The Goldilocks zone doesn't enter the Drake equation at all.
As a reminder, this is the equation: https://en.wikipedia.org/wiki/Drake_equation#Equation
It makes very few assumptions.
As a reminder, this is the equation: https://en.wikipedia.org/wiki/Drake_equation#Equation
It makes very few assumptions.
The last five factors in the equation will be filled in by assumptions based entirely on one data point, life on Earth. From your link:
ne = the average number of planets that can potentially support life per star that has planets.
fl = the fraction of planets that could support life that actually develop life at some point.
fi = the fraction of planets with life that go on to develop intelligent life (civilizations).
fc = the fraction of civilizations that develop a technology that releases detectable signs of their existence into space.
L = the length of time for which such civilizations release detectable signals into space.
Edit: the parent post has been edited substantially after I replied.
They are "defined" conceptually, in words, not in physical quantities. It assumes we can assign a known value to any of that when we don't and likely never will. It's like saying "Let X answer the unanswerable question. X is the answer".
> at no point does it assume a planet must be in the Goldilocks zone
You could say it implies it with fl.
> Edit: the parent post has been edited substantially after I replied.
Only for legibility.
For all we know civilization exists inside our car battery. Why assume it only exists on planets.
It's not explicit in it's assumption but implicit assumption the equation is meaningful.
Rick Sanchez uses a microverse battery
https://annas-archive.org/md5/4c381ac344506d10037fc8e7747098...
The cheela lived on the surface of a neutron star, and they lived faster because the nuclear physics that powered their metabolism are far faster than the chemical and mechanical physics that power our own.
Anyway, sounds interesting, gunna add that to my list
Also Macbeth was written 400 years ago. Let's not pretend this is a fair comparison. This author has been dead only 20 years - it might be that their partner is still alive and needs that money, or their children.
Amazon is hanging on by a thread, and piracy is stealing their cut.
Anyway, what is copyright expiration in America these days? 100 years?
Also, is it simply a matter of X years after creation? I somehow doubt it's that simple anymore. I wouldn't be surprised if "copyright is extended indefinitely if the work is being actively commercially used" or some such
Which is saner eh! That way people living at the time who are protecting it (copyright and patents are both protections for things otherwise being distributed and which could be copied easily) can benefit from it eventually.
100 years is just rent extraction.
We need more discussion about copyright in our society, and we need it most in front of those who are unaware, inattentive, or would otherwise shirk that discussion. Posting a relevant link in a relevant discussion appears as good an avenue as any to get people talking.
That's a rather severe escalation to me.
Drexler and colleagues did that, and found "a substantial probability that we are alone in our galaxy, and perhaps even in our observable universe (53%–99.6% and 39%–85% respectively). ’Where are they?’ — probably extremely far away, and quite possibly beyond the cosmological horizon and forever unreachable."
It's nowhere near a precise estimate of the probability of life. What it mainly shows is that the Fermi "paradox" is no such thing. It can look that way if we guess specific parameter values, but if we fully account for our uncertainty on the various parameters, then the result is a decent chance that we are alone, given the knowledge we have so far.
You can’t have a distribution with one data point.
It’s similar to the arguments about 3I/Atlas being an alien spacecraft because it’s so ‘weird’.
With so few data points, everything is fundamentally ‘weird’ - or normal - we have no way to tell, so making any sort of statistical argument about it is fundamentally useless and misleading, as statistics is based on groups. And we don’t have a group yet.
One of the most uncertain parameters is the rate of abiogenesis events per planet. For that one they used a log-normal with a standard deviation of 50 orders of magnitude. They discuss specific theoretical limits from biology for both ends of the range.
Compared to this approach, the usual method is to just pick particular values out of a hat. This paper at least improves that by directly representing our vast uncertainty for some of the values.
It doesn't tell us how many alien civilizations there are. But it does tell us the range of possibilities, given what we know and don't know.
Life, once established, is about competition for niche resources. Established life would kick the polypeptides out of a protocell quite easily (with certainty > 99%).
Protocells could be evolving right now at vents in the ocean, with zero of them managing to escape their birthplace due to being outcompeted by things with fully developed organelles.
If you're willing to concede that in fact, that doesn't happen, then you're putting a limit on that parameter, just like the paper did.
The underlying model is just:
N*f
How many planets are there, and what proportion of them have detectable life?
The f does not have to be structured as fl->fi->fc, although we can see why you'd assume that kind of structure. It's simple to calculate the PI(series) when the model is just a funnel. Like the Million Dollar Money Drop gameshow.
But you could imagine a more complex model of probabilities that branches and merges. There could be events on the bayesian tree that amplify downstream events. For instance, suppose there is some pathway that if reached will leave certain minerals that future civilizations could use. This has happened already on earth at least once: lignin bearing plants could not be easily digested for a long time, and that led to coal formation during the carboniferous period.
You could imagine many such potential trees, but we only have one iteration.
> n_e = the average number of planets that can potentially support life per star that has planets.
The fact that the planet is neither too hot nor too cold would seem to be a major component of this term: