[music]
[Adam] With that, let us get prepared
for the next talk by Matías Suazo,
if I have pronounced that correctly,
Searching for Dyson Spheres
with Gaia and WISE.
[Matías] Hello, everybody.
My name is Matías Suazo.
I am a first-year PhD student in Astronomy
at Uppsala University in Sweden.
I'm new in the field of study,
but I'm looking forward to learning
more about the field.
Today, I'm going to present my first project
for my PhD,
what is about assessing upper limits
on the prevalence of Dyson spheres
in the Milky Way using a Gaia and WISE.
Before I talk about my project itself,
I think I should recall some few concepts.
I know that you probably know them all,
but I think it's very educational
 to refresh them,
the first one being the notion
of the Dyson sphere.
We know that in the '60s,
Freeman Dyson theorized
that any civilization that have existed
for millions of years
could be in the need of creating
a megastructure to collect the energy
from their host star.
He also made some calculations to estimate
the time scale 
for this industrial expansion,
and he got a number of 3,000 years,
roughly, which is very short
if we compare it with star lifetimes.
However, Dyson's original idea
was very vague.
He talked about an artificial biosphere
surrounding the store.
However, we know that a monolithic sphere
would be mechanically unstable,
so different variations of this scheme
have been proposed,
and here we have a few of them.
We have the Dyson ring,
we have the Dyson swarm,
and we have a Dyson bubble.
Regardless of the structure 
we are talking about,
their potential signatures
would be the same.
First of all, we have to recall that
whatever happens in a Dyson sphere
is going to be a thermodynamic process.
As any thermodynamic process,
this harvest of energy is going to imply
some waste heat to be released to the space.
Also, the structure would partially block
some of the starlight,
so the second signature could be a drop
in the optical flux.
Finally, we have another signature,
a time-variable flux.
This is very dependent 
on the kind of the structure,
the nature of the structure.
Another concept that we have to keep in mind
is the AGENT formalism
described by Wright et al. 2014.
In this paper, it described this balanced
energy equation
applied to the alien's energy budget
and is summarizing this is in this equation.
In the left-hand side,
we have alpha that stands for radiation
collected by Dysons sphere;
epsilon, that stands for the energy
produced by other means.
The left-hand side is the collected energy
while in the right-hand side,
we have the disposable energy.
Gamma is the waste heat
while nu are other losses like neutrinos
or gravitational waves.
After giving you this bunch of information,
I would like to recall again that the goal
of this project is to estimate upper limits
on the prevalence of the Dyson spheres
in the Milky Way.
Then we can proceed to talk about
Dyson sphere models.
However, we have to make some assumptions,
and here we have them.
The standard assumptions
is that they are grey absorbers.
Then that in this energy balance equation,
alpha and gamma are equal.
That means that the radiation collected
by the Dyson sphere
and the waves heat are going to be the same,
or what comes is left,
and also that this waste heat can be modeled
as a black body with a temperature
in the range of 100 - 1,000 kelvin.
Also for the sake of simplicity,
I have redefined the gamma value
for this expression,
is just the energy of the Dyson sphere 
normalized by the external energy
before it is obscured.
I call it the covering factor as well.
With these assumptions,
it turns out that to model a Dyson sphere,
we just need two parameters.
The temperature and the gamma,
the covering factor.
Then we can apply the model
to any spectrum.
For the sake of simplicity,
I'm going to do it to this very simple
blackbody spectrum for a solar-type object.
That means a temperature of 5,800 kelvin
and a volumetric luminosity
of one solar luminosity.
Then we apply the model.
Here we apply three models,
and we get these new spectra.
In this case,
the three models are Dyson sphere
with a temperature of 300 kelvins
but different covering factors.
You can see that we recover two signatures,
one is the drop in the optical flux
and the other one is the boost
in the mid-infrared
We can also apply models
with a fixed covering factor.
In this case, 0.5, and different temperatures,
but in this image,
I would like you to keep in mind
that it is important is that
 the mid-infrared boost falls into
the detectability region
of the WISE mission.
Now I can proceed to talk about
the strategy and the data.
Since it's important to count
on very good optical data
and meaningful data,
I've been using Gaia data,
is the data that provides 
parallax distances,
positions, proper motions,
as well as three broadband magnitudes
for roughly 10^9 objects
and AllWISE data that provides
maybe infrared photometry for roughly
7.5 x 10^8 objects.
When we combine this data,
we end up with the relevant data
for roughly say 10^7 - 10^8
Milky Way stars.
