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[Music]
now our next talk is simulating
universes our speaker is Philip Bush
he's a PhD student at the max plank
Institute he used to study at some at
The liet Institute and as quite a few of
you he's also an angel at the
Congress
uh he's going to speak about how astr
physics profited from improvements in
computational power and what the current
understanding of the universe is for
this
perspective please welcome him with a
huge round of
applause
hi so thanks everyone for coming and
thanks for the organizers for giving me
the chance to talk about this uh
actually last Congress I heard some very
interesting talks in this room and I
thought why not give a talk about an
aspect of science that completely relies
on huge computers and couldn't be done
otherwise and um to show you what I'm
where we're going to end up at the end
of The Talk talk I want to show you this
video this is uh the uh a modern
cosmological simulation including gas
physics and everything run by a
collaboration of astrophysicists from
the US and Germany and some other
countries and um basically I hope at the
end of the talk you'll be able to
understand what you're seeing here and
why it's
there okay and to get there as this is a
simulation we need to simulate
universes um I couldn't have given this
talk without learning a lot from
different people uh first of all I want
to mention in the top row my uh former
and current supervisors uh in Garing and
poam few friends and colleagues of mine
in the second row who helped me prepare
this talk and uh some more colleagues
that provided me with M material for
this talk and yeah I mean science is a
group effort so um I couldn't have done
it without them
before uh I really come to the
simulations we first have to talk about
what we are simulating and so I have to
give you a quick introduction into Co
cosmology which is the science of the
development of the universe as a whole
so this is in a certain sense
neighboring or specialty um of
astrophysics and there's also going to
be a lot of astrophysics in the talk
although we're not going to go very deep
into this part but so let's dive right
in um this is a in our community very
famous plot um by the plank
collaboration plank is a satellite that
measures the cosmic micro background
which I'm going to come to in a second
and this basically has it all in there
everything that we know or that we think
to know or do know to a large degree
about the how the universe developed is
in this plot we're here today and
because light has a finite speed we look
away and we look into the past because
light from for the way took some time to
reach
this and so we look all the way to the
paast and of course we can't look all
the way to the Big Bang but that's where
our story
starts and so we have
this big bang event uh which I guess all
of you have heard about and afterwards
we have a phase of Rapid expansion in
which uh actually quantum mechanical
fluctuations are blown up to macroscopic
sizes and it's these fluctuations which
perturb an initially homo homogeneous
universe and which then bring the
structure that we see today galaxies and
so on and
um after this very rapid expansion the
universe still expands and as it expands
it cools down and particles start to
form um there's still a lot of light in
there so a lot of photons which interact
with these particles and some of these
particles are what we call dark matter
and they don't interact with these light
particles while the rest is the normal
matter that we know so uh basically uh
protons neutrons and later on electrons
and they do interact with light and uh
because they do interact with light um
although they attract each other
gravitationally um they do not form
structure yet but dark matter because
it's decoupled uh from the photons can
already start forming structure and
that's one of the hints why there has to
be something like dark matter because if
there wouldn't be dark matter there
wouldn't have been enough time today to
see any structure in the universe as
something like galaxies and so on okay
then um stuff the universe further
expands uh the contents further cool
down and at one point um the Universe um
is so big and so dilute that um the
normal matter and photons stop
interacting with each other and at that
point the photons can just fly
freely and at some point later on
reaching us after being red shift by a
large amount red shifted is um so the
wavelength increases red red light has a
longer wavelength so we call this red
shifting and uh that basically happens
because the universe is expanding under
the light as it travels to us and um
because of this red shift it reaches us
as Cosmic microwave radiation Cosmic M
the cosmic microwave background um but
at this point it's not a microwave yet
it's shorter wave thing anyway the dark
matter um has already formed structure
the gas streams into the structure and
starts forming stars and galaxies and
more and more structure forms the longer
the universe exists and so stuff further
clumps and um it becomes less and less
homogeneous and uh this is this dark
matter structure in purple but the
structure we actually see are the
galaxies and the galaxies inhabit this
rich dark matter structure in uh
basically just as tracers so we don't
see the full structure like that but we
only see some light bulbs if you want to
say on this tree or on this network of
Dark Matter
structure
okay now uh this is a picture or
depiction of the cosmic microwave
background and uh so this is a full Sky
Map this is basically all around us this
was measured by plunk again this is from
2013 um so it's a satellite that
basically measures how how the cosmic
microwave radiation reaches us and um it
can calculate what's called a black body
body temperature or black body um um
yeah temperature for each point but
that's not really important what I want
to show you here so there is some
structure in there um but you only see
the structure because we subtracted a
value 100,000 times bigger than the
variations so for the most part the
cosmic micro background is one
temperature but there are tiny
fluctuations as I uh show down here it's
uh
0.1% variation on this one temperature
and these variations are very close to
what mathematicians would call a gan
random
field and um this is um this was
predicted this way this this is
predicted by our cosmological model uh
whether there are some tiny deviations
It's actually an interesting current
question um but because it's a goshan
