omenti

red-edging life

Challenger, go at throttle up.

Roger, go at throttle up.

 

The disaster extended well beyond the manned space program.  The Galileo mission to Jupiter was going to take Galileo into orbit where powerful rocket known as the Centaur-G would set it on a direct trajectory to Jupiter.   New post-Challenger safety protocols and large schedule delays forced the Jupiter mission to use a less powerful booster.  Getting to Jupiter now required an indirect path using gravity-assist flybys.  First it aimed towards Venus and then made two close flybys of Earth gaining speed on each pass.

 

The delay and slower route frustrated many, but a bit of serendipity appeared.  The idea came from Carl Sagan.  As Galileo approached Earth its instruments were aimed Earthwards recording light reflected by the Sun.  Would there be indications that life existed on Earth?  Maybe it would be a clue to how we should be looking.  

 

 

In fact four signals indicated there was life on Earth.   The strongest indicator came as something of a surprise  - a dramatic change in the reflectance of near infrared light.  It turns out plants strongly absorb light in the visible part of the spectrum.  We see a lot of green because photosynthesis doesn't use it so plants reflect some, but for the most part plants are roach moteles for visible light.  At slightly longer wavelengths -  moving from visible red to the near infrared - plants become more fussy.  Having no use for these longer wavelength photons, they bounce them back.  The result is a huge increase in reflectance at around 750nm (visible red light's wavelength is around 650 nanometers).  Our planet has so much vegetation that the signal was easily spotted by Galileo as it sped by.    Note that many photos taken in the infrared often color code near infrared as red - the "red" in this false color photo by Trev Lea is the type of near infrared light Galileo would have recorded.

 

The spectral feature became known as the red edge and sparked a lot of thinking about astrobiology.  If a planet had life with an Earth-like photosynthesis, you could scan for a red edge as it turns out to be unlikely that other sources could generate such a feature.  Of course extraterrestrial  light harvesting life doesn't need to use light to make carbohydrates, but one can image photosynthetic processes with their own "red edges" at different wavelengths.  It is possible that some of this life may not get energy from light and that creates other challenges. Astrobiology became a serious discipline.

 

If  extraterrestrial life exists, it seems likely "dumb" lower life forms will be much more common that intelligent life trying to signal or visit us.  Other than waiting for radio or physical contact,  signatures in planetary atmospheres is one of the main tools we have until we develop interstellar travel.  But you have to start somewhere ... like finding planets in other solar systems.  But even the closest stars are a long way away and are much brighter than any orbiting planets.  Fortunately people are clever and a few methods have been developed.  

 

The first method is to recognize planets don't orbit stars. Rather stars and planets both orbit the barycenter - the center of mass - of their solar system.  The Sun has a bit less than 99.9% of our solar system's mass, so the barycenter is close to it.  Jupiter's mass is about one thousandth that of the Sun everything else is about a third of a Jupiter.    Our solar system's barycenter wanders around a bit and is usually inside the Sun.   If you were to look at the Sun from a distance over time you'd notice it wobbles a bit.  You can detect the wobble using  the doppler effect.   When the wobble - the technical term is radial velocity - is towards you, its light is shifted a bit towards the blue end of the spectrum.  Moving away it the light becomes a bit redder.  You have to get lucky and stumble onto stars with wobbles along the direction between you and the star, but it doesn't need to be exactly lined up.  The technique works best with huge planets in close orbits around small stars.  Think of a Jupiter sized planet inside the orbit of Mercury.  Usually they're really hot .. like thousands of degrees and are often called hot Jupiters.

 

Another technique is to watch a planet transit a star.    Watching from Earth, some exoplanets will appear to pass in front of a star as they orbit.  The star is so bright it washes out the planet completely, but it's apparent brightness dims a bit during the transit  An alien observing the Sun from a great distance would see the Sun dim by about one part in a million the Earth transited the solar disk.   Jupiter is so much larger that it would drop the Sun's apparent brightness by nearly one percent - an easy measurement for an alien with 1990 Earth technology.    The real ticket is to observe from space.  The Kepler Space Telescope bagged a few thousand exoplanets by staring at a small patch of sky for a few years watching for these minute dips in brightness.

 

While Kepler was great at finding new solar systems, the Hubble Space Telescope and the Spitzer Space Telescope would take a more detailed look at some of these candidates and wait for a transit to occur (many of these have planets that orbit their star quickly with years measured in days or a few weeks)  During the transit some of the star's light goes through the atmosphere of the planet.  It's a very delicate measurement, but it is possible to look at the chemical composition of some of these exoplanet atmospheres.  Then, perhaps, you could look for signs of life.    But the sensitivity isn't quite high enough to get too excited - yet.

 

Before talking about the signs of life that might be picked up and what might make a planet habitable, a bit on where we're headed.  The James Webb Space Telescope and the Wide-Field Infrared Survey Telescope will extend sensitivity far beyond what we have now with Hubble and Spitzer.  WFIST has a coronagraph - essentially it sticks its thumb in front of the star to create an artificial eclipse making it much easier to detect light from an exoplanet when it isn't in transit.    Further down the road the ideas is to make a better coronagraph.   The starshade is an umbrella-like objects tens of meters in diameter positioned about 50,000 kilometers  in front of the telescope precisely blocking out light from the distant star cutting down even more on the glare from the star.   Curiously the design is strongly influenced by the art of oragami..  a natural way to construct such an object.

