc.
And what happens is - we found these spirals
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and within these spirals, we change
pressure. And with this actually, if you
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see this orange, everywhere where it's
orange it's hotter than the iceline. So,
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we don't have water where it's orange. And
where it's blue we can have water. And the
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interesting thing is, even if we put a
planet out here like Jupiter, we still
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form these regions in the inner system
where we have less water.
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caro: One problem in astrophysical
simulations is that we don't always know
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how to shape our boxes or how small these
boxes have to be. So, we use a trick to
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reshape the boxes as we need them. It's
called adaptive mesh. And this is a
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simulation of the red fluid flowing in
this direction and the blue fluid in the
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other one. So, at the boundary, the two
fluid shear and they mix up somehow and we
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don't know how in advance. So, we start a
simulation and as the simulation starts,
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we reshape those boxes here. So, in the
middle we don't need much. We reshape
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because it's not that complicated here.
It's just the flow. But at the boundary we
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see those mixing up of the two fluids. And
so, we reshape the cells as we need them.
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This is done in a program, in an
astrophysical program called AREPO. We
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will later show you some more programs to
use for simulations. But another
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simulation I want to show you first is
also done with AREPO and it's a simulation
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of the universe. So, from here to here,
it's very big. It's 30 million light
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years. So each of these dots you see here
is the size of a galaxy or even more. And
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here you can actually see that at some
regions it's very empty. So, we're
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rotating around this universe, this
simulated universe here. And these regions
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here are empty. And we don't need a lot of
boxes there. The big boxes are enough
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here. But in this dense regions where we
have a lot of material, we need smaller
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boxes. And this method I showed you where
we reshape the boxes as we need them is
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used for this simulation.
miosta: So, actually, you see the
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beginning of the universe there.
caro: Yes!
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miosta: Basically, the initial mass
collapsing to the first galaxies and first
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supernovae starting. Very beautiful
simulation.
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caro: So, there are different programs, as
I already mentioned, in astrophysics.
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Three of them, those three are all open
source, so you can download them and use
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them on your own machine, if you like. But
there are more, a lot more. Some of them
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are open source, some of them are not.
Sometimes it's hard to get them. In the
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following, we will present the tool
FARGO3D and PLUTO in a detailed version or
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a more detailed vision than AREPO
because we usually use those two for our
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simulations. What I want to show you with
this slide is that depending on what you
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want to simulate, you need to choose a
different program. And one thing is that
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in astrophysics we sometimes call the
whole program code. So, if I use the word
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code. Sorry about that. I mean, the whole
program. So, let's have a look at FARGO3D.
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It's a hydro dynamics code and what you
see here is an input parameter file. There
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you define how the disc looks like. How
much mass does it have? How big is it? And
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what planet? So, here at Jupiter, do you
see that? Jupiter is put in. And we also
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define how big our boxes are. This
program is written in C, which is quite
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nice because a lot of astrophysical
programs are still written in Fortran. So,
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this is good for me because I don't know
any Fortran. We can run this and what's
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typical for FARGO3D. So that's a compilation
actually on my computer. So, I don't need
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a fancy computer. I just did it on my
small laptop and now we run it. Now,
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typical for FARGO3D, as you will see are lot
of dots. So, here it will print out a lot
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of dots and it will create at certain
times some outputs. And these outputs are
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huge files containing numbers. So, if you
look at them they are not really
357
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interesting. They just are a numbers in
something like a text file. So, a big part
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of astrophysics is also to visualize the
data. Not only to create it but also to
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make images so that we can make movies out
of them. For that, I prefer to use Python
360
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but there are a lot of tools Python
Matplotlib, but there are a lot of
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different tools to visualize the data. So,
this is actually that output. That first
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one we just saw. The Jupiter planet in the
disc that I defined in this parameter file
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and it's already started to do some
spirals. And if I would have let it
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run further than the spirals were more
prominent. And yeah, now we have a planet
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here on our computer.
miosta: OK, so we also have PLUTO. PLUTO
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somehow has a bit more setup files. So,
what I need is three files here. Looks a
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bit complicated to break it down. This
file defines my grid and initial values.
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And this simulation time here we input
actually what physics do we want to need?
