The search for extraterrestrial intelligence is an exercise in difficulty.
It’s tempting to say that after decades of searching, since Frank Drake’s Project
Ozma in 1960 to now, that since we’ve never seen any signals that we can unambiguously
state are of alien technological origin they just must not be out there.
But the reality is that the signals we search for today are going to necessarily be subtle
and difficult to pick up.
Not impossible, but we’ve also only barely searched these with targeted SETI radio telescope
searches.
But it’s not just a matter of pointing a radio telescope at as many star systems as
you can, there are as many as 200 billion of them in this galaxy alone, that’s a lot
of searching, but you also have to keep checking them across time.
When you don’t know when aliens transmit, or what frequency they transmit at, or when
they repeat, you’ve got a lot of work ahead, most of which is yet to be done.
What we do know reasonably though is that the original idea of a huge beacon blasting
out radio energy as a contact signal seems to not be happening in the galaxy.
We had to look, but the beacons of the original Cocconi and Morrison paper that set SETI in
motion were probably always a long shot for anything but a supercivilization due to the
energy requirements involved.
And there has also been the progression of technology.
The Big Ear radio telescope that detected the famous and still unexplained Wow signal
had a receiver that only had 50 channels near 1420 mhz, each being a slice only 10 kilohertz
wide over a tiny area of the radio spectrum.
That was a very, very tiny area of the radio spectrum based around the hydrogen line idea,
that putting a signal near where neutral hydrogen emits radio is a natural place for a contact
signal since all scientists doing radio astronomy in the galaxy know about that 1420 mhz area.
But the reality is that aliens could be transmitting at any frequency, especially if those transmissions
are their internal communications not intended to say hello to us that we happen to be able
to eavesdrop on.
As a result, SETI receivers now cover millions of channels and large areas of the radio spectrum.
We are much better at picking up signals than at any other time.
But here too is a problem, that creates a huge amount of data and that data must be
sifted through.
In the past, the SETI@Home project used the resources of the public participants' computers
as a screensaver to crunch the data.
That no longer exists, but this task of data sifting continues now with computer programs
that automatically sift the data and pick out signals of interest which the scientists
then follow up on.
One of the major programs used is known as turboSETI.
This is a standard algorithm and does not employ machine learning, you basically tell
it what human interference looks like and it carries out its instructions as to filtering
it out.
It works, but it’s not perfect and signals of interest do get missed.
Yet it produces a lot of signals that are of interest initially, but most of them being
due to interference it wasn’t familiar with.
Humans then had to go in and improve the program.
This is still a problem in SETI, one of the more noteworthy candidates in recent years
was BLC1, which was a strong candidate signal, but ultimately proven to be interference no
one had seen before.
But in any case, the data sifting can’t be done manually, nature produces all sorts
of radio signals and human interference from our own transmissions is an ever present problem.
There can initially be tens of thousands of signals.
So each signal in a typical SETI experiment data set never gets looked at by a human,
and thus gets filtered out by a computer program designed to spot and eliminate those signals.
And with that, there is the risk that a signal of alien origin could be missed.
This is complicated stuff because there are differences in how these programs are written
depending on a number of variables, and indeed the type of radio telescope used to collect
the data.
There is a difference between a single dish radio telescope and array telescopes and how
the data is processed.
But work is proceeding, and a new way of filtering signals using machine learning has both shown
promise, and indeed has yielded eight new signals of interest that were missed in previous
searches of that particular data set.
In a paper by Peter Ma and colleagues, link the description below, they detail a new way
of searching SETI datasets employing machine learning.
The data set they searched was about 480 hours of data taken by the Green Bank radio telescope
in West Virginia taken as part of the privately funded Breakthrough Listen initiative.
This comprised 810 nearby star systems,
The new program broke the data down into snippets and searched them for signals of interest.
It found millions, but rated them on how confident it was on them actually being an interesting
signal.
It then learned from that and organically learned how to filter signals.
As a result, the team was able to throw out 90 percent of the signals as probable earth
interference or natural phenomena, and they avoided areas of the spectrum which ran between
1 and 2 gigahertz that were known to have heavy earth radio traffic.
That process still left over 20,000 signals to do a second check on, but what was of note
is that the result was actually less than what a program like turboSETI would have produced.
This means that the new program is better at removing false positives.
And that’s where this gets interesting.
