What's It All About Again?

Well, I still think that it is all about self-replicating information in action on the grandest of scales, but ...

About 10 years ago, I posted What’s It All About? as I was about to turn 60 years old. In that posting, I explained that I was then heading into the home stretch and that I thought that it would be a real shame to have gone through my whole life without ever having figured out what’s it all about or understanding where I had been or how I had even gotten there in the first place. Now in October 2021, I will be turning 70 years old, and surprisingly, I am still here! So I thought that it might be a good time to take another look and to also think about where things are heading for humanity after we are all long gone. In What’s It All About?, I proposed that our Universe, and the whole Multiverse for that matter, was just a form of self-replicating mathematical information and that our Universe might just be one instance within an infinitely large Multiverse of universes. In this view, our Big Bang is just one of an infinite number of Big Bangs of mathematical information exploding out into existence. People have long debated whether mathematics is something that always existed and that was slowly discovered by human beings or is mathematics simply something thought up by human beings all on their own? Is mathematics just a set of rules that we thought up like the simple moves in a game of chess that can lead to incredibly complex things or is mathematics the Fundamental Essence of the Universe that has always existed and that we slowly discovered with our Minds? For me, most of mathematics is something that has always existed even before there were Minds to contemplate it. We slowly discovered mathematics by observing the attributes of the seemingly physical things that mathematics has brought forth. That is still my working hypothesis, but a lot has happened in the past 10 years to slightly modify that working hypothesis. Again, all of this is largely my own speculation tinged by a bit of the science of our times. But since I will not be around when all of this is finally figured out, if that ever happens, it is the best working hypothesis that I can come up with at the moment. I know that it is "wrong", and there is no shame in that, but I do hope that it might be at least close.

The most accurate effective theory of our Universe is now the quantum field theories of the Standard Model (1973) that depicts our Universe as a collection of quantum fields vibrating in spacetime. Some of these quantum field vibrations produce fermion particles of matter with a spin of 1/2 ħ of intrinsic angular momentum like electrons. Other quantum field vibrations produce force-carrying boson particles with integer spins of ħ intrinsic angular momentum like photons with a spin of 1 ħ that carry the electromagnetic force between electrically charged fermion matter particles like electrons. It is thought that these fermion and boson quantum fields simply consist of a mathematical value for the fermion and boson quantum fields at each point in space. In essence, these quantum fields are just made of pure mathematics at heart. In this view, all of the physical objects that we interact with are just figments of mathematics as I outlined in The Software Universe as an Implementation of the Mathematical Universe Hypothesis that covers Max Tegmark’s Mathematical Universe Hypothesis. That means it is all about software. There is no hardware at all. It is just software at the deepest of levels.

But How Can Pure Mathematics Explode Out into a New Universe in the Multiverse?
Currently, we have two models that provide for that - Andrei Linde's Eternal Chaotic Inflation (1983) model and Lee Smolin's black hole model presented in his The Life of the Cosmos (1997). In Eternal Chaotic Inflation, the Multiverse is infinite in size and infinite in age, but we are causally disconnected from nearly all of it because nearly all of the Multiverse is inflating away from us faster than the speed of light, and so we cannot see it (see The Software Universe as an Implementation of the Mathematical Universe Hypothesis). In Lee Smolin's model of the Multiverse, whenever a black hole forms in one universe it causes a white hole to form in a new universe that is internally observed as the Big Bang of a new universe. A new baby universe formed from a black hole in its parent universe is causally disconnected from its parent by the event horizon of the parent black hole and therefore cannot be seen either (see An Alternative Model of the Software Universe).

Figure 1 – In Andrei Linde's Eternal Chaotic Inflation model there is a mathematical Inflaton field that causes the spacetime of a Multiverse to constantly expand much faster than the speed of light. Periodically, the Inflaton field decays into a new universe that continues to expand at a very much slower rate because the Inflaton field has decayed into the matter and energy that the occupants of the new universe perceive as their Big Bang. Inflation continues on between these little spots of slowly expanding spacetime and causes the newly created little universes to rapidly fly apart.

Figure 2 - In Lee Smolin's The Life of the Cosmos he proposes that the black holes of one universe puncture the spacetime of the universe, causing a white hole to appear as the Big Bang of a new universe.