random field there's one statistic that
describes it fully in a statistical
sense uh and that's the power Spectrum
so basically what kind of how strong are
the fluctuations on a given scale and
it's not really important that you
understand why this curve looks this way
what is important here and which I would
like you um to see is that um so in red
we see the data points we see what we
measure from this map and in green is a
fit on or is a cosmological model with
uh six free parameters only six and
these six free parameters give us a
predicted power spectrum that fits these
data points to this degree of accuracy
so the line is the is the uh mean value
and then the green area is basically
uncertainty on this level and um
unfortunately this works so well people
would love if it wouldn't work so well
because then there would be more to talk
about but um for the last 30 years it
has worked really well and people are
trying to break it and um Sarah Conrad
is going to give a talk about um how
people might find some problems in there
and what what can be done or what what
other Avenue can be explored uh on day 4
at 2:00 p.m. or 2:10 p.m. so I would
definitely also check this talk out and
learn more about this um okay from this
fit we get uh the following um yeah
makeup of the universe once at the time
of the uh of the CMB where the CMB was
emitted and then today and at the time
of the CMB there was emitted atoms at
dark matter which don't really change in
absolute amount but in relative amount
uh where the most part of the universe
then we had neutrinos and photons and
because of the expansion of the universe
and the red shifting they decrease in
basically energy content and atoms and
dark matter still stay the same but then
there's something weird called Dark
Energy uh which drives the accelerated
expansion as we know since the late '
90s of the
universe and yeah which again Sarah
conart will also uh talk much more in
depth about
okay so um so far I most mostly talked
about gravity only and I talked a bit
about gas flowing and that's Al that
also sets the stage for our simulations
the most important thing we have to talk
about is gravity and that's the we can't
do simulations of the universe without
gravity the second thing is
hydrodynamics and we can already do
quite good simulations without
hydrodynamics but in the end if we want
to look at the smaller scales we need
hydrodynamics and then there are many
more things radiation and many more
things that might also appear later on
in the talk but they're not that
important and I don't have the time to
actually um talk about how we
incorporate them in
simulations so uh well the first
question I guess is why do we Sim why do
we do simulations at all and I mean yes
there are a lot of analytical models but
they only take us so far and we have a
problem the things in space are pretty
big so we can't really set them up in a
lab and so if we want to play around
with things we kind of um yeah have to
see what we can actually observe with
our groundbased telescopes and nowadays
also
satellites and then I mean we do have a
large amount of other physical theories
that we know about and so we H have so
we might have some idea how these things
work in
space and um then we can calculate what
they should do which is our
simulation and then we see whether they
actually do that
and our simulation itself takes some
input and um then uh we have some
algorithm that is inspired by physics
which basically incorporates our
physical laws and then predicts some
output and whether our output matches
the observation then tells us whether uh
we're on the right track or
not okay but uh what we need one more
step for simulations we need to disc
critize our
problems and this is something that will
appear over and over in this talk that's
why I'm putting it here otherwise I
don't I try not to get to technical but
um this basically is just so we have
some continuous
field and uh I mean to describe this
field we will discretize it into a
finite amount of elements and for
example we can just use uh particles of
the same mass if we interpret this as a
density field and then where it's denser
so where it's darker we have more
particles per unit area and where it's
less dense we have less particles per
unit area okay and our simulations
themselves will only deal with the
particles they will only see how these
particles
work
okay so I talked about how um dark
matter doesn't interact with light and
because it doesn't interact with light
so it doesn't do electromagnetic
interactions it also doesn't collide
with itself as normal mattera does uh so
we have a collisionless system and
which is only influenced by gravity and
uh it's a good approximation to just say
everything in the universe is just
something like dark matter it's just
collisionless um only um gravitationally
influenced matter and we'll see where
this takes us and the problem um that
this is uh can be is called the nbody
problem that's why these simulations are
called nbody
simulations and basically it's just the
question how do these n bodies so these
particles for example uh that only
interact via gravity how do they behave
over time and we all know from High
School physics we have some gra Newton's
gravitational law and we don't need gr
at this point because we're far from the
limits where gr would be of any
relevance to us um but we basically have
to see how n particles act on these n
particles and as I've written down here
just because I mean in the end we're at
a technology and computer focused uh
Congress um usually this calculation
would scale as o n
squar but we can make this much faster
using smart codes like uh particle mesh
which use fph transforms or tree codes
and so on to get to n log n and then
some newer codes even uh Implement
methods um in o n so just for the people
that are interested in this okay then uh
let's get to the to an early example of
this because people have been trying to
solve this problem for quite some time
even before they had computers and this
is more the for the hacker and tinkering
uh part of the audience because Mr
Holberg here Eric Holberg in
1941 um also tried to solve this problem
and he mostly was concerned with this
one over D squ thing in there and I mean
many things scale as one overd squ for
example the light intensity from light
bulb so he set up a system of uh little
analin with a light bulb and a photo
receptor and that were those were his
particles and then he basically measured
