New Guy in Town

These graphs show the results of evolutionary experiments by Richard Lenski, in which a bacterial species ( e coli) has been evolving under constant conditions for many years: tens of thousands of generations.

These bacteria were not perfectly adapted to the experimental environment, and so there is selection for changes that allow them to do better in these conditions. Adaptive change is rapid at first and slows down with time, as the culture approaches an optimum phenotype. Fitness increases rather like the logarithm of time.

The probability of a beneficial mutation fixing is proportional to the advantage it confers. Large-effect beneficial mutations are more likely to fix and dominate the early phase. As the bacteria get closer to an optimum, the possible gain from a beneficial mutation is smaller, and so those smaller-effect beneficial mutations ( the only ones possible) are less likely to fix. Thus they take longer to fix (on average they need to occur many times before succeeding) and they also fix more slowly, since their growth advantage is small.

relevance: a new virus in humans is like the situation near the origin of graph B.  The virus is not yet close to an optimum, so change is fairly rapid – particularly if the virus is infecting vast numbers of people ( like covid-19) which greatly increases the number of copies of the virus and thus the chance of favorable mutations ( Fisherian acceleration). Favorable to the virus, that is.

An old virus in humans, say measles ( > 1000 years old)  is closer to an optimum: change is much slower.

It seems that most professional virologists are used to viruses that have been around for quite a while – understandable, since new viruses do not sweep through the human race every year.

You could have predicted the emergence of new higher-transmission variants of covid-19 from this theoretical perspective. I did, arguablywrong did, probably others have as well. But virologists did not.





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New variants

There’s a new variant of cov-19, the UK strain, that is something like 70% more infectious than previous strains. At this point its lethality seems about the same as earlier strains.

Virologists, most of them, did not expect this.  I did.

Let’s consider some simple examples. Imagine that you have someone – a single individual – with what we will call a normal strain, A. On average, in  the current situation,  it has an R0 well above 1.

What is the most likely outcome? Most likely, he doesn’t spread it to anyone, and it dies out.  Overdispersion: most people don’t do much spreading, and a few do a lot. Let’s say that 20% of those infected do all of the spreading.  Right off the bat, 80% of new strains die out, just because of this pattern.

Now, imagine that we simultaneously introduce two new strains, A  and B with a 50% greater R0%.  for each, a single individual.

There are four possible outcomes: A spreads widely, B spreads widely, both and A & B spread widely , both A and B disappear.

Most likely both will disappear (~64% chance) .

There’s a fair chance that A will spread while B is lost, and a moderately larger chance that B will spread while A is lost.

There is essentially zero chance that both will spread widely: even if both manage to avoid being lost by chance in the beginning, B will grow faster than A and replace it.

So, suppose you introduce one person with A, and one person with strain B: can you judge the relatively infectivity by which one succeeds?  No – there’s a significant  chance that the less-infective one will win out.

Now consider a situation in which A is already common, and a single case of B  is introduced.  what are the possible outcomes?

  1.  B is lost by chance.  ( > 80% probability)

2.  B replaces A – happens if B is lucky enough to get past the risk of extinction when rare.  But once it gets up to a few hundred copies, it will surely replace A.

What can we conclude if B is rapidly replacing A ( as has been the case with the new UK strain)?

That it surely has significantly higher transmission, significantly higher R0.

Many virologists thought this very unlikely, and some said that you could never know that a new variety had higher transmission from mere incidence data: you must understand the biological mechanism.  Are they correct?  Obviously not.

Why did they think that a new, more transmissible variant of COVid-19 was unlikely?  I would say there are several reasons. One, they typically deal with viruses that have been around for a long time, like measles ( > 1000 years) .  An old virus is going to be pretty well-adapted to to humans.  Probably it’s at a local optimum, where small changes would reduce infectivity. But you don’t expect that high degree of optimization in  a virus that’s brand new in humans: while spreading to very many people, more than 100 million,  greatly increases the chance of  transmission-increasing mutations.  Fisherian acceleration.

Like most biologists and MDs, most virologists don’t know any theory, and in fact don’t _believe_ in theory.   For this they occasionally pay a price.