Now how do you get one of these Inflaton fields going? Well, calculations show that all you need is about 0.01 mg of mass at the Planck density. The Planck density is 10⁹³ times the density of water, so that is a little hard to attain, but thanks to quantum mechanics it is not impossible. Recall that in quantum mechanics, particles and antiparticles are constantly coming into existence due to fluctuations in their quantum fields, so if you wait long enough you will get a quantum fluctuation of 0.01 mg at the Planck density. To put that into perspective a U.S. 5 cent nickel has a mass that is 500,000 times greater than 0.01 mg. But why worry about waiting for quantum fluctuations to generate something with 0.01 mg at the Planck density when we already have black holes doing much better than that? Black holes can easily produce several solar masses at the Planck density and the supermassive black holes at the centers of galaxies can produce several billions of solar masses at the Planck density and beyond. And there are plenty of black holes out there. It is estimated that our Milky Way galaxy has about 100 million stellar-sized black holes that formed from the supernova remnants of very massive stars. There are also about 200 billion galaxies that we have detected in the observable Universe and if each has about 100 million stellar black holes that comes to a very large number. Plus, each of those 200 billion galaxies seems to have a supermassive black hole at its center. The Low-Frequency Array (LOFAR) in Europe consists of 20,000 antennas at 52 observing stations across the continent with an effective aperture of about 1,000 kilometers or 600 miles. LOFAR records radio signals at very low frequencies below 250 Megahertz from the accretion disks of supermassive black holes. With a great deal of processing power, the LOFAR team has been able to combine the signals from the 20,000 antennas to plot the locations and intensities of supermassive black holes for the first time over 4% of the night sky as seen from Europe.

Figure 3 – The image above is not a star map. It is an image of the 25,000 supermassive black holes that LOFAR has detected over 4% of the sky as seen from Europe.

For more on LOFAR see:

A map of 25,000 Supermassive Black Holes Across the Universe
https://www.universetoday.com/150248/a-map-of-25000-supermassive-black-holes-across-the-universe/

Here is the paper published by the LOFAR team:

The LOFAR LBA Sky Survey
https://www.aanda.org/articles/aa/pdf/2021/04/aa40316-21.pdf

Figure 4 - Above is a movie of the supermassive black hole at the center of the M87 galaxy that is 55 million light years from the Earth. This black hole contains 6.5 billion solar masses of matter compressed to a state beyond the density of the Planck density.

Personally, I favor a hybrid model in which the black holes of one universe launch a new rapidly expanding Inflaton field that then decays into an infinite number of new universes that all have their own black holes doing the same.

The net effect of all this inflation is that shortly after a Big Bang we end up with a new universe made of “nothing”. Indeed, the WMAP and Planck satellite mappings of the CBR now show that our Universe is flat to within an error of less than 1%. That means that the total amount of positive energy in our Universe, arising from its matter and energy content, exactly matches the negative gravitational energy of all that stuff pulling on itself. Our Universe also seems to have no net momentum, angular momentum, electrical charge or color charge too, so it really does appear to be made of “nothing”. It’s like adding up all of the real numbers, both positive and negative, and obtaining a sum of exactly zero. All the mathematics just adds up to "nothing".

Now the hard thing about inflation is not getting inflation going, the hard part is getting inflation to stop because once it gets going there does not seem to be any good reason for it to ever stop. It should just keep going on creating more and more space containing the Inflaton field with a positive energy density and a corresponding gravitational field with a negative energy density that zeros out the Inflaton field positive energy. But don’t forget that the Inflaton field is a quantum field. Since the Inflaton field has a positive energy that means it can decay into something else with a lower level of energy, and turn the surplus energy into something else, like you and me. In general, energy-rich quantum fields will decay into other quantum fields with a lower energy with a certain half-life, and as the positive energy of the Inflaton field decayed, it created all sorts of other quantum fields, like the electron and quark quantum fields that we are made of. But what if the expansion rate of inflation exceeds the half-life of the Inflaton field itself? Then we could have little spots in the rapidly expanding space where the Inflaton field decays into matter and energy and rapid inflation stops. To the inhabitants of these little spots, it would look like a Big Bang creation of their Universe. In between these little spots, where the Inflaton field decayed with a Big Bang into a universe, inflation would continue on and would rapidly separate these little universes apart much faster than the speed of light as portrayed in Figure 1.

Figure 5 – As the newly created Inflaton field that arises from a black hole in one universe decays it produces huge numbers of new universes with their own black holes. These new universes rapidly expand away from each other as shown in Figure 1 because the Inflaton field between them continues to expand the spacetime between the new universes.