 

 

A few other techniques to find exoplanets exit, but this should be enough for now.  Now  the task is to ask what do you look for and what are some of the characteristics life might require...    

Out of time, so perhaps the next post.

 

about two hundred miles north of roswell, new mexico...

As Edward Teller, Emil Konopinski, Enrico Fermi and Herbert York walked to lunch one of them noticed a New Yorker cartoon taped to a door blaming trashcan thefts on aliens.  It was 1950 and the country was in something of a UFO craze.  They laughed and continued.  

 

Unidentified flying objects have been a thing in the US since the late 1880s.  As soon as flying machines captured imaginations UFO sightings were reported.  Sometimes explained as foreign war machines, more often they were from other planets in the solar system falling in line with science fiction in the penny press and dime novels.  Jules Verne and HG Wells created more sophisticated aliens and UFO sightings reported rockets and flying saucers during the Great Depression.  The movie comic book industries picked up on it and fanned the enthusiasm.  

 

After WWII the atom bomb - something right out of science fiction for most people - and conspiracy theories growing out of secret government programs gave a sense to many in the public that these events were real.  The four physicists knew everything so far had a down-to-earth explanation - and if there was something, they'd probably be among the first to know. 

 

They sat down to lunch and physics talk when Fermi, who had been uncharacteristically quiet, suddenly exclaimed "where are they?"  Everyone at the table knew what he was talking about.  He scribbled away with some guesses about life supporting planets, the probability of life and the probability of interstellar travel.

 

° there are billions of stars similar to the Sun.  Many are much older than the Sun

° Many probably have planets and some are probably Earth-like.

° Some must have developed intelligent life.  Some of these civilizations are likely to be much more advanced than us.

° even at conservative interstellar travel speed of a half of one percent of the speed of light it would be possible to spread life from one location throughout the out galaxy in under 100 million years.  Not a huge amount of time compared to the geological age of the Earth.

 

We should have been visited .. regularly, in fact.  But where are they?  Although it's not a paradox it is commonly called the Fermi Paradox.   A large number of explanations have been given.  Here's an unordered partial list of the top of my head:

 

° extraterrestrial life is very rare..  we indeed may be alone

° life might be common, but evolution to intelligent life is very rare.

° intelligent life destroys itself before it develops interstellar travel - a popular conjecture during the Cold War and one Carl Sagan warned about.

° civilizations are too far apart in space-time 

° it's too expensive to mount such expeditions.  

° AIs will replace biological intelligent life and they may be focused elsewhere.

° we don't know how to look

° they're not interested in us or they purposely are avoiding us

° they're already here .. or their sensors are

° they're too alien

° and on and on

 

Frank Drake modified a technique particle physicists use to create the first serious attempt to quantify how common life is in the Milky Way galaxy.¹  The Drake Equation differs from the Fermi Paradox in that physical contact isn't necessary.. it's a counting rather than a visit.  It's easy to criticize as many of the terms are little more than educated guesses and some of them depend on poorly defined terms like life and intelligence.  It was also conceived before the Big Bang was established and assumed a steady state universe.  Lots of issues,  nut it fires the imagination and encourages dialog to the point where some progress has been made.

 

In its original form there are seven terms that are multiplied together .. note the fractions f are between 0 and 1.0.

R_*     the rate of star formation

f_p     fraction of stars with planets

n_e     number of planets that might allow life to evolve per star

f_l     fraction of planets that could have life that have life

f_i     fraction of planets with life that evolves to intelligent life

f_c     fraction of planets with intelligent life that have the capability of interstellar communication

L     the length of time such a civilization can broadcast and listen

 

As you might imagine there's some serious guesswork involved.  The last three terms in particular give such a spread that it has been criticized as an exercise in personal bias.   But we've learned a lot since 1961.   Now we have a good estimate of the probability a star has planets .. it's very common.  Furthermore there's been a good deal of work on the signatures of life and physically where to look - so called goldilocks zones.  One of the goals of the James Webb Space Telescope - the follow-on to the Hubble Space Telescope - is probing for signs of life.   That's for one of the next posts.

 

My own view, admittedly not worth much as I don't have enough empirical evidence, is that life must be very common, but intelligent life (whatever that means) is fairly rare.  Still the Universe is so large that I think there must be many civilizations.    But I also like to think we may be very rare and that humanity is special and worth preserving.   My belief is that Elon Musk and Stephen Hawking are very wrong when they say we need to leave Earth very soon to preserve humanity.  We have a very special and amazing place that is worth saving.

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¹ The form has its roots in 19th century system efficiency calculations. If a machine or process has parts each with their own efficiency and everything connected together you simply multiply the efficiencies to get the total system efficiency.  You can use the same technique to estimate the probability of finding a potential mate:-)

 

 

 

 

the universe is a time machine

I was asked to write about extraterrestrial  life. That's an approximately big subject that I'll approach with a few posts starting off with some context.  An old friend wrote this about the Universe:

 

Space is big. You just won't believe how vastly, hugely, mind-bogglingly big it is. I mean, you may think it's a long way down the road to the chemist's, but that's just peanuts to space.

