Welcome to today's deep dive. If you're joining
us, you are likely the kind of person who doesn't
just want to know what happened, but exactly
how it happened, whether you're using this time
to catch up on the cutting edge of physical cosmology
or. prepping your brain for complex problem solving,
or you just have this insatiable curiosity about
our place in the cosmos, you are exactly where
you need to be. Absolutely. Today, our mission
is to understand how humanity maps the completely
unmappable. We are doing a deep dive into simulating
the universe, specifically looking inside the
illustrious project and the supercomputer's mapping
cosmic evolution. It's a massive topic. It really
is. We're going to unpack dark matter, dark energy,
galaxy formation and try to wrap our heads around
how scientists have managed to simulate the entire
history of the universe all 13 .8 billion years
of it inside a machine. And we are using the
detailed source material on the illustrious project
as our roadmap today. It is truly a monumental
achievement in astrophysics. Over the course
of this deep dive, we're going to break down
the timeline, the staggering computing power
required to pull this off, the underlying physics
encoded into the software, and the highly specialized
spin -off projects that this original simulation
spawned. Yeah, projects like Illustris TNG and
Auriga, which are just fascinating. Exactly.
What makes this so compelling is that it represents
a massive paradigm shift in how we do science.
I mean, for centuries, astronomy was purely observational.
You just look up. Right, you build a bigger telescope,
you look up, and you try to deduce the rules
of the universe based on what you see. But the
illustrious project... flips that entirely. It
is experimental computational astronomy. OK,
let's unpack this methodology. Imagine trying
to bake a cake, right? But the recipe takes 13
.8 billion years. It requires 25 terabytes of
RAM. And the ingredients are things like dark
matter and supermassive black holes. That is
a very stressful baking show. Right. But instead
of looking up at the finished product, the finished
cake, you start with the raw ingredients and
the laws of physics. put them in a digital box,
and see if you can bake a universe that actually
matches what we see through the telescopes. Exactly.
And the underlying goal isn't just to make a
visually stunning digital planetarium. This is
about establishing a rigorous predictive theory
of galaxy formation. By building a comprehensive
physical model and running it forward, researchers
are testing our fundamental understanding of
reality. They want to see if the math actually
works. Precisely. They want to know if the physics
we think govern dark matter, dark energy, and
standard matter are actually correct when applied
on a cosmic time scale. Okay, but on the surface
that almost sounds circular. Let me play Devil's
Advocate for a second here. Go for it. If these
scientists specifically key figures mentioned
in our source, like Mark Vogelsberger at MIT
and Volker Springel at the Max Planck Institute
for Astrophysics, if they are writing the code
and they are programming the simulation using
the physics rules they already believe are true,
aren't they just building a massive echo chamber?
That's a really common critique. I mean, aren't
they guaranteed to just get a universe that perfectly
matches their preconceptions? That is the exact
trap they had to avoid. And it's a brilliant
question because it strikes at the heart of why
this simulation is so incredibly difficult. The
way they avoid the echo chamber is by strictly
separating the micro rules from the macro results.
Meaning they don't program a galaxy to look like
a galaxy. Precisely. They do not write a single
line of code that says make a spiral galaxy here
or make an elliptical galaxy there. They only
program the foundational microscopic rules of
physics. Like gravity. Right. They code in the
gravitational constant. They code the thermodynamic
properties of gas. They code the rate at which
gas cools and condenses to form stars. They drop
in dark matter and dark energy based on the parameters
measured by the cosmic microwave background.
The echo of the Big Bang. Exactly. They set up
these initial basic conditions as they existed
right after the Big Bang, hit run, and let 13
.8 billion years of virtual time unfold. So the
macroscopic structures, the massive spiraling
galaxies, the galaxy clusters, the cosmic web,
all of that has to emerge entirely on its own,
organically, just from the micro rules interacting
over time. It's called emergent complexity. If
they run the simulation and the resulting virtual
universe is filled with galaxies that are way
too massive or galaxies that don't cluster together
the way real ones do, they don't tweak the galaxies.