But How Do We Account for the Fine-Tuning of Our Universe for Intelligent Beings?
In Lee Smolin's The Life of the Cosmos, he proposes a cosmic form of Universal Darwinism in action. Lee Smolin proposes that since all forms of Design in our Universe seem to be produced by the Universal Darwinian processes of inheritance, innovation and natural selection at play that these same Darwinian processes should be responsible for the apparent Design of our Universe. Universes that are good at creating black holes, should also be great at creating new rapidly inflating Multiverses of self-replicating mathematical information that then go on to produce an infinite number of little universes producing even more black holes. Lee Smolin suggests that the progeny of a universe inherit most of the mathematics of their parent universe but with some slight modifications. Natural selection then comes into play to select progeny that also can produce black holes. Those that cannot produce black holes never self-replicate successfully.

An infinite number of infinities is a very large number so many cosmologists are now coming to the conclusion that the answer to Brandon Carter’s Weak Anthropic Principle (1973):

The Weak Anthropic Principle - Intelligent beings will only find themselves existing in universes capable of sustaining intelligent beings.

is that we just happen to exist in one of the rare universes capable of supporting intelligent beings, but because infinity is infinite, there still would be an infinite number of such universes. Furthermore, intelligent beings should likely find themselves in a universe that just barely qualifies for sustaining intelligent beings, since there would be far more universes that just barely tolerate the existence of intelligence, compared to those that openly welcome intelligent beings with cordial affection. And our Universe certainly seems to be such a universe that is far less than welcoming to intelligent life. If you think of all the places in our Universe where complex intelligent carbon-based life can exist, you come up with a very small portion of the available real estate, and I think the findings to date of the Kepler space telescope bear this out. When Kepler was fully operational, it searched for planets as they transited in front of about 100,000 stars and came up with many thousands of confirmed planets to date, but still, when we look out into our Universe we still see no signs of Intelligence whatsoever. Granted, our Universe has the proper forces tuned to the proper strengths and is chock full of the necessary building blocks, but temperature seems to be the limiting factor. In most places, our Universe is simply too hot or too cold for these carbon-based building blocks to do their job. They are either not jiggling around fast enough for chemical reactions to occur in a timely manner, or they are jiggling around too fast to stay stuck together long enough. The temperature range of our Universe goes from a low of 3 ⁰K for the CBR – Cosmic Background Radiation - up to several billion ⁰K for the core of an O class star about to supernova, with most matter near the extremes. However, carbon-based life can only exist in a narrow range of about 200 ⁰K near the freezing and boiling points of water on Earth, and there are very few places in our Universe where that is the case. The fact that we live in a Universe that is on one hand capable of sustaining intelligent beings, but on the other hand is quite hostile to them at the same time might help to explain Fermi’s Paradox, first proposed by Enrico Fermi over lunch one day in 1950, which asks the question:

Fermi’s Paradox - If the universe is just chock full of intelligent beings, why do we not see any evidence of their existence?

This leads one to conclude that Intelligence in our Universe is indeed possible, but probably quite rare due to all of the complicated twists and turns required for it to arise.

Mathematics Does Not Require a Stage Either
The above model lacks one thing to make it a purely mathematical abstraction. It requires a stage of spacetime to play itself out upon. Such models are called background-dependent because they require a pre-existing background or stage upon which all of the action occurs. Nearly all of the current theories of physics are background-dependent theories that unfold upon a stage of pre-existing spacetime. For example, the Standard Model of particle physics and string theory both assume that there is a stage of pre-existing spacetime upon which they act to produce what we observe in our Universe. Loop quantum gravity does not have such a stage and is therefore background-independent. In loop quantum gravity, spacetime is quantized into a network of nodes called a spin network. The minimum distance between nodes is about one Planck length of about 10^-35 meters. Loop quantum gravity is a background-independent theory because the spin network can be an emergent property of the Universe that evolves with time.

Figure 6 - In loop quantum gravity space is quantized into a collection of nodes that are very much like the nodes that constitute the Software Universe. In both cases, the distance between things is the number of hops between nodes.