 

Hold a finger about a foot - thirty centimeters - from your eye and focus on it.  It's part of you, but you're seeing it as it was about a billionth of a second ago.. the amount of time it takes light to travel a foot.¹  The Moon appears as it was a bit over one and a quarter seconds ago and the Sun is about five hundred seconds in the past.  

 

Generally we don't think about these things unless we have to synchronize events or consider the historical context of an event.   It comes into play exploring the Solar System, but also when measurements are made of events recorded in more than one place.  In experimental physics you worry about it all of the time, but it's important in high frequency market trading. 

 

When you look at the closest star - Centauri Proxima - you're seeing something that took place about four and a quarter years in the past.  A few years ago some of us studied weather patterns on a type of star known as a brown dwarf.  One could make predications and we issued a weather report.  The problem was we were looking at something that happened about sixteen years in the past and if some being near that star could read our report, they'd be looking at our history making the total out-of-dateness of the report about thirty two years.   When I know when someone was born I sometimes send them a birthday greeting naming the star from which starlight that originated when they were born is just making it to Earth.

 

The farthest in the past you can usually see with your naked eye is the Andromeda Galaxy .. about two and a half million years ago.  Telescopes take us farther back to about thirteen billion years ago when gravity was beginning to pull the primordial elements of hydrogen and helium into stars and organizing the earliest galaxies. Thi distant past is bizarre and quite foreign to anything more recent, but it's there for the looking if you have enhanced your senses properly.  Getting that far back is difficult and many more recent histories exist, so most Astronomers work in different time periods.,

 

We're not at the center of the Universe.  Rather we're at the center of our own perception.  Our finger is a bit in the past and our friend on the other side of the room a bit father back.  We look out into concentric layers of the past marking different epochs.   The history of the Universe that is written in light and now even in sound in these layers until we get to the last layer.. the fire of creation.  

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¹ Assuming your perception is instant, which it isn't..  it adds 250 to 300 thousands of a second, but that muddies the point.

We also live in neurological and acoustic pasts.  Those signals travel much more slowly than light, but over short distances so we tend not to think about them except during thunderstorms.

 

 

 

 

hope for nature and humanity

In grad school I came across The Limits to Growth - a book by the Club of Rome. Basically a report on computer simulations of exponential population growth and limits of the carrying capacity of the planet for a number of resources.  It struck me as bleak and depressing suggesting zero population growth was our only path out. I was curious about their model and found issues with the underlying data set and models. It wasn’t possible to describe population growth trends with simple exponentials. Something else was going on. They admitted some issues, but swept it under the rug sort of claiming “correct” data would fit their model. It began to slowly eat at me.

 

A few years later  I found myself traveling to Princeton regularly as part of a collaboration. It’s a great place to run into people and ask questions.  Eventually I found some demographers and learned at their feet. They weren’t terribly impressed by the book. They freely admitted there were serious issues, some of which may be existential threats.  At the same time there were some extremely positive trends.. Instead of simple exponential models there are periods of development with different population dynamics.  At first I had a my doubts, but their models fit the available data and fit some emerging trends much better than the CoR report.  There are a  variety of models, but they mostly boil down to three main stages.

 

The first is a period where the death rate is very close to the birth rate - sometimes exceeding it, sometimes falling short. Humanity was scattered around the globe and regions would fade in and out.  Eventually with trading centers becoming stable with very low population growth. The death rates were enormous.. for a family to continue to the next generation you generally needed more than six children.

 

The second stage is marked by the introduction of sanitation and successful disease prevention. Death rates drop dramatically, but people still maintained extremely high fertility rates.   The sanitation and medical knowledge is quickly communicated to populations at a similar stage. This results in enormous population spikes.  In the US the core part of this stage was from about 1920 to 1970.

 

The third stage sees women gaining education, opportunity and control over their bodies and fertility. Incomes are rising and families begin to focus putting more into fewer children. The fertility rate drops .. often dramatically.  Think Japan and parts of Europe. 

 

Different regions of the world go through these at different times and rates. One of the huge drivers for the second and third stages is urbanization. At first it  seemed counterintuitive, but when you talk to demographers and read their papers it becomes clear the growth of cities is the rocket fuel that enables the rest.

 

About fifteen years ago I organized a small conference on this at Aspen. I left with great hope and enthusiasm believing that lowering some of the other potentially existential threats would only make this process easier. In my mind the immediate low hanging fruit was working on global warming. It could have been, but I didn’t understand the inertia and control of the fossil fuel industry.

 

I could go on and on about these demographic trends and had intended to, but it would be book length and others are more expert in the area. I may talk about it in the future. The next stage is cloudy I can argue for at least four very different paths .. some of them pretty awful. But I recently came across a nice discussion of the saving nature piece..

 

Now for the good part.  Sean Carroll of Caltech interviews Joe Walston - the senior VP of Field Conservation at the Wildlife Conservation Society.  Joe offers a better summary of these issues than I could in an hour of writing  It's a bit over an hour long, but worth it if you have any interest in demographic trends, why they happen and where they could go.