369
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What is our coordinate system? So, do we
want to have a disc or just like spherical
370
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boxes or like squared boxes? And how is
the time defined? And here we then
371
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actually write a bit of code to say, OK,
now how do I want a gravitational
372
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potential? So, what's the source of
gravity or what will happen at the inner
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region where we have this dark spot? We
have somehow to define what happens if gas
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reaches this boundary. Is it just falling
in? Is it bouncing back or something? Or
375
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is it looping through the one end to the
next? This is also something we then just
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have to code in. And if we then make it
and let run, it looks like this. So,
377
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again, our nice thing we hopefully put in
or wanted to put in: the time steps, what
378
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our boundaries were, parameters of
physics. Hopefully, the right ones and
379
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then nicely we start with our time steps
and then we see this. It's hooray! It
380
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worked actually. Because it's actually not
quite simple usually to set up a running
381
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program. A running problem, because you
have to really think about what should be
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the physics. What's the scale of your
problem? What's the timescale of your
383
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problem? And specify this in a good way.
But in principle, this is how it works.
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There are few test problems if you
actually want to play around with this to
385
00:43:49,320 --> 00:43:56,390
make it easy for the beginning. And this
is how we do simulations. So, as I already
386
00:43:56,390 --> 00:44:02,320
set, we can just start them on our
laptops. So, here this is my laptop. I
387
00:44:02,320 --> 00:44:07,859
just type a dot slash FARGO3D and that
should run, right? And then I just wait
388
00:44:07,859 --> 00:44:16,450
for ten years to finish the simulations of
500 timesteps or outputs. Well, that's not the best
389
00:44:16,450 --> 00:44:27,660
idea. So, we need more power. And both of
us, for example, are using a cluster for
390
00:44:27,660 --> 00:44:36,880
Baden-Württemberg and that takes down our
computation time by a lot. Usually, like a
391
00:44:36,880 --> 00:44:45,050
factor of maybe 20, which is a lot. So, I
would need on my computer maybe a year and
392
00:44:45,050 --> 00:44:53,040
then I just need maybe 5 hours, a few days
or a week on this cluster, which is
393
00:44:53,040 --> 00:44:56,380
usually the simulation time about a week
for me.
394
00:44:56,380 --> 00:45:04,440
caro: So, what you see here is that we use
GPUs, yes. But we do not or mostly not use
395
00:45:04,440 --> 00:45:09,630
them for gaming. We use them for actually
actual science. Yeah, would be nice to
396
00:45:09,630 --> 00:45:20,614
play on that, right? That just said!
miosta: So, back to our Earth, actually.
397
00:45:20,614 --> 00:45:27,670
So, can we now? We wanted to grow our own
planet. We can do that, yes of course. Can
398
00:45:27,670 --> 00:45:31,600
we grow Earth? Well, Earth is a very
special planet. We have a very nice
399
00:45:31,600 --> 00:45:37,720
temperature here, right? And we have not a
crushing atmosphere like Jupiter, like a
400
00:45:37,720 --> 00:45:43,440
huge planet that we could not live under.
We have a magnetic field that shields us
401
00:45:43,440 --> 00:45:53,760
from the radiation from space and we have
water. But just enough water so that we
402
00:45:53,760 --> 00:46:00,170
still have land on this planet where we
can live on. So, even if we fine tune
403
00:46:00,170 --> 00:46:05,230
simulations, the probability that we
actually hit Earth and have all the
404
00:46:05,230 --> 00:46:12,800
parameters right is actually tiny. It's
not that easy to simulate an Earth. And
405
00:46:12,800 --> 00:46:17,320
there are a lot of open questions, too.
How did we actually manage to get just
406
00:46:17,320 --> 00:46:24,240
this sip of water on our surface? How did
we manage to collide enough mass or
407
00:46:24,240 --> 00:46:30,060
aggregate enough mass to form this
terrestrial planet without Jupiter is
408
00:46:30,060 --> 00:46:35,740
sweeping up all the mass in our system?
How could we be stable in this orbit when
409
00:46:35,740 --> 00:46:42,660
there are seven other planets swirling
around and interacting with us? All of
410
00:46:42,660 --> 00:46:48,660
this is open in our field of research
actually, and not completely understood.