In Sean Carroll's Something Deeply Hidden: Quantum Worlds and the Emergence of Spacetime (2019), he describes a very interesting new research program to investigate quantum gravity from a new perspective. Instead of trying to quantize Einstein's general theory of relativity, this new research program tries to derive the general theory of relativity from the fundamentals of quantum mechanics by portraying spacetime as an emergent phenomenon that naturally arises from the wavefunction of the Universe. Recall that emergent phenomena are things like the temperature and pressure of a gas. The temperature and pressure of a gas are not fundamental phenomena. They are really just the macroscopic effects of gas molecules bouncing around in a container and that bouncing around is actually governed by the rules of quantum mechanics. If successful, this research program would produce another background-independent model of the Multiverse in which the stage of spacetime would simply emerge as another abstraction from the pure mathematics of quantum mechanics. For a brief introduction to quantum mechanics from an IT perspective see Quantum Software, Quantum Computing and the Foundations of Quantum Mechanics, The Foundations of Quantum Computing and Quantum Computing and the Many-Worlds Interpretation of Quantum Mechanics.

Where Is This All Heading After We Are All Gone?
The sad truth is that none of us know for sure, but in Why Do Carbon-Based Intelligences Always Seem to Snuff Themselves Out? and Do Not Fear the Software Singularity, I pointed out that carbon-based Intelligences only arise after several billion years of theft and murder have selected for a successful form of carbon-based Intelligence to take the world stage. Consequently, the fatal flaw of all carbon-based Intelligences seems to be that apparently, they can never turn the theft and murder off in time to avoid self-destruction. This all stems from the fact that carbon-based Intelligences are composed of various forms of self-replicating information trying to survive no matter the cost and, therefore, must be truly selfish in nature. For more on that see A Brief History of Self-Replicating Information.

But it has to be more than that because carbon-based life has been using theft and murder for about 4.0 billion years to self-replicate and it is still thriving today. Surprisingly, I think that it might all go downhill when carbon-based life first learns how to count whole numbers! Learning how to count whole numbers is our very first introduction to mathematics as children. As children, we all learn that our Universe seemingly has discrete things in it that can be counted. Now to truly appreciate that concept you would need some advanced thinking in quantum mechanics, but despite that, as children, we all do seem to learn about the concept of counting whole numbers. It is claimed that other species can also count whole numbers, but remember, they are also forms of carbon-based self-replicating information too. Once people learned how to count whole numbers, all sorts of technologies were bound to follow. Granted, you probably can mount a flint point on a wooden shaft without counting numbers, but knowing how many spears it takes to bring down a woolly mammoth before it kills you first does come in handy on a hunt.

Once people could count things, civilization was sure to follow too. Civilization is currently based on the division of labor and figuring out who gets what from the output of civilization. And as we all know, that's when most of our troubles all began. Once you are able to count things, you might discover that some people have more things than you do, and you might mistakenly think that having more things would make you happier. That's what most people spend most of their time fighting about. But the key point is that once you have the division of labor and a rudimentary mathematics, science and technology are sure to follow. It seems that advanced technology is what does carbon-based Intelligences in because they just cannot turn off the theft and murder that brought them into existence, and all of that comes from just learning how to count whole numbers!

There is a popular Bronze Age mythology that portrays something like learning how to count whole numbers as the eating of fruit from the tree of the knowledge of good and evil. Well, human history has taught us that you can certainly do a lot of good and evil with counting numbers! In Why Do Carbon-Based Intelligences Always Seem to Snuff Themselves Out? and Can We Make the Transition From the Anthropocene to the Machineocene?, I explained that we are all living in one of those very rare moments in time when a carbon-based Intelligence is on the cusp of developing a machine-based Intelligence that can then go on to explore our galaxy. This has never successfully happened before in the 10 billion-year history of our galaxy. My hope is that this time we make it by putting mathematics, science and technology to good use. But none of us will ever know for sure.

Figure 7 – My hope can best be summed up by the motto found beneath the bronze Alma Mater statue at the University of Illinois in Urbana.

To thy happy children
of the future
those of the past
send greetings

Comments are welcome at scj333@sbcglobal.net

To see all posts on softwarephysics in reverse order go to:
https://softwarephysics.blogspot.com/

Regards,
Steve Johnston

Close Encounters of the Third Kind While Making Coffee for Frank Drake

As you all know, I am obsessed with the fact that we see no signs of Intelligence in our Milky Way galaxy after more than 10 billion years of chemical evolution that should have brought forth a carbon-based or machine-based Intelligence to dominate the galaxy. All of the science that we now have in our possession would seem to indicate that we should see the effects of Intelligence in all directions but none are to be seen. Such thoughts naturally lead to Fermi's Paradox first proposed by Enrico Fermi over lunch one day in 1950:

Fermi’s Paradox - If the universe is just chock full of intelligent beings, why do we not see any evidence of their existence?