 

Finally it's interesting these trends appear to be society independent.  We like to think how different we are, but in many ways, for good and bad, we're the same.  I find that comforting.

 

 

 

coming november 26th - seven minutes of terror and planetary farts

minipost

 

Great science communication takes a variety of forms.  Recently I've been impressed by some great blogs and YouTube videos, but traditional story telling and the illustrated comic format can be equally amazing

On the 26^th of November InSight will land on Mars.  For understanding the solar system robotic spacecraft win hands down over manned flights.  The exploration of Mars has been an incredible story and it could take a huge leap forward starting Monday.  The Oatmeal put together a wonderful science explainer. Learn about the mole, martian farts and the number.

 

great stuff!  read the full piece.

Manned spaceflight is still cool and possibly even justifiable, but it generally isn't science.  In my mind some of the most impressive work has been the inspiration Chris Hadfield has given to million of children.  That may be enough to justify the price.  I'm not a fan of flying Teslas, but that's another story.

 

 

 

 

 

 

 

 

 

pop go the bubbles

The wooden crate arrived via air freight from Geneva.  Fifteen bottles of champagne and a simple handwritten note with the words "I concede" and the name of the sender.  

 

A few branches of physics have a curious way of dealing with a class of disputes. People make conjectures that are impossible to test at the time.  When strongly held disagreements flare.  The tradition, dating back at least to 19^th century Cambridge is the gentleman's wager.  A statement is made by one of the conjecture holders in writing and witnessed.  Often these are of the nature "in ten years such-and-thus will have been found."  In this case it was fifteen years and was the sort of thing Paul would be committing the next ten or so years of his life chasing.  Paul's hunch was right.  In this case the quality of the champaign wasn't specified.  I'm told two of the bottles were excellent and the rest average.

 

There were four of us from the old group and we couldn't let the booty go to waste.  We wanted to learn something about the physics of popping the cork and immediately began asking questions.  Where does the pressure that pops the cork come from, how strong is it, how fast does the cork fly, what happens in the liquid when the cork comes off, what happens to the gas above the liquid and so on... The only thing we had to make  was the mechanical cork popper.  

 

We read what was available - literature on champagne told us about ten grams of carbon dioxide is produced by yeast fermentation in the standard 750ml sized bottle.  Outside the bottle it would occupy about six liters, so the pressure inside the bottle was fairly high - nearly 90psi (or over 600 kPa) , or roughly what you have in a bicycle tire.  It jus sits in equilibrium waiting...

 

When the cork is released the pressure gives it a fine sendoff.  Our fastest cork cocked in at a shade over 11 meters per second - about 25 miles per hour.  Our release mechanism wasn't that good and one high speed photograph showed a hand released cork moving a bit faster.   The speed depends on the temperature of the liquid.  CO₂ is less soluble at high temperatures, so warm champagne will give you a faster cork.  This, of course, is offensive to the French, so we tried to stay below 10° C. 

 There's an immediate drop of pressure in the neck of the bottle with the temperature falling to about -60°C for a few milliseconds.  Water and alcohol vapor condense in a short lived cloud that your eye might catch.  (We used photography and scattered laser light to get a sense of droplet size)

 

Inside the liquid a fizz starts as the carbon dioxide comes out of solution.   There is some disagreement on how to properly pour the liquid and what kind of glass should be used.  These questions and others are addressed by a number of papers that came about a decade after our little investigation.  The dynamics of the bubbles near and above the surface of the liquid are very important.  Ideally the fizz throws bits of wine into a diffuse cloud that hangs over the surface.  People say this greatly enhances the drinking experience.  The bottom line is a flute shaped glass does the best job of concentrating the cloud, but high carbon dioxide concentrations are acidic in the nose and mouth.  The trick, apparently, is a tulip shaped glass.    The trick for pouring is to tilt the glass at an angle and pour down the side.  Anything else leads to turbulence that liberates too much carbon dioxide.

 

 

Bubbles are historically important in particle physics. You've probably see photographs of particle decays.  From the mid 1950s up until about 1970 most of those images really were photographs. A high speed particle would collide with a particle in a target  and the collision products would head towards a bubble chamber.  These were tanks fulled with a clear liquid (usually liquid hydrogen) under pressure and a dissolved gas (hydrogen in this case).  Just before the collision the pressure in the chamber was lowered by quickly pulling a piston out a bit.  This sensitized the  liquid  just before particles from the collision flew through at a fraction of the speed of light.  They were long gone when the exposure was made, but they disturbed the liquid enough to form tiny strings of bubbles along their paths. At just the right time a flash went off and three exposures - one for each axis - were made.  Timing and lighting were issues and the optics were mind boggling, but miles and miles of special film was exposed in the day. An The results were measured by hand by "girls" (sexism of the day) on digitizing screens and then sent to a computer for pattern recognition.  Later computer programs digitized the images directly from the film eliminating a very tedious job.  To my knowledge this was the first use of a computer to make sense of an image and possibly the first example of big data.  Certainly one of the most exotic types of camera every made and they led to over a dozen Nobel Prizes.