Even though it’s a more reliable program, it still produced 8 signals of interest after
all was said and done, and these signals had not been caught by previous searches of that
particular data set.
And here’s the kicker, while there were eight signals, they came from only 5 nearby
stars meaning that 3 of the targets actually produced two signals of interest, albeit at
different frequencies.
Because of the difference in frequency they were treated as separate detections, but it’s
difficult to ignore two signals on different areas of the dial coming from the same star
system.
These star systems are very close, ranging between 30 and 90 light years away, which
incidentally lies within the zone of Earth’s broadcasting time where aliens could see our
signals, but partly outside of the time needed to send a signal back to us.
The signals passed two tests.
One, they were narrowband.
Nature and technology differ here.
Nature only rarely and very specifically produces narrowband signals, instead bleeding and smearing
broadband all across the dial.
Technology on the other hand prefers narrowband, because the more broadband you go, the more
energy you waste and the more you bleed into other useful frequencies.
But that’s a problem for SETI, because the vast majority of our signals, the interference,
is narrowband.
But it’s only step one.
The second is the doppler effect on the signals.
This is the dopplerr shifting of the signals if the source is moving, such as if they originate
on a planet or station orbiting a star and constantly moving in its orbit, or on a planet
constantly rotating on its axis.
These signals exhibited that.
And they did it in a different way than the more famous recent BLC1 signal, which has
shown to almost certainly have been human interference, though it’s not clear exactly
what was producing it.
Some comparisons between these new signals and BLC1 have been made, but they aren't that
similar.
BLC1 had the tricky problem of coming from the direction of Proxima Centauri, the nearest
star system, which creates a statistical problem.
If you detect an alien signal from the next star system over, then it implies that alien
civilizations, or colonies of a civilization, pervade the milky way and are everywhere.
Thus, you should expect to be detecting more signals of a similar nature everywhere, and
we simply aren’t.
These new candidates suffer less from this problem being distributed further away.
The other issue is that BLC1’s drift was weird, in that it was the opposite of what
you’d expect from an alien signal.
Not so with the new candidates.
But, as is the age-old problem with SETI candidate signals, followup observations failed to pick
any of them up again, though the authors urge further and more follow-ups to get a longer
sampling of observations of these candidates.
Until they repeat however, they are wow signals and simply aren’t actionable evidence to
determine if they truly are alien.
And we don’t know everything, nature surprises, and signals like this might signal some previously
unknown astrophysical phenomenon, though the narrowband nature makes this unlikely.
And then there is earth interference, and that’s beyond extensive, and as BLC1 showed
can confound SETI search algorithms and mimic signals of interest.
Repeated detections are needed to eliminate that issue.
The good news is that this new data mining approach for searching SETI datasets has no
shortage of them to look through.
There are more sets from Greenbank, but also the Parkes Observatory, and also with more
development data sets from the multiple telescope arrays.
But it’s interesting to compare how we do SETI today versus how it was done in the past.
There never really was a time where a radio astronomer equivalent of Jodi Foster sat around
on top of a car listening to radio hoping for prime numbers pulsing in the ear phones,
but there was a time such as the Wow!
Signal where the data had to be visually searched, in this case by volunteer Dr. Jerry Ehmann
during his off hours while as a professor at the Ohio State University, For those interested,
in the early days of hosting Event Horizon we sought out and interviewed Dr. Ehmann,
an interview that gave me chills when I did due to the perplexing nature of that signal
that haunts me to this day, link in the description below, but these days SETI searches really
aren’t conducted by humans any longer, but computers.
The computers report back to us what they find, or what they don’t find.
This leads to a curious situation.
As human technology advances, we end up doing less and less ourselves, leaving it to labor
saving devices such as computers.
In communications, computers run a lot of the infrastructure such as the satellites.
Might it be that this trend continues for any technological civilization and that our
first contact with an alien civilization won’t be us talking to aliens, but a machine talking
to a machine.
Thanks for listening!
I am futurist and science fiction author John Michael Godier currently eyeing the radio
telescopes suspiciously.
Hidden signals that you have to dig deeper into in order to uncover, mmm hmm, a likely
story and a be sure to check out my books at your favorite online book retailer and
subscribe to my channels for regular, in-depth explorations into the interesting, weird and
unknown aspects of this amazing universe in which we live.