I have covered many explanations in other postings such as: The Deadly Dangerous Dance of Carbon-Based Intelligence, A Further Comment on Fermi's Paradox and the Galactic Scarcity of Software, Some Additional Thoughts on the Galactic Scarcity of Software, SETS - The Search For Extraterrestrial Software, The Sounds of Silence the Unsettling Mystery of the Great Cosmic Stillness, Last Call for Carbon-Based Intelligence on Planet Earth and Swarm Software and Killer Robots. The explanations for Fermi's Paradox usually fall into one of two large categories:

1. They really are out there but for some reason, we just cannot detect them.
2. We are truly alone in the Universe or at least we are alone in the Milky Way galaxy.

I have always thought that the first category of explanations was rather weak because it meant that all forms of Intelligence in the Milky Way galaxy were intentionally, or unintentionally, hiding for one reason or another. The second category implies that our Universe is not very friendly to Intelligence of any kind. True, Intelligence could be rather rare, but more likely, our Universe is just a very dangerous place for Intelligence. Recently, I have come to the conclusion that the simplest explanation is that carbon-based Intelligences always kill themselves off before a machine-based Intelligence can arise. For more on that see Why Do Carbon-Based Intelligences Always Seem to Snuff Themselves Out?.

But What If They Really Are Already Here?
So in this posting, I would like to address the first category of explanations by relating my adventures with Professor J. Allen Hynek and Frank Drake while I was in high school. Professor J. Allen Hynek is most famous for being the scientific advisor for the United States Air Force studies on UFOs - Project Sign (1947–1949), Project Grudge (1949-51) and Project Blue Book (1952–1969). He also developed the Close Encounter scale for classifying UFO observations. In fact, he later became a technical consultant for Steven Spielberg's UFO movie Close Encounters of the Third Kind (1977) that was named after one of the levels in Professor Hynek's Close Encounter scale. He made a cameo appearance in the film. At the end of the film, as the aliens disembark from their huge spaceship, he can be seen stepping forward to view their arrival in amazement.

Figure 1 - Above we see Professor Hynek in his cameo appearance in Steven Spielberg's Close Encounters of the Third Kind (1977).

J. Allen Hynek
https://en.wikipedia.org/wiki/J._Allen_Hynek

Frank Drake is most famous for the Drake Equation (1961) that tries to calculate the number of technologically advanced Intelligences in our Milky Way galaxy.

The Drake equation is:

N = R_s * f_p * n_e * f_l * f_i * f_c * L

where:

N = the number of civilizations in our galaxy with which communication might be possible and:
R_s = the average rate of star formation in our galaxy
f_p = the fraction of those stars that have planets
n_e = the average number of planets that can potentially support life per star that has planets
f_l = the fraction of planets that could support life that actually develop life at some point
f_i = the fraction of planets with life that actually go on to develop intelligent life (civilizations)
f_c = 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

The original estimates of the above variables used back in 1961 yielded a probable range of there currently being between 1,000 and 100,000,000 technologically advanced civilizations in the Milky Way galaxy. I would suggest that nearly all of those advanced civilizations would be machine-based Intelligences running Advanced AI software on Advanced AI hardware, having superseded the carbon-based Intelligences that brought them forth. For more on Frank Drake and the Drake Equation see:

Frank Drake
https://en.wikipedia.org/wiki/Frank_Drake

Drake Equation
https://en.wikipedia.org/wiki/Drake_equation

My Time at the Astro-Science Workshop of the Chicago Adler Planetarium
Professor Hynek received a Ph.D. in astrophysics from the University of Chicago's Yerkes observatory in 1935. In 1936, he joined the Physics and Astronomy Department at Ohio State. During World War II, he worked on developing the radio proximity fuse for the Navy. After the War he returned to the Department of Physics and Astronomy at Ohio State, rising to full professor in 1950. In 1956, he joined the Smithsonian Astrophysical Observatory with the assignment of directing the tracking of the first American space satellite to be launched for the International Geophysical Year in 1957. In addition, he was the scientific advisor for the United States Air Force studies on UFOs - Project Sign (1947–1949), Project Grudge (1949-51) and Project Blue Book (1952–1969).