 

(cork popping image by Niels Noordhoek [CC BY-SA 3.0], from Wikimedia Commons

reflecting on the moon in the pursuit of truth

It was the beginning of Spring in 2014 and there was electricity in the air. I've only seen scientific drama at that level a few times.  First the leaks and then a well-known team made a dramatic announcement.  These dramatic events can be confirmation of a radical hypothesis or sometimes it's Nature proclaiming how limited human imagination really is with something completely unexpected.  This time it appeared to be confirmation of a beautiful idea.  If it held up it would signal the potential of a new chapter in physics and cosmology.   A few people thought about shopping for suits that would be appropriate at a formal event in Stockholm.

 

For about fifty years we've known the Big Bang couldn't be the primordial event.  It was not the beginning of our Universe.   There were a conjectures ..  the most interesting came from Alan Guth who proposed an enormous mind-blowing-even-by-the-standards-of-cosmology inflation that took the Universe from something unimaginably small to something more the size of a baseball in a tiny sliver of time.  Over the years it was modified and tweaked and, although unconfirmed, many of us fell back on it to think about the pre-Big Bang because it nicely predicated what followed.  It had become a standard bias - one that people would abandon if proven wrong - but a bias nonetheless.

 

The conjecture was developed into a testable hypothesis by a few groups.¹  The first report came from an experiment at the South Pole called BICEP2 in 2014.  They saw a high quality signal that implied cosmic inflation. I noted my own excitement at the time. 

 

During the year that followed the serious skepticism of science took hold.  The team was known to be careful.  There are several things you do in any physics experiment to check your apparatus, how you handle information, biases and errors.  Ultimately you hope that someone else has a similar result with a different approach and apparatus.

 

There's a lot of preparatory work.  You need to understand what processes might mimic what you might be looking for.  Usually it's not a blind hunt..  you're guided by theory looking for something quite specific.  Discovery is finding it or finding the unexpected. It's fun to make theorists go back to the drawing board.  Most of them agree.

 

A good deal of thought and computer modeling goes into designing the experiment and understanding exactly what you should see - rediscovering well-known and agreed upon experiments.  If you can't get this foundational piece right, no one will believe you.  It turns out this step is where many of the data analysis paths are fleshed out.  This part, by the way, is where playfulness is essential.

 

You need to understand what are known as "backgrounds"  - events that mimic what you might be looking for.    There are null tests where you put a detector in a shielded box and understand the noise it produces.  These can get sophisticated.  Then there are calibrations where you see if you can measure known signals with all parts of your experiment.  Currently a hot topic in astrophysics is understanding what went on in the Universe when the first stars formed.  Unfortunately there wasn't any light - it was a dark age.  But there's a signal from hydrogen atoms that can be detected.  The process is well-known in radio astronomy and regularly used, but tuning into the dark age is leading edge work.  To sort out the background noise astronomers pointed a radio telescope at the Moon during the last lunar eclipse.  The noise component from the Sun would be missing and they'd be able to calibrate their apparatus and computational approach.  The signal was beautiful - the reflection of the rest of the Universe from the Moon.  Most of it turned out to be the Milky Way and the animated gif shows the result.

 

There are also jack-knife tests to remove regular occurring biases.   If you were studying car traffic flow you'd note rush hours are busy and weekends aren't.  So you break up the data into chunks and examine them separately to see how they compare.  The need for good enough random numbers often turns up here.

 

You constantly have to check the state of your apparatus and filters.  In an experiment of any size there's always something broken and something malfunction.  These have to be noted and accounted for.  It's not uncommon to spend a significant amount of time looking for problems.

 

Then there's the human problem.  How broad and deep is the team?  In the case of BICEP2 there wasn't any communication with people who did observational galactic astronomy.  When the results were published they noted there was a background that hadn't been accounted for.  It seemed obscure to the team and to most of us, but in the end it was nearly fatal.  The probability of discovery and confirmation dropped dramatically.  About a year later another experiment drove the nail home.  Inflation wasn't dead, but their experimental approach couldn't detect it.

 

And then there are dragons.  If someone asks you what's in your driveway and you tell them a car, both of you are generally satisfied.  But if you tell them it's a dragon ...  well then you have some explaining to do.  Reporting dragons can color fields.  A classic example came during the 60s.

 

Joe Webber was an outstanding experimental physicist who thought he had come up with a way to detect what Einstein predicted, but said would never be detected ... gravity waves.  He carefully eliminated many sources of noise and ended up seeing a signal.  He didn't have much in the way of theoretical guidance to know how big the signal was and he thought he was careful enough, so he published.

 

The problem was no one else was able to find a signal. For the next few decades no one saw anything and the field was nearly dead quiet for about thirty years.  There were theoretical hints that big advances in detector technology might find a signal and, through luck and enormous work, the Laser Interferometer Gravitational Wave Observatory - LIGO - was born.  About twenty years later it bore fruit and an advance as important as Galileo's telescope was made.  But people had to be careful... very careful.  How do you deal with human sociology?  What if people expect something to be there - or not - and these biases get built into data taking, algorithms and the final results.  

 

They had a neat idea

 

The LIGO physicists, astrophysicists and engineers got the signal they were looking for.  About four hundred people went to work trying to prove or disprove it.  About six months later they knew they had something.  The team leaders gave their thumbs up,  champagne came out and several lengthy papers were written.   As they were getting ready to send the papers for peer review a senior researcher held a town meeting.   They had been working on a faked signal - a devilishly clever faked signal.  