Because that would be cheating. Right. They realize
that their understanding of the fundamental microphysics
must be flawed. It serves as an unforgiving reality
check. If the virtual universe doesn't mirror
the observable universe, it means our textbook
theories need adjusting. That makes perfect sense.
The simulation is a stress test for our physics.
Which brings us to the actual ingredients they
put into this digital box. When you are simulating
physical cosmology, you can't just throw in some
gravity and a bunch of stars and call it a day.
No, the universe is much messier than that. It
really is. The simulation has to include the
chaotic stuff. We're talking about star formation,
supernova explosions, the formation of supermassive
black holes, and of course, the invisible scaffolding
of the universe, dark matter and dark energy.
Out of all those ingredients, the one that often
surprises people the most is the role of supermassive
black holes in supernovae. If we want to understand
how a galaxy forms, we have to understand a concept
called feedback. Feedback. Because when we picture
gravity, we usually just picture things falling
inward. Gravity pulls matter together. So if
a universe only had gravity, you'd eventually
just get incredibly dense, dead clumps of matter.
Everything would just collapse into itself. There
has to be a push to counteract that pull. That
push is the feedback. And it is arguably the
most difficult thing to model correctly in a
universe simulation. Let's look at supernovae
first. When a massive star reaches the end of
its life, It doesn't just quietly wink out. It
explodes. It detonates in a supernova, one of
those violent explosions in the universe. This
explosion sends shockwaves out into the surrounding
interstellar gas, heating it up and literally
blowing it away. And since stars form from cold,
dense gas, if a supernova blows all that gas
away and heats it up, it's effectively shutting
off the assembly line for new stars in that area.
Exactly. It regulates star formation. Without
supernova feedback, galaxies and simulations
convert their gas into stars way too fast. They
burn out. They do, resulting in virtual galaxies
that are unnaturally bright and overly packed
with stars compared to the real universe. So
the simulation has to constantly track where
massive stars are forming, calculate when they
die. and model the subsequent thermal and kinetic
energy injected back into the gap. And then you
scale that up to the absolute extreme with supermassive
black holes. We usually think of black holes
as these ultimate cosmic vacuum cleaners that
just eat everything. But the reality of a feeding
black hole is profoundly explosive, isn't it?
It is. When gas falls toward a supermassive black
hole at the center of a galaxy, it forms an accretion
disk. This material swirls inward at a significant
fraction of the speed of light. The friction
there must be insane. It's incomprehensible.
The friction and magnetic forces within this
disk generate massive amounts of heat and radiation.
Furthermore, complex magnetic interactions can
channel some of that infalling material into
massive twin jets that blast outward into space.
So while a black hole is consuming some matter,
it's violently ejecting vast amounts of energy
outward. The source calls this active galactic
nucleus, or AGN, feedback. Correct. And AGN feedback
is crucial for regulating the largest galaxies.
Without supermassive black holes actively pushing
back against the crushing weight of gravity,
the largest galaxies in the universe would continue
to grow out of control, becoming vastly larger
than anything we actually observe. They would
just eat everything around them. Right. The illustrious
project had to encode the mathematics of this
energetic feedback, the push and pull, the expanding
and contracting to create the delicate, chaotic
balance that allows beautiful, intricate structures
to to form and stabilize over billions of years.
It's basically a cosmic ecosystem. The predators,
the black holes, and supernovae keep the population
of stars in check so the galaxy as a whole can
survive and evolve naturally. But simulating
an ecosystem of that scale, tracking the gravity
of dark matter, the expansion driven by dark
energy, the fluid dynamics of gas, and the localized
explosions of supernovae over 13 .8 billion years.
That requires a machine that borders on science
fiction. That requires computational brawn that
most people have a hard time conceptualizing.
You cannot do modern physical cosmology on a
standard computer. Definitely not. The illustrious
simulation relied on top -tier supercomputers.