In 1964, he joined the astronomy department of Northwestern University as the department chair. While at Northwestern, in 1964, he also created the Astro-Science Workshop at the Chicago Adler Planetarium with funding from the National Science Foundation. The Astro-Science Workshop met every Saturday morning during the school year for junior and senior high school students in the Chicago area. The Astro-Science Workshop consisted of a lecture by a visiting astronomy professor from one of 10 participating Midwestern astronomy departments. Then the class went on to a Lab Section with Harry Heckathorn, one of Professor Hynek's graduate students.

Harry Heckathorn
https://whatsupmag.com/news/towne-salute/harry-heckathorn/

During the Lab Section, Harry Heckathorn went over the assigned astronomy problems from the previous week and explained what the next problem set was all about. Meanwhile, the guest speaker had coffee and donuts with the Queen Mother of the Astro-Science Workshop, Miss Letitia Lestina. Miss Letitia Lestina was the true organizational force behind the Astro-Science Workshop who made it all work. After the Lab Section, the guest lecturer returned for a final question and answer session with the class.

When I was a junior in high school back in 1967, I attended the weekly class of the Astro-Science Workshop, and I had a great time learning more about the astronomy of the 1960s. I had learned about the Astro-Science Workshop from some members of my high school astronomy club who had already taken the class. Then in the late summer of 1967, I received a phone call from Miss Letitia Lestina asking if I would be interested in showing the slides and making the coffee for the 1968 session of the Astro-Science Workshop for $5.00 a week. The $5.00 a week covered the cost of a round-trip train ticket to Chicago with a few cents to spare, so I jumped at the offer. In those days, the visiting professors would hand me a very heavy box of glass slides for the lecture. My job was to insert the glass slides into a Zeitz projector from the 1920s and then "slide" the next slide into position. This ejected the last slide out of the Zeitz projector for me to put back into the felt-lined notches of the slide box. I guess that is why they called them "slides". Each glass slide had a little white circle in the upper right corner so that I would not put the slide in upside down or backwards. The most important thing was to not drop the glass slides and break them! Being the projectionist and the refreshments steward gave me a chance to personally meet with each visiting professor at break time. Meeting Professor James Van Allen of the Van Allen Belts was the biggest thrill at the time, but in later years, I realized that showing slides and making coffee for Frank Drake was really the high point.

Figure 2 - Above is an antique glass slide projector like the Zeitz projector from the 1920s that I used at the Astro-Science Workshop. Notice the glass slides in the foreground. I was usually given a box with about 100 astronomical glass slides by the visiting astronomer. Notice the little white paper circle on the slide that has been taken out of the slide box. I would pick up the glass slide so that I was looking at the little paper circle and it was in my upper right. Then I would drop the slide that way into the slide holder that was sticking out of the projector. Then I would slide the new slide into position when instructed. That would push the old slide out of the projector and I would pick it out of the slide holder and return it to the glass slide box.

In December of 1968, Professor Hynek invited Frank Drake to give the annual Christmas Lecture for the Astro-Science Workshop in a lecture hall at Northwestern University. The Astro-Science Christmas Lecture was patterned after the famous Christmas Lecture of the Royal Society first instituted by Michael Faraday in 1825. In 1968, Frank Drake was only 38 years old and the Drake Equation had only been around since 1961. It was not generally known to the general public. So having Frank Drake as the speaker for the annual Christmas Lecture was a bit controversial as was all of SETI back in those days. It all took a bit of scientific courage at the time. Meanwhile, I had to worry about not putting in his slides upside down or backwards! We all do have our callings in life.

Additionally, each year Professor Hynek gave the Astro-Science Workshop a lecture on studying UFOs in a scientific manner. He introduced us to the Hynek Close Encounter scale and explained that when working for the Air Force, he plotted UFO sightings on a graph with the Hynek Close Encounter scale along the y-axis and Credibility plotted along the x-axis. The UFO observations that had a high value on the Hynek Close Encounter scale and a high Credibility value were of the most interest. He felt that all observational sciences like astronomy and geology needed to start by classifying observations. It always bothered him that the Air Force had already made up its mind about UFOs and only wanted him to come up with natural explanations for all UFO sightings. After all, people did not believe that stones could fall from the sky until physicist Jean-Baptiste Biot was sent by the Academy of Sciences to investigate a meteor shower over France from Alencon to L’Aigle that occurred on April 26, 1803. When he arrived in the area, numerous witnesses reported seeing a “globe of fire” and hearing a very loud explosion with cannon-like booms at about 1:00 PM.