411
00:46:48,660 --> 00:46:54,620
This is the reason why we still need to
do astrophysics and even in all our
412
00:46:54,620 --> 00:47:01,010
simulations there is no planet B. And the
earth is quite unique and perfect for
413
00:47:01,010 --> 00:47:06,570
human life. So, please take care of the
Earth and take care of yourself and of all
414
00:47:06,570 --> 00:47:12,270
the others people on the Congress. And
thank you for listening and thank you to
415
00:47:12,270 --> 00:47:20,380
everyone who helped us make this possible.
And to the people who actually coded our
416
00:47:20,380 --> 00:47:24,210
programs with which we simulate.
Thank you!
417
00:47:24,210 --> 00:47:37,370
applause
418
00:47:37,370 --> 00:47:42,320
Herald: Thank you for the beautiful talk
and for the message at the end, the paper
419
00:47:42,320 --> 00:47:47,970
is open for discussion, so if you guys
have any questions, please come to the
420
00:47:47,970 --> 00:47:57,160
microphones. I'm asking my Signal Angel?
No questions right now. But microphone two
421
00:47:57,160 --> 00:48:00,160
please!
Mic2: Oh, yeah. Thank you very much.
422
00:48:00,160 --> 00:48:05,690
Really beautiful talk. I can agree. I have
two questions. The first is short. You are
423
00:48:05,690 --> 00:48:10,980
using Navier-Stokes equation, but you have
on the one hand, you have the dust disc
424
00:48:10,980 --> 00:48:14,940
and on the other hand, you have solid
planets in it. And so are you using the
425
00:48:14,940 --> 00:48:18,620
same description for both
or is it a hybrid?
426
00:48:18,620 --> 00:48:23,550
miosta: It very much depends. This is one
of the things I showed you that for PLUTO,
427
00:48:23,550 --> 00:48:31,300
we write this C file that specifies some
things and about every physicist has
428
00:48:31,300 --> 00:48:39,090
somewhat his or her own version of things.
So, some usually the planets, if they are
429
00:48:39,090 --> 00:48:47,030
large, they will be put in as a gravity
source. And possibly one that can accrete
430
00:48:47,030 --> 00:48:54,090
and pebbles are usually then put in a
different way. However, also pebbles are
431
00:48:54,090 --> 00:48:57,540
at the moment a bit complicated. There are
special groups specializing in
432
00:48:57,540 --> 00:49:04,080
understanding pebbles because as we said
in the beginning, when they collide,
433
00:49:04,080 --> 00:49:10,450
usually they should be destroyed. If you
hit two rocks very together, they don't
434
00:49:10,450 --> 00:49:14,870
stick. If you hit them hard together, they
splatter around and we don't end up with an bigger object
435
00:49:14,870 --> 00:49:23,390
caro: Just to explain pebbles are small
rocks or like big sand stones or something
436
00:49:23,390 --> 00:49:28,710
like that. Yeah. So bigger rocks,
but not very big, yet.
437
00:49:28,710 --> 00:49:33,190
miosta: Yes!
caro: It depends on which code you use.
438
00:49:33,190 --> 00:49:38,370
Mic2: Thank you. Very short, maybe one.
Do you also need to include relativistic
439
00:49:38,370 --> 00:49:46,520
effects. Or is that completely out?
miosta: It's a good question. Mostly if
440
00:49:46,520 --> 00:49:54,680
you have a solar type system, you're in
the arrange where this is not necessary.
441
00:49:54,680 --> 00:50:00,010
For example, with the binaries, if they
got very close together, then at the inner
442
00:50:00,010 --> 00:50:05,200
part of the disc, that is something we
could consider. And actually, I know for
443
00:50:05,200 --> 00:50:10,500
PLUTO, it has modules to include
relativistic physics, too, yes!
444
00:50:10,500 --> 00:50:14,000
Mic2: Thank you!
Herald: OK, we have quite some questions,
445
00:50:14,000 --> 00:50:19,700
so keep them short. Number one, please!