Specifically, the source mentions the Curie supercomputer
located at the CEA in France and the SuperMUC
supercomputer at the Leibniz Computing Center
in Germany. Let's put some numbers to this because
the scale is just phenomenal. To run the main
Illustrious simulation, it took 19 million CPU
hours. They used 8 ,192 CPU cores running in
parallel. And the peak memory usage during this
run hit 25 terabytes of RAM. That is a staggering
amount of memory. Just to translate that for
you listening. If you tried to run this exact
simulation on a single high -end desktop processor,
you would be waiting over 2 ,000 years for the
progress bar to reach 100%. And that 2 ,000 -year
figure assumes your machine doesn't crash, overheat,
or experience a hardware failure, which is a
major logistical hurdle when dealing with compute
times of this magnitude. When you are running
a simulation across 8 ,192 cores for months on
end, the physical reality of the hardware becomes
a factor. Right. Computers get hot. Exactly.
Processors generate heat. They require massive
cooling infrastructure. Individual nodes can
fail. The software has to be robust enough to
handle the sheer physical strain it puts on the
data center. But the real magic trick is how
you get 8 ,192 separate computer brains to perfectly
collaborate on a single universe without stepping
on each other's toes. I know in supercomputing,
you can't just divide a task easily if everything
is connected. If a supernova explodes in processor
number 500, the shockwave is eventually going
to hit the gas being calculated by processor
number 600. They have to communicate instantly.
This is where the MPI approach comes in. MPI
stands for message passing interface. It is a
standardized means of exchanging messages between
multiple computers running a parallel program
across distributed memory. Imagine 8 ,192 cartographers,
all standing shoulder to shoulder, each tasked
with drawing a small piece of a massive dynamic
map. And the map is constantly changing. Right,
so cartographer A needs to constantly tell cartographer
B, hey, a massive hot gas just crossed the border
from my section into yours. MPI is the highly
optimized language and protocol they use to shout
these updates to each other. millions of times
a second. That sounds chaotic. It would be, without
the interface. Minimizing the latency, the delay
in that communication, is critical. If one core
gets bogged down calculating a particularly complex
galaxy collision, the other 8 ,191 cores might
have to sit idle waiting for it to catch up,
wasting precious compute time. So the software
has to be incredibly smart about how it distributes
the workload, ensuring no single processor becomes
a bottleneck. Which brings us to the brains of
the operation, the actual code running on those
machines. The program used for Illustris was
written by Volker Springel, and it's called a
REPO. Springel had previously authored a widely
used astrophysics code called Gay -Gidaro, but
a REPO represented a monumental leap forward
in how we simulate fluid dynamics in space. Before
we get into the heavy math of Arepo, I just have
to mention a fantastic piece of trivia from the
source. The name Arepo isn't an acronym. It's
actually derived from the Sator Square, which
is an ancient Latin palindrome. Yes, the word
square. It's a square containing five words,
Sator, Arepo, Tenet, Opera, Rotus, that reads
the same top to bottom, bottom to top, left to
right, and right to left. It's been found in
ruins all over the Roman Empire from Pompeii
to Britain. I just love the juxtaposition there.
You have the most advanced, bleeding -edge astrophysics
code in human history, built to unravel the mysteries
of dark matter, and it's named after a 2 ,000
-year -old linguistic puzzle. It's a wonderful
nod to the enduring human desire to find patterns
and structure in the universe. And structure
is exactly what the Arepo code is designed to
handle. At its core, Arepo was built to solve
the coupled equations of gravity and hydrodynamics.
We talked briefly about gravity, but hydrodynamics
is where this gets incredibly complex. When we
look up at the night sky, we tend to think of
space as a vacuum, entirely empty except for
solid planets and burning stars. But that's not
accurate, is it? Not at all. The space between
stars, and especially the space between galaxies,
is filled with the diffuse medium of gas, primarily
hydrogen and helium. Over cosmic time scales
and vast distances, this gas doesn't act like
isolated particles. It acts like a fluid. Like
an ocean. Very much like that. It flows in massive
cosmic winds. It pools in gravitational wells.
It creates eddies and shockwaves. Hydrodynamics
is the study of fluids in motion. To simulate
a universe, you must accurately simulate fluid
dynamics on a galactic scale. And simulating
fluids is notoriously difficult. Anyone who has
ever watched an older video game struggle to
make water look realistic knows that calculating
how a liquid or gas moves and interacts with
itself takes massive processing power. Now imagine
simulating a fluid that spans billions of light
years, where its density can vary by factors
of millions depending on whether it's in the
deep void of space or inside a collapsing star
-forming cloud. So how does a repo do it? The
text mentions a highly specific mathematical
technique called a moving Voronor tessellation.
This sounds intimidating, but it is actually
a beautiful concept once you visualize it. Let's
break it down, because this is really the secret
sauce of the illustrious simulation. Historically,
cosmologists use two different methods to simulate
fluids. The first is an Eulerian approach, which
involves throwing a fixed rigid 3D grid over
the universe. Imagine a giant cosmic jungle gym.
You calculate how much gas moves in and out of
each square box in the grid. The problem with
a fixed grid, I imagine, is resolution. The universe
is mostly empty space. If your grid boxes are
too big, you can't see the fine details of a
galaxy forming. But if you make the boxes small
enough to see a galaxy, you suddenly have trillions
of empty boxes in the cosmic voids that your
computer is wasting time calculating for no reason.
Exactly. It's incredibly inefficient. You are
burning CPU hours calculating nothing. The alternative
method historically used was Lagrangian, specifically
Smoothed Particle Hydrodynamics, or SPH. In this
method, there is no grid. Instead, you represent
the gas as millions of individual virtual particles,
and you track where they move. This is great
because your computing power naturally follows
the matter. But I'm guessing SPH has its own
drawbacks. It does. It struggles with fluid instabilities
and sharp shock waves. When two gas clouds smash
into each other, SPH sometimes artificially smooths
out the collision, losing the chaotic turbulent
details that are essential for mixing the gas.
So, a fixed grid is bad at following the matter,
and floating particles are bad at capturing sharp
fluid dynamics. Volcker's spring oil needed a
third way. And that is the moving Voronoi tessellation.
Right. A Voronoi diagram is a way of dividing
space into distinct regions based on distance
to a specific set of points. The classic example
is mapping cell phone towers. Okay, I can picture
that. If you put 100 cell towers on a map, a
Voronoi diagram draws boundaries around each
tower, creating a polygon. Everywhere inside
a specific polygon is closer to that tower than
to any other tower. Okay, so take that flat map
of cell towers, make it three -dimensional, and
apply it to the universe. Exactly. A repo casts
a brilliant mathematical net of these 3D Voronoi
cells over the entire virtual universe. But here's
the genius part. The net is not rigid. The points
that define the cells are allowed to move with
the flow of the cosmic gas. Oh, wow. So as gravity
pulls gas together to form a galaxy, the cells
of this mathematical net flow inward alongside
the gas, shrinking and clustering tightly together
where the density is highest. Exactly. It's an
adaptive dynamic mesh. In the empty voids of
space, the cells stretch out and become enormous,
saving computing power. But in the dense, turbulent
center of a forming galaxy, the cells become
incredibly tiny and numerous, providing ultra
-high resolution right where the physics are
most complex. That is so smart. And because it's
still technically a mesh, it handles fluid dynamics,
turbulence, and shock waves beautifully. The
moving Voronoi tessellation gave Arbo the best
of both historical methods without the fatal
drawbacks of either. It is an elegant, dynamic
solution to mapping the unmappable. It allows
the simulation to breathe, contracting its focus
where the action is, and expanding where space
is empty. They took this code, fired up the supercomputers,
and let it run for 19 million CPU hours. They
built a 13 .8 billion year universe. And then
they did something that I think defines the best
of modern science. They gave the universe away.
The commitment to open science here is remarkable.
In April 2015, just 11 months after the foundational
papers describing the illustrious results were
published, the project team publicly released
the data products from all their simulations.
They didn't lock it behind a paywall. No, and
they didn't hoard it for their own institution's
exclusive use. We need to quantify what giving
away a universe looks like. We are talking about
over 230 terabytes of cumulative data volume.
During the simulation run, they couldn't just
save a single video file of the whole thing.
Instead, they took full snapshot particle data
at 135 distinct time points throughout the 13
.8 billion years, plus one final snapshot, making
a total of 136 snapshots. Think of it like a
time lapse of the cosmos. These snapshots contain
the precise location, velocity, mass, and temperature
of billions of resolution elements at that exact
moment in cosmic history. But raw data of billions
of particles isn't incredibly useful on its own.
It's just a wall of numbers. The team went a
step further and processed this data into usable
tools for the wider astronomical community. They
included things called group catalogs of individual
halos and sub -halos. For you listening who might
not know, what exactly is a halo in this context?
In cosmology, a halo refers to a massive clump
of dark matter. Dark matter doesn't interact
with light, but it has mass, so it exerts gravity.
In the early universe, dark matter clumped together
into these vast, invisible halos. The gravity
of these dark matter halos is what pulled in
the normal gas and dust, eventually sparking
star formation. So the dark matter halo is the
invisible bowl and the galaxy is the soup that
collects inside it. That's a great way to visualize
it. So a halo is the main dark matter structure,
and a sub -halo is a smaller clump of dark matter
residing within it, which usually corresponds
to a single galaxy or a satellite galaxy. By
releasing these group catalogs, the illustrious
team basically provided a full census of every
single dark matter bowl and every single galaxy
soup in their virtual universe, categorized by
mass, size, and star formation rate. And they
also included merger trees. I love this concept.
A merger tree is exactly what it sounds like.
It's a genealogical family tree for galaxies.
Galaxies don't usually form in isolation. The
hierarchical model of structure formation dictates
that small things merge together to form bigger
things. Small clumps of dark matter and early
stars smash together to form dwarf galaxies.
Those dwarf galaxies get pulled together by gravity
and merge into massive spiral galaxies like our
Milky Way. And eventually spiral galaxies can
collide to form giant elliptical galaxies. Precisely.
A merger tree allows a scientist to pick a massive
galaxy in snapshot 135 the present day and trace
its ancestry backward through time. They can
see exactly which smaller galaxies collided,
when they collided, and how those collisions
triggered burst to star formation or fed the
central black hole. It's tracing the lineage
of a cosmic structure over billions of years.
And the accessibility of this data is a game
changer. Releasing 230 terabytes of data is one
thing, but expecting researchers around the world
to have the local storage and computing power
to download and analyze it is unrealistic. So
the illustrious team built a web -based API and
application programming interface. Which effectively
means you don't need a supercomputer in Germany
to study this universe. A graduate student with
a standard laptop in a developing country or
a researcher at a small university without a
massive funding grant can write a script, connect
to the API via the internet, run a specific search
query directly on the Illustra servers and download
just the specific subset of data they need. It
entirely democratizes the cosmos. It allows thousands
of researchers to test their own unique hypotheses
about galaxy rotation, black hole growth, or
dark matter distribution against a state of the
art simulation. It accelerates the pace of discovery
across the entire field because the bottleneck
of access has been removed. It's a beautiful
model for how science should be shared. Now,
we've been deep in the weeds of APIs, terabytes
of RAM, and supercomputing architecture, but
I want to pivot to something that highlights
the broader cultural impact of this achievement.
In December 2018, the illustrious simulation
received a very unique honor from a surprisingly
old -school institution. The German Postal Service
recognized the project with a special series
postage stamp. It is a wonderful, almost poetic
contrast. On one hand, you have 230 terabytes
of the most complex, dynamically generated digital
information ever produced by humanity. And on
the other hand, it is commemorated by being printed
on a tiny physical square of paper that you lick
and stick on a letter. I think it speaks volumes
about how scientific milestones transcend academia.
When a physics simulation gets put on a postage
stamp, it means it has entered the cultural zeitgeist.
It's a physical stamp of approval for a purely
virtual universe. And I think a huge part of
why it captured the public imagination is the
visual aspect. The data visualizations generated
by illustris are absolutely breathtaking. They
really are. When you render the gas density,
temperature, and metallicity of the illustris
universe, it looks incredibly authentic. You
see the glowing, delicate filaments of the cosmic
web connecting massive glowing nodes of galaxy
clusters. You see the distinct spiral arms of
virtual galaxies rendered in vibrant colors that
map to real physical properties. It bridges the
gap between abstract math and human intuition.