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Signs, Portents, and Appetizers

Was thinking about various factors that influenced the discovery of America – by which I mean Columbus’s voyage. Not Saint Brendan or Madoc,  not the Phoenicians, not the Romans, not the Solutreans.  Not Basque fishermen.  Not Leif Ericsson or Bjarni  Herjólfsson either, because, although they really did get there, the information didn’t spread far. The same for Polynesian contacts – they did visit South America, but since they themselves were isolated from the Old World, it didn’t go anywhere.

First, they had cheap, reliable ships that were up to the job.  I emphasize cheap.

Columbus and European civilization _knew_ there was land on the other side – China, if nothing else. They knew the world was round.   Unfortunately for Columbus,  potential backers also knew how _big_ the world was, and how very far it was to China ( he had a fruitful delusion about this.)

One factor must have been the discovery of a number of useful islands in the Atlantic: the Azores, Madeira, the Canaries ( rediscovered, really – already inhabited and known to the  Romans). An expedition that merely found another Madeira would have more than paid for itself.  Legend placed plenty of other islands out in the Atlantic,  from Antillia to Huy-Braseal.

Could Columbus have known about Leif Ericsson and Vinland?  Just barely possible: there were people in Iceland that remembered Vinland, but the story wasn’t generally known in Europe. And even if he had heard, he was going far south of their discoveries.

People have occasionally wondered if sea beans had something to do with it. Sea beans, or drift seeds, at least the ones we’re interested in, are buoyant seeds come from tropical plants in the New World.  They can float long enough to reach the shores of Western Europe. When you found a sea-heart on the beach, something that clearly did not originate in Europe, surely that unknown land felt a bit more real.


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Books, 2020

You might also be interested in my booklists from 201420162017,  2018, and 2019.

  1. The Big Sleep 
  2. In the Courts of the Crimson Kings 
  3. Memoirs of an Invisible Man
  4. The Mote in God’s Eye
  5. The Weirdstone of Brisingamen
  6. The Brothers Karamazov
  7. Life among the Savages
  8. I Bought a Mountain
  9. The Hot Rock
  10. Waldo & Magic Incorporated
  11. Lucifer’s Hammer
  12. The Harvest of Sorrow
  13. The Ghosts of Evolution
  14. The Complete Illustrated Encyclopedia of Dinosaurs & Prehistoric Creatures:
  15. Population Genetics
  16. Marching Through Georgia
  17. Genetic Takeover
  18. The Idea Factory
  19. The Knowledge 
  20. The Alexiad
  21. In the Country of the Blind 
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Doctor Doctor Give Me the News

Credentials don’t make an incorrect argument right, and the lack of them can’t make a correct argument wrong. The track record tells you more – George Green and Srinivasa Ramanujan ( and Freeman Dyson)  did what they did.  In that sense, degrees don’t matter.

But they can give you signals of greater or lesser utility.   Ph.Ds in math or the hard sciences prove you have some brains – not necessarily that you will make good use of them, or that you’ll be useful, but sure, you probably have some brains.   Or at least you once did. Doesn’t necessarily mean that you know much outside your specialization, or have much sense.   Although you might.

What about a Ph.D. in psychology? it doesn’t mean that you can’t have some brains, but its predictive value isn’t very high.

An M.D.?  Again, doesn’t mean that you can’t be smart, but, usually, not born puzzle solvers.  Significantly overrated by both the general public and holders as an indicator of general omnicompetence.

Ph.D. in education?  On average, it predicts that you’re dumber than someone with a B.A in education, already below the general college average.

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Coding Error

James Coleman published an influential study in 1966, “Equality of Educational Opportunity”. It found that variation in school quality (per pupil expenditure, size of school library, and so on)  had little influence on  educational achievement, while students’ family backgrounds did.  Which is consistent with genetic influences.

He did find that a student’s educational attainment was related to that of other students in the school – somehow, educational success rubbed off on others. This was often cited as evidence to support policies of forced integration and busing.

But that finding was a mistake – due to a coding error.  Which I first thought meant missing a parenthesis in some computer program, but more likely had to do with mislabeling or misclassifying entered data.