 

They needed to go back and understand what they were doing at a much deeper level. They had too many biases. Since then there have been several false alarms and about a half dozen real signals.  They have developed one of the most careful cultures on the planet using their blind injection technique.

 

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Carl Sagan wrote extensively on critical thinking. Perhaps his best non-technical piece on the subject is a chapter in The Demon-Haunted World: Science as a Candle in the Dark.  The specific chapter is The Fine Art of Baloney Detection.   The type of skepticism is useful far beyond science...  I'm thinking of advertising, social media, politics...

 

The kit is brought out as a matter of course whenever new ideas are offered for consideration. If the new idea survives examination by the tools in our kit, we grant it warm, although tentative, acceptance. If you’re so inclined, if you don’t want to buy baloney even when it’s reassuring to do so, there are precautions that can be taken; there’s a tried-and-true, consumer-tested method.

 

he offers nine tools - read the chapter for the detail

 

Wherever possible there must be independent confirmation of the “facts.”

Encourage substantive debate on the evidence by knowledgeable proponents of all points of view.

Arguments from authority carry little weight — “authorities” have made mistakes in the past. They will do so again in the future. Perhaps a better way to say it is that in science there are no authorities; at most, there are experts.

Spin more than one hypothesis. If there’s something to be explained, think of all the different ways in which it could be explained. Then think of tests by which you might systematically disprove each of the alternatives. What survives, the hypothesis that resists disproof in this Darwinian selection among “multiple working hypotheses,” has a much better chance of being the right answer than if you had simply run with the first idea that caught your fancy.

Try not to get overly attached to a hypothesis just because it’s yours. It’s only a way station in the pursuit of knowledge. Ask yourself why you like the idea. Compare it fairly with the alternatives. See if you can find reasons for rejecting it. If you don’t, others will.
Quantify. If whatever it is you’re explaining has some measure, some numerical quantity attached to it, you’ll be much better able to discriminate among competing hypotheses. What is vague and qualitative is open to many explanations. Of course there are truths to be sought in the many qualitative issues we are obliged to confront, but finding them is more challenging.

If there’s a chain of argument, every link in the chain must work (including the premise) — not just most of them.

Occam’s Razor. This convenient rule-of-thumb urges us when faced with two hypotheses that explain the data equally well to choose the simpler.

Always ask whether the hypothesis can be, at least in principle, falsified. Propositions that are untestable, unfalsifiable are not worth much. Consider the grand idea that our Universe and everything in it is just an elementary particle — an electron, say — in a much bigger Cosmos. But if we can never acquire information from outside our Universe, is not the idea incapable of disproof? You must be able to check assertions out. Inveterate skeptics must be given the chance to follow your reasoning, to duplicate your experiments and see if they get the same result.

 

He goes on and notes we are vulnerable to common pitfalls of common sense and lists twenty common ones... the list is excellent and exceptionally appropriate these days.

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¹ In the physical science rough ideas are conjectures..  If you can test them they are elevated to hypothesis.  Theory usually refers to something that is well understood and tested by several approaches. It is a fairly high bar.  In particle physics it means being observed with an uncertainty lower than one part in three million - preferably by multiple approaches.  This is one of those differences in definitions that causes confusion when communicating with the public where 'theory' usually means someone's idea -no matter how good or bad.  I'll be a bit more specific as these ideas can be used to one degree or another outside of science.

I'll add that cosmology and astrophysics produce the most mind blowing graphs I've encountered.  Math can be more dramatic, but these are trying to find a visual vocabulary to describe Nature.  

 

the other scientific revolution of 1953 that radically accelerated knowledge

In the Winter of 1953 Francis Crick interrupted the lunchtime patrons of the Eagle in Cambridge to announce he and James Watson had discovered the secret of life.   In fact it wasn't far from hyperbole - they had discovered the structure of DNA and the world was forever changed.¹  Something else world-changing happened later that year.  Without it we  wouldn't have advanced past the technologies of the 1960s.  Surprisingly one of the people behind it thought it cute, but hardly worth publishing.  

 

But first a bit of historical context

 

The Manhattan project began with blackboards and experiments.  Individual researchers had their desk calculators, but it soon became necessary to work out how neutrons diffused when a critical mass of fissile material came together. A group of scientist's wives came together to perform the repetitive calculations.  Next came IBM card reading calculators and then von Neumann became interested in developments in electronic computing at Harvard, Bell Labs and the University of Pennsylvania.  There's a deep and rich history from this time on, but the important point was the meaning of "computer" was shifting from a woman with a mechanical calculator to an electronic machine.²

 

In 1953  electronic computers were still rare, mostly one-off machines that were expensive and temperamental.   It was still a world of research and development. A few people recognized practical applications, but the machines mostly weren't ready.  Except for physics.

 

Physicists were heavily involved in the birthing of electronic computers focusing on specific problems that tended to involve military projects or fundamental research to drive the hardware.  Fundamental research was seen as the tip of the R&D effort and was often funded from military budgets which were large enough to support these efforts.   Enrico Fermi  had an interesting idea.