When people can literally see the output of Arepo's
hydrodynamics, it makes the staggering complexity
of physical cosmology feel tangible. But the
scientific process doesn't stop at a successful
proof of concept or a commemorative stamp. The
original illustrious simulation was a triumph,
but it wasn't perfect. Right, there were flaws.
There were discrepancies between the simulated
universe and the real one. Certain populations
of galaxies didn't match perfectly, and the physics
of black hole feedback needed refinement. Which
is exactly how science is supposed to work. You
build a tool, you push it to its absolute limits
to see where it breaks, and then you build a
better tool. Once they proved that the IREPO
code could construct a universe, the team didn't
just pat themselves on the back and move on.
They initiated a series of highly specialized
incredibly ambitious spin -off projects to ask
deeper, more complex questions. If we consider
the original Illustris simulation as a broad
foundational map of the world, the spin -offs
are like using specialized satellite imaging
to zoom in on specific topographies, weather
patterns, or demographics. The first and most
prominent follow -up was Illustris TNG, which
literally stands for The Next Generation. This
project was presented in July 2017, again led
by Volker Springel, alongside a broader team
of scientists from in Germany and the U .S.?
With TNG, they significantly upgraded the physics
programmed into the simulation. The most crucial
addition was a field of physics known as magnetohydrodynamics.
And we talked about hydrodynamics, the flow of
fluids. Adding the magneto prefix implies we
are now tracking magnetic fields. Why is that
necessary? Are magnetic fields really that important
in the vacuum of space? They are profoundly important.
While space is a vacuum by earthly standards,
the diffuse gas that permeates the cosmos is
often ionized, meaning the atoms have been stripped
of electrons, turning the gas into a plasma.
Plasmas are highly conductive and interact strongly
with magnetic fields. So the magnetic fields
can actually shape how the gas flows. Exactly.
Magnetic fields can provide pressure that supports
gas against gravitational collapse. They influence
how cosmic rays travel through a galaxy. And
crucially, they play a massive role in how supermassive
black holes accrete matter and launch those massive
powerful jets we discussed earlier. In the original
illustrious simulation, the fluid dynamics were
purely kinetic and thermal. By adding that ghetto
hydrodynamics to illustrious TNG, they made the
cosmic fluid vastly more realistic. But adding
magnetic fields to the moving Voronoi tessellation
means the mathematical complexity just went through
the roof. It did. Tracking the strength and direction
of magnetic fields across billions of moving
computational cells requires an immense leap
in processing power. Which explains the hardware
upgrade. The flagship simulation of this new
project was run on the Hazel Hen machine at the
High Performance Computing Center in Stuttgart,
Germany. They scaled up from the original 8 ,192
computer cores to employing up to 25 ,000 computer
cores working in parallel. And continuing their
commitment to open science, they released the
TNG data publicly in December 2018. But this
time, they made it even more accessible by including
a JupyterLab interface. For listeners who might
not be in the computer science field, JupyterLab
is a web -based interactive development environment.
It allows researchers to write and execute code,
like Python, directly in their browser. They
can analyze the TNG data right on the project
servers without having to download massive data
sets or set up complex coding environments locally.
It lowered the barrier to entry even further.
Illustris TNG was a massive step forward, but
it was still simulating a large representative
volume of the universe. What if you want to understand
something very specific, like the exact history
of our own home galaxy? That brings us to the
first of the highly specialized spin -offs, the
Auriga Project. The Auriga Project is fascinating
because it shifts the focus from the macro to
the micro. The source notes that Auriga consists
of high -resolution zoom simulations of Milky
Way -like dark matter halos. Break down that
term for us. Zoom simulation. Does that mean
they just take the data from the main simulation
and look really closely at one part? Not exactly.
In a full box simulation like Illustris, the
resolution, the smallest detail you can accurately
model, is limited by the sheer size of the universe
you're trying to fit into the computer's memory.