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Everyone makes mistakes

Razib Khan dredged up an article that talked about the role of Japanese intelligence and/or the Black Dragon Society in furthering the developing of  black nationalist groups before WWII – one such group eventually developed into the Nation of Islam. Perhaps this accounts for some of the odd Yacub stuff, which I’m pretty sure isn’t in the Koran.

But there was a very interesting point mentioned in that article that Razib did not notice, or perhaps did not find interesting:

“”After Nation of Islam members participated in what was reported as a human sacrifice, NOI founder W. D. Fard was instructed by Detroit detectives to leave the city in December 1932. ”

Probably everybody knows about this, except me.





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Learning to Decode

(Stolen from David Kahn’s _The CodeBreakers_.


In the presidential election of 1876, Samuel J. Tilden had a quarter-million majority of the popular vote,. but the outcome of the electoral college vote depended on which of the rival returns from Florida, Louisiana, South Carolina and Oregon were accepted. If all of the disputed ballots went Republican, Hayes would win by one electoral vote. A special electoral commission awarded all of  them to Hayes, by a straight party-line vote – and Hayes became President.

During the ensuing controversy, a Congressional committee investigated persistent Democratic rumors of Republican purchase of electors’ votes. As part of this investigation, they subpoenaed 641 political telegrams – those that hadn’t been burned by Western Union.  27 of those enciphered telegrams were leaked to the New York Tribune, run by Whitelaw Reid.

Now it’s 1878.  Manton Marble, one of Tilden’s closest political advisors, had written an open letter to the New York Sun contrasting dark Republican practices with Tilden’s station in “the keen bright sunlight of publicity.” Reid wants to decipher those messages, but doesn’t know how. Many people suggest ideas, but they fail. One meta-idea was good  – the Secretary of State suggested hiring a young mathematician.

The managing editor, John Hassard, decide to try and crack the cryptograms. Shortly thereafter, William Grosvenor, the economic editor of the Tribune, did as well.  A little later Edward Holden, a mathematician at the U.S. Naval Observatory, added his efforts.

They made a fundamental advance in cipher analysis, and they read almost all of the coded messages.  My, but they were interesting.

Tilden’s campaign manager ( and nephew) , Colonel William Pelton, had been offering to pay electors to switch their vote. He only needed one ! He offered an elector  from South Carolina $85,000 – a fair piece of change in those days.

All this came out a few weeks before the 1878 off-year elections.  The Democrats did poorly, and although Tilden claimed he had no idea that his nephew/manager was doing all this ( in Tilton’s house !), the disclosures ended his presidential aspirations.  As his old supporter, the Sun, sadly conceded, “Mr. Tilden will not again be the Presidential candidate of any party.”

Reid ended up Ambassador to the Court of St. James.



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Free Parameter

What if this coronavirus were 10 times more deadly? 20 times?  What if it hit all ages equally, or was especially lethal to young adults ( like the 1918 flu)? What if it crippled, like polio?

Would people in those hypothetical scenarios have been as crazy as they are now,?  They are not impossible: the idea  that natural selection tightly limits  possible virulence is not correct.  In the famous misapplied example, myxomatosis, virulence in rabbits dropped from > 99% to ~ 50% – but I wouldn’t quite call  that having a cold. And it involved selection acting on the rabbits, as well – old-fashioned rabbit strains exhibit much higher than 50% mortality when exposed to current strains of myxomatosis.

I don’t believe that there’s a reserve supply of sanity that is called out when it’s truly needed.  Not this year, anyhow.






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Too Many Muons

There is a notion that radiation may be  limiting qubit lifetime. Even if you use low-radiation materials and shielding, you still have to worry about muons generated by cosmic rays.  They are very penetrating – some reach kilometers down into the rock.

If so,  we may need to build quantum computers several klicks underground.  The deeper, the better:  another factor of ten attenuation of the muon flux could materially extend qubit lifetime and drastically improve performance.

We could perhaps use the old Homestake mine in South Dakota,  now the location for DUSEL (Deep Underground Science and Engineering Laboratory ).   But it’s only 2.4 km down.

The best mines ( for our purpose) are more than 3 kilometers deep, and a few approach 4 km.  The problem is, of all the ten deepest mines in the world, only one is in the US.

The United States faces a mine shaft gap.





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