how much light from the other particles
were reaching every given particle and
could this way evolve the
system and he actually got pretty good
results with that so and with a lot of
student work of course because there was
a lot of manual work back then um but so
he has two galaxies actually problem
that we will revisit uh or that I mean
it's of used in in this field of study
uh and we'll see later on but we had two
galaxies and as they Cross or came close
to each other and interacted they formed
these tidal Tales you see here and this
is a picture from a real Galaxy taken
with a h space
telescope and this is how actually
Galaxy looks look like I mean this is
pure work of gravity and and uh yeah
neonian
Dynamics and then when people had
computers they Revisited this problem uh
tumor Trum uh uncle and nephew wrote
this paper together and um yeah we again
see these title
Tales um yeah and even nowadays um some
people look at simulations like that not
necessarily for the title Tales because
it's kind of solved but for other
questions okay but we're actually
interested in the whole universe right
so we look at cosmological inbody
simulations and um we don't start with
the galaxies here but we actually start
with the power Spectrum
so what we're actually doing we're not
um simulating our universe because in
the end the cosmic microw background is
billions of light years away uh because
it was billions of years ago so we just
create a initial density field with the
same statistic with the same power
Spectrum so with the same amount of
fluctuations on different scales as we
measure in our
universe
um and
while nowadays you can do maybe you come
a bit closer as I will show in the end
of the talk to our universe um that is
what we do for the most part and just to
give you a feeling how this such an
nbody simulation looks like I want to
show you this quick video which is just
a 2d simulation so we're not in 3D yet
we're just 2D because then it's easier
understand this was done by a colleague
of mine Yen
sticker and you basically see how in
slightly underd regions the particles
flow out and where you had these slight
over densities the particles flow in and
then at some point they meet each other
down here for example and they flow
through each other and they cross and we
get this system of um of filaments and
nodes um and remember this first video
we also had this system of filaments and
nodes of course in 3D it's a bit
different because after one Crossing you
get some two dimensional structure you
get a sheet and then after second
Crossing only you get a filament because
then you have collapsed two dimensions
and you're left with one dimension and
then when you collapse it in more
dimensions then for example down here Al
now we collapse two dimensions in 2D and
three dimensions we collapse three
dimensions you get what we call Halos
and Halos are um the birth plac of
galaxies because they are the densest
Dark Matter structures and um there the
gas flows in and then the galaxies um
well stars and the galaxies that make up
this uh and the stars that make up the
galaxies form in there sorry
um yeah but we're also not the first to
do this of course I mean people in the
70s already did this and this is a video
that a colleague of mine in Unearthed in
Estonia from the
USSR and where um D kevich and his
co-workers already did this in the' 70s
and then must have projected it on some
screen and filmed it with some camera
from the screen and but you already see
the same structure basically basically
as we've just seen and we can jump a bit
forward so they're um if we jump here
they also did the same problem basically
that we just showed as a toy example and
I mean that's uh by now uh what 41 years
ago and um they even had quite realistic
um like cosmological density
Fields uh but I mean in 2D here but
nevertheless so what I'm working with
still despite this having been run in
2005 but there's just a lot of
information there that we can still um
investigate is the Millennium simulation
which was uh which is very important for
the field because at the time it was the
largest simulation and it was um very
influential in the development and this
uses uh so rough a bit more than 10
billion particles in
2005 um and each particle represents um
something like a billion solar masses so
one solar mass is one sun and a billion
of them is one particle and we have 10
billion particles in the simulation and
um the box is 500 MEAP Parc so we always
have this Let's ignore this over H year
um and one parek is a bit more than
three Lighty
years and mega Parc is then a bit more
than 3 million light years so um and we
have 500 of them on each side as you
will notice actually we have one gigap
paric here uh in this picture of the
slid this is because the people did a
very smart trick of basic unfolding this
box for this picture so that it doesn't
repeat um but then this video shows us a
flight into this thing into the
simulation and we'll see how much
structure is actually resolved and at
this point um so this is actually a good
nice place to stop here you can see a
lot of things already so you see this
network which is called The Cosmic web
and you see the nodes in there where
this is where large clusters of galaxies
form and here smaller clusters or groups
you have empty regions the voids and you
have filaments this is where also a lot
of galaxies uh live and which traced
then by basically these linear um oh
linear um Arrangements of
galaxies and then let's jump forward a
bit uh so now we're zooming into this
thing and we still see structure right
we started with like thousands of MEAP
Parc now we're to single MEAP par and
there's still
structure and um that is to me at least
absolutely fascinating that we can see
that much in a
simulation um nowadays of course
computers get bigger simulations get
bigger um this is from last year is one
of the biggest that I know of it's a two
trillion particle simulation so two with
12 zeros and uh this is used for a
future satellite Mission basically to
have some data that you can already
already analyzed before the mission is
running and to learn how to analyze the
data from this Mission and uh again here
you see um you kind of see these little
um density Peaks um the Halos and that's
a very useful abstraction because they
are the birth place of
galaxies and uh I already told you some
of these things so Halos are these
gravitationally collapsed Dark Matter
objects and um we really would like to
know a lot about Halos and they are