 

He was interested in nonlinear systems thinking they might have something fundamental to do with entropy and why time only flows in one direction.  He, John Pasta and Stanislav Ulam conceived a simple toy problem - sixty four identical masses representing the atoms in a lattice connected end to end by little springs representing chemical bonds. Unfortunately calculating the restoring forces is a beast of a problem.

 

A linear system is one that can be described by a straight line on a graph.  Consider a spring.  Pull it twice as far and it exerts twice as much force. The same is true when you pluck a string on a guitar.³  Nonlinear systems have a more complex behavior.  With linear systems you just add up the contributions of each element without considering the others.  Nonlinear systems are nasty - you need to consider everything at once.  You might be able to calculate very simple systems with a few elements, but after things become very complex.

 

The three physicists wrote down a mathematical description of the physics. Think of it as a strange sort of string that you pluck and then listen to as time goes on.  Solving it would require a lot of computer time.  The big iron at Los Alamos was called the Mathematical Analyzer, Numerical Integrator, and Computer or MANAIC-1 for short.  It had been built for thermonuclear calculations, but this trio had an enormous amount of credibility and it was clearly fundamental research. 

 

The three had no experience with programming, but Mary Tsingou was a mathematical physicist who knew how to reason with  MANAIC-1.  She set to work creating a program that became an experiment simulating how the lattice behaved for sixteen, thirty two and sixty four "atoms" with various spring forces.⁴  

 

Imagine of the frequencies coming out of the system in terms of sound.  They had expected a pure note that would shift  over to more chaotic noises and finally the equivalent of just a hiss.  That didn't happen. 

 

The lattice was "plucked" and a series of overtones appeared and dissolved into each other creating a complex mixture.   Then the whole process reversed and the overtones disappeared in reverse order until the original pure note reappeared and the whole process started over again.  

 

 

Here's an illustration.  Consider the top graph.  The purple points are just the first vibration mode of a simple string - think of it as showing what would happen if it was just a simple string.  The system we're talking about with equal masses and springs is in blue.

 

Even this simple little problem that had baffled some of the greatest minds had a beautiful and completely unexpected result and a new way of doing science had been developed - the computational experiment.  The computer had become not just a bicycle, but rather a telescope for the mind.

 

Much of science is impenetrable without computer experiments like these.  It's so common, I've done thousands, that you tend to think it's natural.  But it had a beginning and without it much of what we've seen from science after the mid 1950s and the resulting technologies wouldn't have been possible.  Inefficient cars and airplanes, no electronic revolution, no cellphones, no ....

 

Fermi thought it was cute, but not fundamentally important.  That may be true for the hypothesis they tested, but how they did it changed the world.

 

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¹ There were many others who were in on this, but Crick and Watson weren't exactly the sharing kind.  Most notably the x-ray diffraction work of Rosalind Franklin.  But she was a women and died before the Nobel was awarded anyway.  

² George Dyson (Freeman Dyson's son) penned Turing's Cathedral.  An excellent and very readable history of the efforts at Princeton.  That may be the most important early thread as the computer architecture used today was developed there.  Much of the slightly later development came out of Cambridge in England. 

³ Sort of ..  you can get it to behave non-linearly, but for now consider a spring that behaves like F = kx where x is the displacement, F is force and k is a constant that tells you about the spring's stiffness.

⁴ I don't know for sure, but have been told she programmed down to the iron in machine language. 

 

 

hearts, minds and actions .. moving people

In the 1960s living conditions in some parts of the developing world were beginning to make serious progress.  It wasn't terribly uniform, but some counties in Africa and Eastern Asia were feeling the impact of the green revolution, sanitation, and widespread immunization.  Korea was at the leading edge, but there was this problem.  A large percentage of the population was rural and agrarian.  To deal with very high infant and childhood mortality rates families had an average of six or seven children.  Now it was likely that the vast majority of those children would live and the fertility rate was the same.  The Korean government was faced with a serious problem.

 

Other countries had the same problem.  The standard approach was to shame people who had too many children and provide education about contraceptives through media campaigns.  It was a tough slog with success rates somewhere between miserable and non-existant.  Korea, on the other hand, had enormous success. All of their objectives were easily met inside of a single generation.  What happened?

 

Although the Korean program was national, media campaigns were absent. It was felt a better approach would correspond to the village oriented makeup of the population.  Information was provided to a few people in each village and then moved by peer to peer contact.  Curiously, although most villages adopted some form of contraction, techniques varied widely from village to village.  Pill villages, IUD villages, condom villages and so on.    The villages with the strongest social networks saw the greatest degree of behavioral change.

 

There was an academic problem.  Work on viral diffusion of information said that weak times would be a much more efficient mechanism for radiating information and changing behavior than these messier local and strong social ties. After all - there had been a lot of success predicting diffusion of contagions  where weak ties spread diseases much more efficiently than strong ties.  Think about a single plane with someone coughing ... And now millions will know about the best current cat videos inside of a day.  And the six degrees...