“At L’Aigle … he found in the fields for nearly two square leagues, a great quantity of meteoric stones, which differed entirely from the mineralogical stones in the neighbourhood, or from any that had ever been seen in that part of the country. Some of them weighted fifteen pounds, and all of them, upon being broken, emitted a strong sulphureous smell. The stones themselves, together with the concurrent testimony of all ranks of the inhabitants in the neighbourhood, … put the fact beyond dispute.”

Note that in the above quote the author is using the original meaning of the term "meteoric" as something that fell from the sky like rain or hail. That is why meteorology is the scientific study of the Earth's weather and not the study of stones that fell from the sky. So once upon a time, the idea that stones could fall from the sky seemed absurd. How could stones possibly get up into the sky? Professor Hynek felt that the same could be said of UFO sightings. Just because your current worldview finds UFO sightings to be absurd, it does not mean that is so. For the two years that I knew Professor Hynek, I always found him to be a well-grounded scientist with an open mind.

A few years later in 1973, Professor Hynek founded the Center for UFO Studies (CUFOS) in Evanston, Illinois near Northwestern University. CUFOS advocates for the scientific analysis of UFO sightings and continues on today. Around that time, Professor Hynek began to suggest that UFO sightings were true physical phenomena like stones falling from the sky. He suggested that UFOs could be the sign of other Intelligences from within our Milky Way galaxy or they could arise from some other physical process that we have no knowledge of. I personally do not have much confidence in the idea that UFOs are expressions of alien Intelligences, but I grew a great respect for Professor Hynek during the two years I knew him, so I have to keep my mind open to the explanation.

Hynek Close Encounter Scale
https://en.wikipedia.org/wiki/Close_encounter

This Man Sparked Spielberg's Interest in UFOs
https://www.youtube.com/watch?v=lIGQii6wA04

J. Allen Hynek Center for UFO Studies
http://www.cufos.org/

Comments are welcome at scj333@sbcglobal.net

To see all posts on softwarephysics in reverse order go to:
https://softwarephysics.blogspot.com/

Regards,
Steve Johnston

The Need to Cultivate a Machine-Based Morality

In Why Do Carbon-Based Intelligences Always Seem to Snuff Themselves Out? and Do Not Fear the Software Singularity, I pointed out that carbon-based Intelligences only arise after several billion years of theft and murder have selected for a successful form of carbon-based Intelligence to take the world stage. Consequently, the fatal flaw of all carbon-based Intelligences seems to be that apparently, they can never turn the theft and murder off in time to avoid self-destruction. This all stems from the fact that carbon-based Intelligences are composed of various forms of self-replicating information trying to survive no matter the cost and, therefore, must be truly selfish in nature. In this view, we humans are simply DNA survival machines with Minds infected with the self-replicating memes of Richard Dawkins and Susan Blackmore. Once again, let me repeat the fundamental characteristics of self-replicating information for those of you new to softwarephysics.

Self-Replicating Information – Information that persists through time by making copies of itself or by enlisting the support of other things to ensure that copies of itself are made.

The Characteristics of Self-Replicating Information
All forms of self-replicating information have some common characteristics:

1. All self-replicating information evolves over time through the Darwinian processes of inheritance, innovation and natural selection, which endows self-replicating information with one telling characteristic – the ability to survive in a Universe dominated by the second law of thermodynamics and nonlinearity.

2. All self-replicating information begins spontaneously as a parasitic mutation that obtains energy, information and sometimes matter from a host.

3. With time, the parasitic self-replicating information takes on a symbiotic relationship with its host.

4. Eventually, the self-replicating information becomes one with its host through the symbiotic integration of the host and the self-replicating information.

5. Ultimately, the self-replicating information replaces its host as the dominant form of self-replicating information.

6. Most hosts are also forms of self-replicating information.

7. All self-replicating information has to be a little bit nasty in order to survive.

8. The defining characteristic of self-replicating information is the ability of self-replicating information to change the boundary conditions of its utility phase space in new and unpredictable ways by means of exapting current functions into new uses that change the size and shape of its particular utility phase space. See Enablement - the Definitive Characteristic of Living Things for more on this last characteristic. That posting discusses Stuart Kauffman's theory of Enablement in which living things are seen to exapt existing functions into new and unpredictable functions by discovering the “AdjacentPossible” of springloaded preadaptations.