basically the core outcome of these
simulations the core result of these
simulations to know about how the Halos
are distributed how they look like and
so on because how how a haly Halo looks
like and how it was formed um tells us
about the Galaxy that was formed in
there and so here we I just chose this
picture um because it nicely shows this
process of going from a part of the
density field with all these density
peaks in here and then we SE sear at
into a main Halo and a lot of sub Halos
and then basically we're most interested
in this abstracted picture of course not
necessarily in a plot but in a as
abstracted data analysis kind of way of
thinking um and then we want to know how
these Halos what they look like and how
they were
formed
um and to Define these there are various
methods so in the ' 80s people started
with what they called friend of friends
Halo finers I also worked with them for
quite some time time which basically
just collect uh like cluster Optics I
think people from machine learning will
also know these algorithms as cluster
finders and then there's another one
spherical overdensity finds which just
look for um overdensity Peaks or density
Peaks and then grow spheres around them
until they reach a certain minimum
density and stop but modern Halo finders
for example Rockstar by Peter bruzi um
they're much more complex and they're
don't only work on the positions but
they also take uh the full face space so
including the velocities into account
and so on um yeah but I also uh told you
that we were interested in how the Halos
form and that is encoded in here and
this is uh what's called a merger tree
um basically because Halos don't form
just from accreting diffused material
but they also form from Halos merging
and this is what we see here so this
Halo today was formed from all these
different Halos and I mean you see all
these little Halos here basically which
at some point in time so this is time
looking backwards from today merged with
this Halo and make up this
Halo okay so what is one of the well uh
yeah most uh prominent and most
important outcomes of these simulations
that uh we didn't know about before
actually is uh what's called the nfw
profile after the the Discover is Navaro
Frank and white which discovered in 1996
in
simulations and this is very remarkable
because um they found that no matter the
the mass of the Halo uh all the density
profile so basically how the density be
evolves as you go outwards can be
described to a very good degree uh with
two parameters this RS and row and R is
basically how far out you are and so you
have a you have a um R to theus1 slope
in the center and then at some point at
RS you go over to an rus2 slope and you
have some normalization
factor and that's actually quite
remarkable and this has also been um
tested with observations and uh has uh
yeah has worked very well so far of
course there's slight deviations in
certain cases but it's it's a very good
model and it was not theoretically
predicted before I mean people had ideas
but how they look should look like but
that it really is that uh what was
unclear before the uh bigger nbody
simulations in the '90s
and we can
also I don't have really time to talk
about how but we can populate these dark
matter only simulations despite not
having gas in there with galaxies
through using these merger trees and um
the masses of the Halos and so on so
just through dark this dark matter
information which basically represents
dark matter and gas we can populate them
with galaxies and then compare these
Galaxy propul
with um real observations of galaxies
and in the uh top left part of this plot
um we see um real observations so people
going out there taking their telescopes
measuring positions of galaxies in
distance and on the sky and we can do
this in the simulation this is in the
Millennium simulation and do it in the
same fashion and we see we there's not a
big difference I mean it really looks
the same so we are on the right track
there and uh this is also why for
example these mock simulations for these
bigger uh or for this satellite this
uclid satellite that I showed you before
where they do these simulations because
basically you can do this analysis
already in simulations to then do the
analys later on with the real
data okay um we can we can even compare
this more quantitively so here we have
the correlation function so basically
how many so I take a certain kind of uh
Galaxy in this case and look how many
other galaxies of this kind or how many
other objects uh I expect at a certain
radius so we have the radial distance
here this is this but it doesn't really
matter what it shows in detail what I
want to show you is that in the dots are
the measured values from the very
important sdss survey and in red we have
different kinds of populating the
simulation uh with galaxies but um it
works really well even if we split
galaxies whether uh in into red and blue
and if we go to different masses so this
is a factor of a thousand in Mass
between here and here um so this works
really well but still I mean we're
treating everything as a collisionless
um
fluid um and that's not really right so
there is gas in the universe there is
normal matter in the universe I we're
Living Testament of that so um we um are
going to hydrodynamic simulations
because we need hydrodynamics at some
point because we actually want to know
how the gas
behaves and these hydrodynamical
simulations um for us today they're only
going to have these four
ingredients um we need so apart from
gravity of course I mean gravity is
still in there it's still the most
important part we need to model the
hydrodynamics we need to see how we form
stars in there because that's in the end
what we see and uh how we treat the
super massive black holes because it and
at the center of galaxies because turns
out they're actually quite important to
what we see in these galaxies and how
the stars and the super massive black
holes act back on their host galaxies
and how they um form
them and they more phenomena that are
included nowadays in most simulations
but as I said time does not permit
treating them okay so uh ularan
hydrodynamics is the first way of
treating hydrodynamics so we just
discretize space this time into a grid
and and we have because we have some
regions where we need more spatial
resolution than in others uh we have
nested hierarchy of grids in there and
there codes today that still use them uh
or not still use them but that do use
them for example rames and Eno um to