Mic1: Thank you. Yeah. Thank you very
446
00:50:19,700 --> 00:50:24,490
much for your interesting talk. And I
think you had it on your very first slides
447
00:50:24,490 --> 00:50:31,780
that about 70 percent of the universe
consists of dark matter and energy. Is that
448
00:50:31,780 --> 00:50:37,000
somehow considered in your
simulations or how do you handle this?
449
00:50:37,000 --> 00:50:43,020
caro: Well in the simulations we make, we
are doing planets and discs around stars.
450
00:50:43,020 --> 00:50:47,440
It's not considered there. In the
simulation we showed you about the
451
00:50:47,440 --> 00:50:52,670
universe at the beginning, the blueish
things were all dark matter. So, that was
452
00:50:52,670 --> 00:50:56,260
included in there.
Mic1: OK, thank you.
453
00:50:56,260 --> 00:51:00,510
Herald: OK. Microphone 3.
Mic3: Hi, thanks. Sorry, I think you
454
00:51:00,510 --> 00:51:05,740
talked about three different programs. I
think PLUTO, FARGO3D and a third one. So,
455
00:51:05,740 --> 00:51:09,620
for a complete beginner: which program
would you suggest is like you more use
456
00:51:09,620 --> 00:51:12,570
like if you want to learn more?
Which one is user friendly or good?
457
00:51:12,570 --> 00:51:18,590
miosta: I would suggest FARGO3D first. It's
kind of user friendly, has a somewhat good
458
00:51:18,590 --> 00:51:26,240
support and they are always also very
thankful for actual comments and additions
459
00:51:26,240 --> 00:51:32,030
if people actually are engaged in trying
to improve on that. Because we are
460
00:51:32,030 --> 00:51:37,328
physicists. We're not perfect programmers
and we're also happy to learn more. So
461
00:51:37,328 --> 00:51:42,720
yeah, FARGO3D I would suggest, it has some
easy ways of testing some systems and
462
00:51:42,720 --> 00:51:45,440
getting something done.
caro: And it also has a very good
463
00:51:45,440 --> 00:51:53,567
documentation and also a manual "How to
make the first steps on the Internet". So,
464
00:51:53,567 --> 00:51:56,980
you can look that up.
Mic3: Awesome. Thank you.
465
00:51:56,980 --> 00:52:00,150
Herald: Let's get one question from
outside, from my Signal Angel.
466
00:52:00,150 --> 00:52:05,600
Signal Angel: Thank you for your talk.
There's one question from IRC: How do you
467
00:52:05,600 --> 00:52:09,510
know your model is good when you can only
observe snapshots?
468
00:52:09,510 --> 00:52:17,770
caro: Oh, that's a good question. As we
said, we're in theoretical astrophysics.
469
00:52:17,770 --> 00:52:25,170
So, there are theoretical models and these
models cannot include everything. So,
470
00:52:25,170 --> 00:52:32,610
every single process, it's not possible
because then we would calculate for years.
471
00:52:32,610 --> 00:52:37,480
Yeah, to know if a model is
good you have to…
472
00:52:37,480 --> 00:52:46,430
miosta: Usually, you have a hypothesis or
an observation that you somehow want to
473
00:52:46,430 --> 00:52:54,064
understand. With most of the necessary
physics at this stage to reproduce this
474
00:52:54,064 --> 00:53:01,660
image. So, also from the observation we
have to take into the account what our
475
00:53:01,660 --> 00:53:07,650
parameters kind of should be, how dense
this end of the simulation should be and
476
00:53:07,650 --> 00:53:13,150
things like this. So, by comparing two
observations, that's the best measure we
477
00:53:13,150 --> 00:53:21,790
can get. If we kind of agree. Of course,
if we do something completely wrong, then
478
00:53:21,790 --> 00:53:26,600
it will just blow up or we will get a
horribly high density. So, this is how we
479
00:53:26,600 --> 00:53:34,270
know. Physics will just go crazy if we do
too large mistakes. Otherwise, we would
480
00:53:34,270 --> 00:53:39,330
try to compare two observations that it
actually is sensible what we did.
481
00:53:39,330 --> 00:53:44,440
caro: Yeah, that's one of the most
complicated tasks to include just enough
482
00:53:44,440 --> 00:53:52,400
physics that the system is represented in
a good enough way. But not too much that
483
00:53:52,400 --> 00:53:57,400
our simulation would blow up in time.