Then to estimate the number,
we use the color-magnitude diagram,
but as a first approach
and just taking into account stars
within 100% in the local bubble
because the stars for this stuff,
we can ignore interstellar extinction.
The data sample
contains this number of stars,
260,000 stars.
We are checking
the color-magnitude diagrams.
Here we have color-magnitude diagrams
with a MG on the y-axis
and G-W3 on the x-axis.
The gray dots are the stars in the sample
while the yellow and red stars
are the sun 
and Proxima Centauri respectively.
We can see how different
Dyson sphere model change their position
in their color-magnitude diagram.
We can see here models
for a fixed temperature,
which is 300 at different covering factors.
Here we can see how they change
for a fixed covering factor of 0.5
and different temperatures.
The point is, you will have a color excess.
Then I have proceeded to apply the model
of a Dyson sphere
to all the stars in the sample.
We have the stars in the sample here,
these gray dots,
and we have these models.
Then I proceed to define this line
called the decision boundary.
I will not depend on the creation of this,
but you can ask later.
We say that all stars that are in this region,
in the right-hand side region
of the Hertzsprung–Russell diagram
are objects compatible
with a Dyson sphere with a temperature
in this case of 300 Kelvin
and a covering factor
higher than 0.95 in this case.
Then we count the number of stars
and we say, "Okay,
we have this number of stars consistent
with Dyson sphere."
However, we don't do this
only with a G-W3 color in the x-axis
of this Hertzsprung–Russell diagram.
We also do it with a G-W4 color.
We require for a star to be consistent
with a Dyson sphere
 if it has an excess in both,
in G-W3 and G-W4 color.
In this particular,
we say that we have nine objects
that are consistent with this Dyson sphere
and a covering factor of 0.95
for whose friction is this value,
3.4 x 10^-5 roughly.
We did execute the same for a huge range
of covering factors
and temperatures of Dyson spheres,
and we gather all this information
in this plot called the exclusion map.
In this plot on the x-axis,
we have the temperature of the Dyson sphere
and we have the covering factor
on the y-axis.
The color represents the fraction
that are consistent with this type
of Dyson sphere.
You can see that for low covering factors,
the fraction is very close to one,
and that happens because to have
a low covering factor is equivalent
to have a transparent Dyson sphere.
All the stars are compatible
with transplant Dyson spheres.
Also, when we have very close stars,
also the fraction is the same,
is close to one, but that happens
because when we have very, very close
Dyson sphere models,
the radiation falls in the far-infrared
and is not in the detectability region
of the WISE bands.
However, we got very interesting limits
in this region for covering factors
between point 0.1 and above
and temperatures between
100 Kelvin and 600 Kelvin.
Then I proceeded to apply
to do exactly the same
but extending now the sample
to stars within 200%. res
In this case, the sample contains roughly
two million starts which is a lot
and this is the [?]
the same as before we get,
huge fractions for what we call 
hot Dyson spheres
and huge fractions for low coverage.
We also have a tiny fraction
in this particular region.
However, now we have too many stars
and too many candidates
that are consistent with Dyson spheres,
so we decided to to use
complementary data.
In this case, we use two mass data,
and we reduce the sample
from roughly 2 million to 1.5 x 10^6 stars,
and we included a new condition
for Gaia and WISE.
Dyson sphee condition is to have
a Nexus in G-W3 and G-W4 color,
but now we added the condition of
 not having the sources
or the candidates 
accessing the needing for it.
We end up with this new exclusion map.
Actually, similar to the previous one,
but the positions of the of these 
limits are shifted by one order of magnitude.
Then I proceeded to check
what kind of sources we have in this
in this region for this that are consistent
with this Dyson sphere for these range
of temperatures,
and this range of covering factors.
Here we have a few examples.
Most of them are actually stars
embedded in nebular regions,
and that's the reason why they have
[?] for excess.
Also, we found some ghosts
that are due to diffractions in the camera.
Also, we found some natural light sources
of medium for emission.
Like the Tauri stars
and cataclysmic variables.
That would be all for the moment,
but instead of having a conclusion slide,
I would like to mention the future,
what will I intended to do.
First, this works wants to cover
all the stars in the whole
and Gaia [?] sample.
That means this number,
between 10^7 and 10 ^ 8 objects.
We also plan to to improve the upper limits
by including the G-W2 and G-W1 colors.
Once we have all the candidates,
all the sources consistent
with a specific type of Dyson sphere,
we plan to release a candidate list.
Also, we plan to check the nature
of the candidates by looking
for auxiliary data on other databases.
That would be all.
 Thank you very much.
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