codes that are very um important in the
field and um but this basically yeah as
I said discretizes space but before we
discretized Mass we can also do this for
hydrodynamics um
we basically divide our gas up into
particles or um or um yeah moving cells
and um so the
first way of dealing with this that did
this was it's called Smooth particle
hydr Dynamics I think many people will
know this by now if they used blender or
something like this I think they also
have this in there many other fields use
this so basically you have a particle
that represents a certain amount of gas
and then you have some kernel function
which Smooths this particle and then
this you these smooth particles
interact and um another way that we're
going to look a bit more in detail at in
a second or just give you a little
example of is an unstructured mes mesh
where you have these generator points
then you calculate a vorono Tessellation
then you know which cells are
neighboring each other and then you a
bit like in the ulian hydronics you let
stuff flow from one cell to the other
but you basically
um um refine Define or def dfine your
grid uh to keep the cells at roughly the
same mass and then there are uh new
techniques which have particles again
which look similar and um which are then
called meshless Methods because they
don't really have this these cells and
mashes but um yeah they just look the
same um okay so just to give you a quick
example how this looks like on the left
is a very bad resolution example where
you can actually see the cells using
this uh technique here in the middle
this uh moving mesh which is also used
in the simulations that I'm going to
show you further on and that I showed
you in the first video um and just to
give you a feeling of what this looks
like so we have a flow to the right and
a flow to the left that you can see this
as cool and this as hot and we see the
cells in the center are very square and
they move with the flow and at the
surface they deform and you see how the
stuff mixes in the cells and how the
cells flow with the
fluid and um this way um you basically
this makes it often advantageous comp as
compared to um uh ulian
hydrodynamics and then if you don't do
this with a bad resolution but with a
quite good resolution and this is pretty
much the same problem with little bit
with a little bit different initial
condition but uh we see we get very nice
results we get a very nice um yeah
Kelvin helmets instability which is the
standard test of hydrodynamical codes um
with these two fluids flowing through
each other or by each other and we see
the level of details and vortices that
we can track with
this okay so this is
hydrodynamics we hope we have a good
handle on that then what about stars and
super Mass like holdes problem is we
can't resolve them I mean particles are
still I mean even in good simulations
they're still way too big to track uh
single stars or to represent the space
that actually is the super mass of black
holes I mean they're huge but they're
still really really tiny compared to the
dimensions of the simulation so what we
use are subg grid models which are
effective models which basically tell us
um how the processes that we cannot
resolve behave and how they act back on
the scales that we do
resolve and so instead of resolving how
all these single stars in this forming
star cluster in the Andromeda galaxy
this that's where this picture is from
actually um form we just have star
particles which represent sometimes
Millions sometimes thousands of stars
and um then we have models how basically
these when these stars explode how they
feed back energy and momentum into the
surrounding gas the same happen happens
for super massive black hoold so here we
have a multi frequency composite image
of um of a very active Galaxy uh where
the super massive black hole at the
center drives out these Jets and emits a
lot of energy because um I mean black
holes do eat but they're very messy
eaters so when they eat the um material
that falls in gets heated a lot it
radiates and uh also a lot of the
materials actually spew spew out again
and um imparts momentum on the
surrounding gas
and um how the Supernova feedback looks
like I want to show you in this video
run by chuu from MPA at the time now in
New York and this gives you a face on
density map of a dwarf
Galaxy and uh cut through this Galaxy
and we see stars forming and then
exploding and forming these low density
Bubbles as they drive out the gas and
this is most important in small galaxies
and dwarf galaxies because they're not
massive enough to really keep all the
gas in and they the potential well so
the gravitational potential uh is weak
enough that these supernovas can really
do a lot of
damage and um as we see here really
reshaped this
galaxy okay on the other Mass end of
galaxies we have very massive super
massive
DS and yeah here I want to show you this
video run by Deo and collaborators in
2005 and while the results are not
scientifically 100% of to date now um
but they're still very close to what's
actually happening and so we have two
very massive galaxies of which we can
see the gas here um with the Hue
representing the temperature and the
color the density if I remember
correctly um interact so fly by each
other that actually
remember the title tailes that I showed
you before that's what's forming there
right now so we see these title tails
and we have super massive black holes at
the centers of these two galaxies and at
one point they start eating a lot of
this gas which is um driven on them as
part of this collision and it starts
heating up and we already see some
outflows there and then at some point
they really start um releasing a lot of
energy and driving out the gas and if
there's no gas gas if there's no cool
gas which can form Stars which can
gravitation collapse it's hot again
remember as talked about in the early
Universe um then we can't really form
stars and this also inhibits starform in
very massive
galaxies and um we didn't always know
that we needed these two processes but
um observations told us that very
massive and very low mass galaxies don't
form a lot of stars and what we see here
is actually the mass of stars divided by
the mass of the of the Dark Matter Halo
of the system so the um as
a proportional to the uh mass of normal
matter in the universe divided by the
matter of the universe so basically this
is a question how much available gas in
the universe is actually turned into
stars in galaxies and uh we see that