Herald: Number two, please.
484
00:53:57,400 --> 00:54:03,210
Mic2: I've got a question about the
adaptive grids. How does the computer
485
00:54:03,210 --> 00:54:10,800
decide how to adapt the grid? Because the
data where's the high density comes after
486
00:54:10,800 --> 00:54:17,660
making the grid...
miosta: Yes, this is actually quite an
487
00:54:17,660 --> 00:54:25,470
interesting and also not quite easy to
answer question. Let me try to give a
488
00:54:25,470 --> 00:54:34,300
breakdown nutshell answer here.
The thing is, you measure and evaluate the
489
00:54:34,300 --> 00:54:39,380
velocities. Or in the flux, you also
evaluate the velocity. And if the velocity
490
00:54:39,380 --> 00:54:44,840
goes high, you know there's a lot
happening. So, we need a smaller grid then
491
00:54:44,840 --> 00:54:50,420
there. So, we try to create more grid
cells where we have a higher velocity. In
492
00:54:50,420 --> 00:54:55,050
a nutshell, this is of course in an
algorithm a bit harder to actually
493
00:54:55,050 --> 00:55:00,000
achieve. But this is the idea. We measured
the velocities at each point. And then if
494
00:55:00,000 --> 00:55:03,510
we measure a high velocity,
we change to a smaller grid.
495
00:55:03,510 --> 00:55:08,640
Mic2: So, you can predict where the mass
will go and whether densities are getting high.
496
00:55:08,640 --> 00:55:12,600
miosta: Exactly. Step by step so to say.
497
00:55:12,600 --> 00:55:15,890
Mic2: Thanks
Herald: We stay with Microphone 2.
498
00:55:15,890 --> 00:55:20,640
Mic2: Okay. I've got a bit of a classical
question. So, I guess a lot relies on your
499
00:55:20,640 --> 00:55:25,201
initial conditions and I have two
questions related to that. So first, I
500
00:55:25,201 --> 00:55:30,670
guess they are inspired by observations.
What are the uncertainties that you have?
501
00:55:30,670 --> 00:55:33,850
And B, then what is the impact if you
change your initial conditions like the
502
00:55:33,850 --> 00:55:41,170
density in the disc?
miosta: Yeah, right now my main research
503
00:55:41,170 --> 00:55:46,110
is actually figuring out a sensible
initial conditions or parameters for a
504
00:55:46,110 --> 00:55:53,220
disc. If you just let it have an initial
set of conditions and a sensible set of
505
00:55:53,220 --> 00:56:00,420
parameters and let it run very long, you
expect a system hopefully to convert to
506
00:56:00,420 --> 00:56:05,130
the state that it should be in. But your
parameters are of course very important.
507
00:56:05,130 --> 00:56:12,240
And here we go back to what we can
actually understand from observations. And
508
00:56:12,240 --> 00:56:17,880
what we need for example is the density,
for example. And that is something we try
509
00:56:17,880 --> 00:56:24,900
to estimate from the light we see in these
discs that you saw in this nice grid with
510
00:56:24,900 --> 00:56:31,110
all these discs we estimate OK, what's the
average light there? What should then be
511
00:56:31,110 --> 00:56:37,790
the average densities of dust
and gas in comparable disks.
512
00:56:37,790 --> 00:56:42,890
Mic2: Okay, thanks.
Herald: Okay, one more at number two.
513
00:56:42,890 --> 00:56:50,150
Mic2: Yes. Thank you for the talk. When
you increase the detail on the grid and
514
00:56:50,150 --> 00:56:59,550
you learn more. When you want to compute
the gravitational force in one cell, you
515
00:56:59,550 --> 00:57:05,090
have to somehow hold masses from the all
the other cells. So, the complexity of the
516
00:57:05,090 --> 00:57:07,090
calculus grows.
miosta: Yes
517
00:57:07,090 --> 00:57:13,820
Mic2: Quadratically, at the square of the...
how do you solve that? With more CPUs?