If you want to study the fine details of how
a galaxy's spiral arms form, or how a galaxy
cannibalizes smaller dwarf galaxies over time,
the full box resolution isn't sharp enough. It's
like trying to read a license plate and a satellite
photo of an entire continent. Right, so a zoom
simulation uses a clever trick. They run a low
resolution simulation of large volume of space
and they identify a specific dark matter halo
that has roughly the same mass and environment
as our Milky Way. Then they rerun the simulation
from the Big Bang, but they concentrate almost
all of the computing power and millions of high
-resolution particles specifically into that
one small region of space. Well, the rest of
the universe surrounding it is simulated at a
very low resolution just to provide the correct
gravitational background. Exactly. It allows
them to study the incredibly intricate formation
history of a Milky Way analog, its spiral structure,
its central bulge, its surrounding halo of stars
and breathtaking high definition, helping us
understand how our own galactic backyard came
to be. That is brilliant. OK, moving down the
timeline. In 2021, we see the introduction of
a spinoff called Thesen, and this one tackles
a very specific and frankly mysterious era of
cosmic history. The source describes Thesen as
a radiative transfer version of illustris TNG
designed to explore the epoch of reionization.
I think we need to define some terms here, starting
with the epoch of reionization. What is that?
To understand reionization, we have to go back
to the Cosmic Dark Ages, roughly 380 ,000 years
after the Big Bang. At that time, the universe
had expanded and cooled enough for protons and
electrons to combine and form neutral hydrogen
atoms. Which means the universe was no longer
a hot, glowing plasma. Right. It became filled
with a thick, opaque fog of neutral hydrogen
gas. There were no stars, no galaxies, no sources
of light. hence the Dark Ages. But eventually,
gravity pulled enough gas together to ignite
the very first stars and the first primitive
galaxies. And when those stars turned on, they
started pumping out ultraviolet radiation. Yes.
And those high -energy UV photons slammed into
the surrounding neutral hydrogen fog, tearing
the electrons away from the protons. This process
is called ionization. As more stars formed, these
bubbles of ionized transparent gas grew and merged
until eventually the entire universe was reionized.
It was the dawn of light. The fog lifted and
the universe became transparent to light, which
is why we can see distant galaxies today. That
is an incredibly poetic moment in the history
of the cosmos, but simulating it requires a new
type of physics, which the text calls radiative
transfer. Tracking the gravity and fluid dynamics
of the gas is hard enough. Radiative transfer
requires calculating how individual packets of
light photons travel through that moving fluid,
how they are absorbed by the gas, and how that
absorption heats and ionizes the gas, which in
turn changes the pressure and the fluid dynamics.
It's a deep, complex feedback loop between light
and matter. Thiessen was built specifically to
model this dawn of light and understand how the
first stars transformed the entire universe.
From the dawn of light, we move to the absolute
giants of the cosmos. In 2022, the Millennium
TNG project was launched. The text notes that
it employs the galaxy formation model in a larger
cosmological volume to explore the massive end
of the halo mass function for detailed cosmological
probe forecasts. There's a lot of dense terminology
there. Let's start with the halo mass function.
Simply put, the halo mass function is a demographic
census of the universe. It is a mathematical
curve that tells you how many dark matter halos
exist at various different masses. So it tells
you that there are trillions of small halos,
billions of medium halos, and only a few massive
ones. Correct. But to accurately plot the massive
end of that curve to study the absolute largest
dark matter structures in the universe, you run
into a statistical problem. Because massive halos
are extremely rare, you won't find many of them
in a small or even medium sized simulation box.
If you want to study the demographics of billionaires,
surveying a small town won't work. You have to
survey an entire country. Perfect analogy. Millennium
TNG scaled up the volume of the simulation drastically.
They needed an enormous virtual universe to ensure
they captured a statistically significant sample
of these extremely rare gigantic structures.