here we see the mass of the galactic
system so dark matter Halo Plus the
Galaxy inside but it's mostly just the
Dark Matter Halo um and we see that at
the low mass end Stellar feedback
almostly Supernova uh really
decreases uh this amount of gas that is
formed into Stars the proportional
amount and at the high mass end and here
these colorful curves are observations
this red and black one is an older
simulation um which actually doesn't get
this top end perfect perfectly right but
um we'll see a video of the refined
model uh which does much better than
this um but nonetheless um we see this
trend already here and we in our galaxy
The Milky Way live here in the roughly
at the sweet spot where we form the most
stars but even there we only turn
25% of the theoretically available gas
into
stars um okay I told you that nowadays
Galaxy simulation or these cosmological
hydrodynamic simulations do much better
and so I want to show you some results
from the illustrous TNG this is from the
illustrous simulation the illustrous TNG
because apparently people like Star Trek
um uh do much better and this is just a
little gallery of all the different
kinds of galaxies they form and they
look pretty
realistic and if you at some point we
can also look at in another talk at more
quantitative floods but also
quantitatively they do much
better and um that's actually the
simulation where this initial video came
from um and now I hope
we may or could explain to you why you
see what you see so here we see the gas
density and
temperature um in this cosmological
hydrodynamical simulation we see the gas
flowing into Dark Matter halos that's
formed and into this Cosmic web
structure formed by the dark matter we
see that um not we you don't see as many
little bright spots as you saw in the
dark matter simulation when we just
showed these density Maps because the
small galaxies don't really can hold
their gas you see how from the big spots
the gas is also driven out in these
winds from the
feedback and you see things merging and
forming bigger and bigger uh lumps and
here we actually see something like a
cluster of Galaxy's
form yeah and um but it's still of
course a bit hard to Envision how this
looks like in
Starlite
so um let's look at this in a bit more
quantitative fashion here we just have
some
slice uh with uh some slice projected
into 2D with three panels the gas
density what we saw just now and the
Dark Matter density what we we've seen
for example for the um Millennium
simulation before and actually the Stars
so this is what you would see if you
could look out with your telescope and
see very faint
objects and um this again from the
lusterous TNG simulation and this it's
run by Dyan Nelson a colleague of mine
did these very nice figures and so let's
run them for a bit we see how the Dark
Matter structure forms and then the gas
follows this already much more
structured dark matter and then we see
over here how Stars created and
sometimes you can even see let's maybe
go back to the beginning of the video
you can see how these single Stellar
particles pop up here and later on
there's enough St information that you
don't see these single events anymore
and um yeah we see how this um structure
forms and this already looks a bit like
if you remember this plot from the very
beginning
um um with um these actual Galaxy
surveys we see this this web
structure and uh but we also see that
galaxies only trace it quite sparsely so
um for the most most of this dark
structure is hidden from us and we also
don't directly see the gas but we could
for example observe it if we have a very
powerful light sources behind it and
then see how as a light pierces through
the gas is Chang in its
properties and dark matter for example
we can see if we um maybe someone else
is give a talk at some point about this
here gravitational lensing how basically
the gravitational force of the dark
metal bends the light around it and um
and uh distorts the Galaxy images that
are behind the
structure
okay
um so what are people doing nowadays so
what's what's happening at the moment in
this
field um of course things get bigger
things always get bigger with computers
so um
um we started here in the '90s
um even before we had a few so this is
the number of resolution elements so
particles or cells or something like
this so nbody particles or Hydro cells
and so on and we started with 10 to
100,000 and nowadays yeah we're in the
in billion tens of billion range um and
body simulations were always faster
because gravitation just calculating
gravity is much faster than also doing
all these other
calculations um but they actually track
each other quite well this is from a uh
publication by ganel in 2014 so we don't
have the most recent developments on
here um but as things get bigger they
also get much harder to save um so the
Millennium
simulation um uses roughly 300 gbt per
snapshot just for a particle data then
if you have data products it gets much
bigger and we have 64 snapshots so
that's roughly the 18 thte that we need
to save if we want to keep it um this
ukl Flagship simulation I calculated if
you would save it as the Millennium
simulation of course you can trick a bit
and and then but then it would be 60
terabytes per snapshot if we have 60
snapshots this would be 3.6
petabyte um which I guess is not I mean
yes I think we can save it our Institute
maybe three times or so but then our
storage is full um so the solution is we
don't really save
everything so uh we produce these Halo
cataloges that I talked about before so
we look for the Halos on the Fly and
write those things out and um how they
merge into each other and so on and we
only record data on a light cone because
um I mean you saw this before when I
showed you this plot in the beginning of
the history of the universe as the Light
reaches us it basically light from
further way places uh reaches us um
later so we see into the past as we look
out and so basically we record on a
light cone as if the light would go
through the simulation box and just
record the particle data on this light
cone and then we have basically an
simulated observation from a certain
point in this simulation
box okay um they also get stronger they
have more physical processes
included um things that I didn't talk
about but for example radiation magnetic
fields are already included in the ous
TNG and illustrous simulation cosmic
rays dust um stars produce dust and dust
couples gas and um
uh yeah radiation and in the end there's