518
00:57:13,820 --> 00:57:20,930
caro: Well, that would be one way to do
that. But there are ways to simplify if
519
00:57:20,930 --> 00:57:26,290
you have a lot of particles in one
direction and they are far away from the
520
00:57:26,290 --> 00:57:34,400
object you're looking at. So, yeah. So, if
you have several balls here and one ball
521
00:57:34,400 --> 00:57:41,710
here, then you can include all these balls
or you can think of them as one ball. So,
522
00:57:41,710 --> 00:57:48,770
it depends on how you look at it. So, how
you define how many particles you can take
523
00:57:48,770 --> 00:58:02,230
together is when you look at the angle of
this... many particles we'll have from the
524
00:58:02,230 --> 00:58:08,040
seen from the object you're looking at.
And you can define a critical angle. And
525
00:58:08,040 --> 00:58:14,230
if an object gets smaller or if lot of
objects get smaller than this angle, you
526
00:58:14,230 --> 00:58:20,200
can just say, OK, that's one object. So,
that's a way to simplify this method. And
527
00:58:20,200 --> 00:58:23,390
there are some, yeah,
I think that's the main idea.
528
00:58:23,390 --> 00:58:30,920
Herald: Okay, we have another one.
Mic2: Do you have a strategy to check if
529
00:58:30,920 --> 00:58:35,890
the simulation will give a valuable
solution or does it happen a lot that you
530
00:58:35,890 --> 00:58:42,060
wait one week for the calculation and find
out OK it's total trash or it crashed in
531
00:58:42,060 --> 00:58:45,400
the time.
caro: So, that also depends on the program
532
00:58:45,400 --> 00:58:53,240
you're using. So, in FARGO3D, it gives
these outputs after a certain amount of
533
00:58:53,240 --> 00:58:58,980
calculation steps and you can already look
at those outputs before the simulation is
534
00:58:58,980 --> 00:59:05,210
finished. So, that would be a way to
control if it's really working. Yeah, but
535
00:59:05,210 --> 00:59:11,530
I think...
miosta: It's the same for PLUTO. So, there
536
00:59:11,530 --> 00:59:18,040
is a difference between timesteps and
actually output steps. So and you could
537
00:59:18,040 --> 00:59:23,490
define your output steps not and as the
whole simulation, but you can look at each
538
00:59:23,490 --> 00:59:31,150
output step as soon as it's produced. So,
I usually get like 500 outputs, but I
539
00:59:31,150 --> 00:59:36,630
already can look at the first and second after
maybe half an hour or something like that.
540
00:59:36,630 --> 00:59:39,950
caro: Yeah, but it also happens that you
541
00:59:39,950 --> 00:59:44,060
start a simulation and wait, and wait, and
wait and then see you put something wrong
542
00:59:44,060 --> 00:59:48,760
in there and well then you have to do it
again. So, this happens as well.
543
00:59:48,760 --> 00:59:53,070
Mic2: Thanks.
Herald: Okay. One final question.
544
00:59:53,070 --> 01:00:02,240
Mic2: Yeah, OK. Is there a program in
which you can calculate it backwards? So
545
01:00:02,240 --> 01:00:07,180
that you don't have the starting
conditions but the ending conditions
546
01:00:07,180 --> 01:00:15,220
and you can calculate how it had started?
miosta: Not for hydrodynamic. If you go to
547
01:00:15,220 --> 01:00:22,240
n-body, there is a way to go backwards in
time. But for hydrodynamics, the thing is
548
01:00:22,240 --> 01:00:31,580
that you have turbulent and almost like
chaotic conditions. So, you cannot really
549
01:00:31,580 --> 01:00:38,810
turn them back in time. With n-body you
can it because actually it's kind of... Well,
550
01:00:38,810 --> 01:00:44,890
it's not analytically solved, but it's
much closer than like turbulences,
551
01:00:44,890 --> 01:00:50,470
streams, spirals and all the
things you saw in the simulations.
552
01:00:50,470 --> 01:00:57,561
Herald: OK, I guess that brings us to the
end of the talk and of the session. Thank
553
01:00:57,561 --> 01:01:03,266
you for the discussion and of course,
thank you guys for the presentation.
554
01:01:03,266 --> 01:01:16,730
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555
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