They want to understand how these titans form
and how they cluster, because the exact number
of these massive halos is highly sensitive to
the fundamental properties of dark energy and
the total mass of neutrinos. By comparing the
massive end of the halo mass function in the
simulation to what telescopes like Euclid or
the Nancy Grace Roman Space Telescope will observe,
scientists can precisely calibrate our cosmological
models. And that scales perfectly into the final
spin -off mention, TNG cluster, introduced in
2023. This is a suite of high -resolution zoom
-in simulations specifically targeting galaxy
clusters. If Millennium TNG was casting a wide
net to find where the giants live, TNG clusters
of putting those giants under a microscope. Galaxy
clusters are the largest gravitationally bound
objects in the universe. We are talking about
structures containing hundreds or even thousands
of individual galaxies all swarming around inside
a colossal dark matter halo permeated by incredibly
hot x -ray emitting gas. The physics in an environment
like that must be incredibly extreme. You have
galaxies moving at millions of miles an hour,
smashing into each other, being stripped of their
gas by the sheer friction of moving through the
cluster environment. It is the ultimate cosmic
mosh pit. TNG Cluster uses the zoom technique
we discussed earlier to resolve the violent,
complex astrophysics happening inside these massive
clusters. How does a supermassive black hole
in the central galaxy of a cluster manage to
heat up gas that is millions of light years away?
How do galaxies survive plunging through the
center of the cluster? These are the frontier
questions of astrophysics today. So let's pull
all of this together. We started with the desire
to map the unmappable. We looked at a single,
mathematically elegant piece of code called a
repo, named after a Roman palindrome. From that
foundation, teams of brilliant scientists utilizing
tens of thousands of supercomputer cores, millions
of CPU hours, and an incredible grasp of gravity,
hydrodynamics, and magnetic fields managed to
simulate a 13 .8 billion year universe. They
simulated the invisible scaffolding of dark matter,
the chaotic explosion of supernovae, the terrifying
feedback of supermassive black holes, the intricate
dance of fluid dynamics, the dawn of light during
reionization, and the assembly of the largest
clusters in the cosmos. And then, instead of
locking it away, they opened the doors. They
provided APIs and web interfaces, handing a 230
terabyte digital universe to the global scientific
community. It sparked a golden age of computational
cosmology, earning a place in cultural history
right down to a commemorative postage stamp.
and its TNG successors are more than just a map
of stars. They are a testament to human ingenuity.
By combining the complex math of microphysics,
they created a sandbox for reality. They built
an environment where we can test the very laws
of nature and watch the consequences unfold and
fast forward. And for you listening to this,
whether you are trying to conceptualize the vast
cosmic web or you are just looking for a bit
of profound inspiration before you tackle your
next big project, the ultimate takeaway here
is the astonishing power of modeling complex
systems. Think about the implications. If human
beings can collaborate, write code, and build
machines powerful enough to simulate 13 .8 billion
years of galaxy formation down to the magnetic
fields and the cooling rates of gas, what other
massively complex, seemingly unsolvable problems
can we model, understand, and ultimately solve
here on Earth? It is a deeply empowering thought.
But in the spirit of this deep dive, I want to
leave you with an idea that is perhaps slightly
more provocative to mull over. We've discussed
the unbelievable detail of the illustrious simulation.
It is so complex that researchers require merger
trees just to track the billions of virtual cosmic
events and genealogies over vast stretches of
time. It is, for all intents and purposes, a
functioning universe within a machine. The universe
constrained by 25 terabytes of RAM. Indeed. But
consider the trajectory of our technology. If
a supercomputer in Germany in the 21st century
can generate 136 distinct time snapshots of a
virtual reality that remarkably mirrors our own
observable universe, what happens in a thousand
years, or a million years? If we can simulate
reality this well now, how do we know for certain
that our own universe, with all its galaxies,
dark matter and cosmic webs, isn't just the ultimate,
infinitely high -resolution simulation running
on some unimaginable cosmic supercomputer? So
that is the perfect mind -bending thought to
end on. A reality check for reality itself. Thank
you so much for joining us on this deep dive
into the illustrious project and the incredible
science of simulating the cosmos. Keep asking
questions, keep wondering at the scale of it
all, and we will catch you on the next one.