a lot more processes that we can follow
which also increase um computation
complexity and as we increase our
resolution we decrease what we have to
consider sub subgrid so in this uh
simulation of the Supernova and this
galaxy I mean the star particles were I
think 10 solar masses or so and in other
simulations um there would have to be
thousands or hundreds of thousands of
solar mass and so on so sometimes you
actually resolve single stars in this
very high um so the very massive stars
you would resolve as a single particle
in these
simulations and they become
faster um because but I mean this being
faster is then translated into we make
them bigger so they're as slow as before
because we have the same lifetime as a
researcher but we now have more
computational time um and um we also
include more things in them but of
course also the codes get faster as I
talked told you about before I mean we
uh when we talked about how this nbody
problem there are faster and faster
methods and and the codes become just
much more efficient and we also have new
codes that maybe solve certain problems
in a more specialized but faster way um
but as computers uh become bigger uh
scaling becomes more of a problem
because we don't just use uh One Core in
the beginning or maybe a few hundred or
a few thousand but now we come into the
scale where so I talked once about
running something on the tan computer so
I think that's 1 point something million
cores or so I I forgot but anyway so
we're talking about massive numbers of
cores that have to work together and uh
so scale faing becomes a major
concern and so right now all most of
these simulations are uh programmed in
this typical MPI openmp Paradigm where
you have MPI for the interprocess
communication and then on a node you
have openmp threads that do most of the
work sometimes just MPI um with uh one
process per core um but uh people move
away from there and work with computer
scientists and uh Specialists from big
uh HBC vendors to um get faster and
better
um uh algorithms uh into these
simulations and as they become faster
there's one more thing that I wanted to
show you um we can actually do uh
interesting things with them and this is
something that yans Yasha who used to be
at my Institute and it's now in
Stockholm um does um where he basically
tries to in a certain sense fit andbody
simulations to our local universe
so where basically calculates n body
simulation in a quick way and um then
perturbs the initial conditions and such
way that he comes closer and closer to
the real outcome and here on the right
you see in dark his simulated density
field and in red actually galaxies from
a real Galaxy
survey and they match really well okay
there are some parts where they don't
really match but most for the most part
they match really really well and then
he knows from where he started so this
is on a shell 100 MEAP paric around us
uh and so this way he can unravel the
initial conditions of our own universe
and there are also other uh groups um
that do similar undertakings for example
in potam and um in a different way but
with similar method or or with a similar
goal yeah and I think also for this uh
audience quite interesting um this field
is becoming increasingly open but it's
already quite open in the sense that um
the codes are to a large degree uh
public uh some codes I mean some parts
of the codes are not necessarily public
but a lot of the big codes try to be as
public as as they deem
possible um so you can just go to uh
GitHub or whever and just look for these
codes and run simulations yourself they
have some small working examples and you
can toy around with them I mean you
don't really have a super computer but
you can still do some nice little
exercises uh the simulation results are
often made public so um they actually
want you to use the data I mean you as a
scientist now that uh produces relevant
citations and um that really helps um
make these simulations known and gets
more value out of these simulations
because more people can actually work on
them and uh here again I want to give
the Millennium uh run the Millennium
simulation as an example um so in 2018
I'm still working on this this was run
in 2005 when I was uh I turned 14 and um
today or the last time I checked that
there were
974 Publications that used the data from
the simulation for this publication I
mean some of them were just on the
simulation some compared it with others
but um yeah I think that's a pretty
impressive number and um yeah that's
really interesting and you can also look
at those things yourself I mean they're
they're on the web in the end um
sometimes you have to
register and uh maybe tell them why you
want to look at these things but um so
there's Cosmos sim.org run by people
from potam the Millennium database um
from Durham and and the mpa and Garing
where I work cosmop I think it's in eth
um and the illustrous TNG database from
this illustrious collaboration also MPA
and Harvard and some other institutions
that are involved there and so the elas
TG was actually publicly released on the
14th of December so uh it's pretty new
on the web now um but you can look at
the Halo catalogs and you can look at um
yeah all the um interesting outcomes of
these
simulations and um with this I want to
leave you with my take-home
messages I hope I could uh yeah um
explain to you why um cosmological
simulations are really powerful
tools and um
for cosmology and Galaxy formation in
these cosmologies and how um they
predict also some previously unknown
things that we U for example this nfw
profile that we didn't really know about
before and um also they're quite robust
in terms of the gravity and also um I
mean we've seen there was some Evolution
still between for example illustrous and
lusterous TNG but they're also getting
better and better in this respect and um
that they are huge computational
undertakings um and that there are very
nice examples of how science and its
results can be made public and the way
to get to these results as well and yeah
and if you want to know more about the
physical SI of these things there's this
there's going to be a great talk by
Sarah Conrad from heidleberg who's going
to talk about dark matter and dark
energy on day four uh at 10 2 in Borg
and yeah I'll definitely go there and I
hope I'll see many of you there thank
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you thank you
philli uh if you would like to leave at
this point please do that very quietly
so that people can still enjoy the Q&A