 

Think about contagions.  While they spread easily, convincing people to get immunized can be a difficult task and some groups adopt anti-scientific beliefs that can lead to breakdowns in herd immunity.  Why doesn't that simple information spread as quickly?   A high level answer moving simple information is very easy and weak tie networks are very effective.  Behaviors tend to be much deeper than simple information and require richer contact often of several types.  We use our close social networks ..  the strong ties of close friends and family ..  for behavioral reference and reinforcement.

 

I know an excellent science explainer.  Make that world-class.  Her parents love the beauty of Nature and moved to Hawaii before she was born.  She returns regularly, but is a bit of the black sheep as they're religious fundamentalists and have come to believe that global warming and science in general are attacks on their belief and identify.  (This linkage is almost uniquely North American. I've talked about it before and probably will again as it's both fascinating and frustrating.)

 

She was home a few months ago when a rare Hawaiian typhoon took a swipe at their island dumping three quarters of a meter of rain in a day.  It is now possible to model how likely a storm like this could exist without global warming.  In this case it was unlikely it would have happened without the current level of global warming.  As the storm raged she broke down into tears.  She shares their love of nature and the storm was a manifestation of change and destruction.

 

They watched and for the first time heard their black sheep science loving daughter.  They're certainly not convinced. Being against a belief in global warming is part of their core identify. But she was able to chip away at their belief.   Her strong tie with them is stronger than the (less strong) tie of their religion and much stronger than widely spread scientifically accurate but weak tied information about global warming.

 

Sometimes simple coded signalings to  strong tie groups are sufficient to bring change.  It seems likely that a lot of personal technology follows this path.  Certainly one can signal to an existing tribe.  If it's done in such a way to resonate with core beliefs it is possible to bring dramatic behavioral change.   New work on  behavioral change diffusion is emerging as people realize the current diffusion models don't always apply.  Viral messaging and weak, but far reaching networked communications fail to describe much of what people actually do and particularly how behavior changes. 

 

Social science isn't a "real" science if you compare them to the "hard" sciences.  Human behavior is still far too complex.  But progress is being made and a better understanding of how behavioral spreads will have deep implications.  Contrary to what Malcolm Gladwell might say, viral information spreading isn't as effective as many think.  (I keep thinking I should write something about Gladwell's books and talks, but...)  If you wonder why your viral ad campaign didn't see any sales bump for your new gizmo, there may be a fundamental reason related to messaging.

 

chilling with light

After the last post, someone asked about laser cooling.  I'll try it without images..  just draw them in your mind.

 

First off what is hot and cold?  

 

Think of heat as the energy of motion of the atoms and molecules in something.  They can be moving through space, rotating or vibrating.  Temperature is just a measure of the average kinetic energy of the molecules of something. "hotter" means a higher kinetic energy.  Cold is just the absence of heat. .  you don't add cold to something.. you have to remove heat.

 

Light has both energy and, even though it doesn't have mass, momentum.  We don't notice the effect at our scale,  but if a molecule absorbs a photon of light it will feel a force.  

 

But isn't that adding energy and isn't using a laser something like using a flame thrower to blow out a candle?

 

Imagine a very simple system.  A single atom that can only move to the left or right.  Its temperature is directly related to its kinetic energy..  half its mass times its velocity squared.   Put a laser on the left side and point it at the atom.  Now the fun.

 

Laser light is monochromatic - one color or a single frequency.  Lasers are perfect, but in a gedanken experiment like this it can be.  Thanks to quantum mechanics it turns out atoms and molecules have very specific absorption frequencies.  If the laser light frequency isn't spot on, the atom completely ignores the light.  Now pick a special kind of laser that allows you to tune the frequency of the light.

 

If the atom was just sitting there and light at its absorption frequency strikes it, it will take the momentum of the light and move to the right.  Not exactly what we want.  We'll invoke the Doppler effect -- the fact the pitch of a siren rises as it approaches and lowers as it leaves.  The same is true for light.   Dial in a frequency just below the absorption frequency of your atom.  If the atom is moving to the left the frequency of light it "sees" is a bit higher than the frequency the laser is putting out.  If you've made the right adjustment the molecule absorbs the light.  The force is opposite the atom's leftward motion and the atom slows down a bit.  If the atom was moving to the right the frequency of the light at the atom would be lower and no absorption takes place.

 

To handle motion to the right, put another laser on the right pointed to the left. Now whichever way the atom moves it will slow down.  Since there is less kinetic energy its temperature has dropped.  You've cooled it.

 

To go to the real world imagine a cavity filled with a gas of these atoms.  There are three directions so use six lasers (or three with mirrors)  up-down, left-right, in-out.  Any motion of the atom can be described as a combination of the three directions so you are cooling the random motions of the atoms of the gas.  A refrigerator that uses light..

 

There are a number of tricks to achieve very low temperatures.  The record is a few millionths of a degree above absolute zero for a very tiny sample and something like half a degree above absolute zero for a sample large enough to see.

 

The technique turns out to be very useful for investigating quantum mechanics.. particularly of macroscopic objects like the guts of quantum computers.  It's also used in some of the most accurate atomic clocks.  The next generation atomic clocks in GPS satellites will use little laser cooled samples for much better accuracy which leads to more accurate navigation.  

 

Imagine -  a constellation of laser cooled atomic clocks 12,600 miles up so you can find your way around better with your smartphone.