if you would like to ask a question
please line up in the microphones uh in
in the room we have a question from the
internet signal angel
please the reason for the simulation
results
embargo sorry what is the reason for the
simulation results embargo oh because I
mean if you run the simulation you also
want to be the first to call dibs and
use the results for some time I mean
they still invite people and but they
have these project Pages where they
basically say Okay I want to do this
with the simulation some other in the
col color eration wants to do this other
project with simulation and um that's
basically that you just want to reap the
fruits of your own
labor all right thanks thank you
microphone number
two um yeah as far as I understood uh
these uh simulations are not as granular
as to predict the behavior of uh
individual stars or are they okay um how
far along will will it approximately be
until this is possible and also um and
also uh factors like uh the different
classes star classes of the Hat Russell
diagram yeah no I mean there are into I
mean so that was something that I had in
the talk that I threw out again so there
are of course simulations that simulate
how star clusters form so there are
simulations even that simulate how a
single star evolves in 3D and how it
explodes as a supernova um but I think
it's not the um it's not really not
every simulation has to do everything at
the same time I mean you can have
specialized simulations that look on a
certain length scale and then use the
information and that's also what people
try to do to use information from that
length scale then in a model that you
can basically use as a subgrid model in
larger simulations for
example thank you um please try to limit
your questions to a single sentence
microphone number one please hi and
thank you
uh of all the particles in our physical
Universe having Mass uh is every
particle able to interact with every
other
particle um no
thanks microphone number
four so in all your uh simulations is
there kind of sometimes a steady state
that simulation goes to and then just
just doesn't go any further in terms of
changes or is it you know all changing
um no I don't think so because I mean
you have an accelerated expansion
so um well it could be that it reaches
equilibrium for some reason or the other
so it doesn't not that I know of not for
any reason that I know of and of course
sorry um so who just for the question
right now I mean yeah it doesn't
interact via all interactions of course
if it has mass it will interact via
gravity yeah sorry just to finish up
this question all right Right microphone
number three your question um yeah so as
you said um the models have been scaling
up um um all yeah during the last
decades um are there actually questions
that could be answered by just a bigger
model so does it really make sense to go
bigger and bigger all the time it
improves your statistics basically um
you get more extreme
environments so basically if you have a
bigger box so for example these smaller
um uh hydrodynamic simulations often
don't have very massive clusters in them
just because clusters are very massive
clusters of galaxies are rare and then
sometimes you form one in them if you're
lucky with your initial conditions but
you can't really predict that because
you haven't run the simulation yet and
then um sometimes you don't and so
bigger boxes basically help you to get
all these different environments sampled
and um the same for the largest voids
and so on you don't have the largest
voids in in a small box because
sometimes your box is smaller than the
largest
void uh microphone number one your
question hi thank you for your interes
in talk uh my question is what is the
time scale at which the simulations are
run um
meaning so you you basically start the
simulation from this uh image of this
temperal temperature scan right and then
you run it for I don't know how much so
could it be that we just run
uh compared to the life of the universe
the simulation for like a very tiny no
no no no no no you so you run it so you
don't run it a you don't run directly
from this image because in the beginning
you can do analytical approximations but
then at some point those break down and
then you have to really do these
calculations um but then you usually run
them until
today so um also this video that I
showed you it runs from when the
universe so just the video shows you the
part of of the simulation that runs from
when the universe was a fifth of its
current volume and then um and then
until today basically that's what you
usually I mean sometimes people
miscalculate their Computing time and
then they run out of computing time and
then they don't get there that's always
a bit um annoying but some PE some
simulations are even constructed that
way because they're not interested in
today they are only interested in the
high red shift universe meaning the old
universe so um for example just yeah the
process of the first how the first uh
starts and
and Galaxy's form and then you don't
really want it to run that far down
because you have enough simulations
showing that part thank you right signal
Angel question from the
internet another question from the
Internet
is um is it possible to simulate
backwards instead of changing start
parameters until they match um what we
observe in our in our
universe
um not so not
no okay thank you uh mic number two your
question yeah so regarding research
about fitting certain uh you know like
uh simulations into our cutting of
current observations would it be
possible um how many initial States
could yield the current uh observations
that we have like not not only the sheer
number but uh because that's probably
infinite but yeah um could two
completely different initial States like
completely random and having no
connection whatsoever yield the same
state like
converge um the exact same um no I mean
two completely different initial States
uh converging into a you know into some
state after the simulation that closely
resembles our current
observations or do they have some common
pattern well I mean if the large scale
FL ation are very different then no I
don't think so but um it's a good
question I might have to think about
this all right thank you Phillip that's
unfortunately is the last question we
out of time um please give him a huge
round of applause for that excellent
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talk
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oh