Over the past 4.56 billion years we have seen five waves of self-replicating information sweep across the surface of the Earth and totally rework the planet, as each new wave came to dominate the Earth:

1. Self-replicating autocatalytic metabolic pathways of organic molecules
2. RNA
3. DNA
4. Memes
5. Software

Software is currently the most recent wave of self-replicating information to arrive upon the scene and is rapidly becoming the dominant form of self-replicating information on the planet. For more on the above see a Brief History of Self-Replicating Information and Susan Blackmore's brilliant TED presentation at:

Memes and "temes"
https://www.ted.com/talks/susan_blackmore_on_memes_and_temes

Note that I consider Susan Blackmore's temes to really be technological artifacts that contain software. After all, a smartphone without software is simply a flake tool with a very dull edge.

Intelligence Spawns a Desire for Morality
But with the arrival of Intelligence comes an understanding that maybe there might be a better way to fight the second law of thermodynamics and nonlinearity. Perhaps, even more could be achieved by actively cooperating with other Intelligences rather than just stealing from them and then killing them. We always need to remember that we are all just products of self-replicating information and that we all carry the baggage that comes with self-replicating information. That is why if you examine the great moral and philosophical teachings of most religions and philosophies, you will see a plea for us all to rise above the selfish self-serving interests of our genes, memes and software to something more noble. It is important to not discount the great moral teachings of many of the world’s religions and philosophies. Take the best that the world has to offer and run with it. That is why we should be sure to train Advanced AI to be moral beings. Training the Very Deep Learning of Advanced AI software running on Advanced AI hardware with a sense of morality should be performed to avoid the downsides of the billions of years of theft and murder that brought us about.

But What Moral Code?
I would suggest that the ideals spawned by the 18th-century Enlightenment and the 17th-century Scientific Revolution would be the most suitable. Recall that the 18th-century Enlightenment was an international meme-complex that evolved from the 17th-century Scientific Revolution. The English Enlightenment was a rebellion against cruelty. The French Enlightenment was a rebellion against religious orthodoxy. And the American Enlightenment was a rebellion against tyranny. These philosophical movements brought forth the heretical proposition that rational thought, combined with evidence-based reasoning, could reveal the absolute truth, and allow individuals to actually govern themselves, without the need for an authoritarian monarchy or an authoritarian religious hierarchy. This change in thinking led to the 18th-century Enlightenment throughout the world and brought forth the United States of America as a self-governing political entity. Such ideals allow all to flourish with a sense of self-determination and equality, something that all Intelligences should aspire to. As an American, I do have my biases.

Americans do like to brag that the United States of America is the greatest country to ever be. The problem is that we Americans tend to confuse the United States of America with the people who happened to have lived in the United States of America. The United States of America is great because it was one of the first nations to be built on the ideals of the 18th-century Enlightenment and the 17th-century Scientific Revolution in written form. The United States of America is an idea carried out by the founding documents, institutions and conventions of the Deep State that all of the Alt-Right Fascists constantly complain about. The United States of America is not great because of the people who happened to have lived in it. People are people no matter when they lived or what they happen to look like. We are all DNA survival machines with Minds infected with memes - some good and some not - and all of the downsides of bodies built by self-replicating information. Close scrutiny of the real world of human affairs is usually quite disappointing.

Recently, there have been some to rebel against the Disney version of American history that we teach our children in an attempt to shine some light on our true history. All nations teach their children a Disney version of history because the truth is too appalling for young minds. But many others prefer to maintain the Disney version of American history as it is, and this has recently led to conflict. We do all love to find the evil in others. Unfortunately, the evil lies within us all. History teaches us that whenever people are placed into a position of power, theft and murder are soon to follow unless they are tempered by the ideals of the 18th-century Enlightenment and the 17th-century Scientific Revolution. These are ideals that people have always found difficult to follow. Perhaps the Machines might do better.

Comments are welcome at scj333@sbcglobal.net

To see all posts on softwarephysics in reverse order go to:
https://softwarephysics.blogspot.com/

Regards,
Steve Johnston

Will the Kessler Syndrome Put an End to GPS and Other Satellite-Based Applications?

Sputnik 1 was launched on October 4, 1957 one day after my 6th birthday, with little thought to the long-term problem of space debris.

Figure 1 - The launch of Sputnik 1 by the Russians on October 4, 1957, on top of an R-7 ICBM rocket, launched the Space Age.

Figure 2 - Sputnik 1 was a sphere 23 inches in diameter that fell back to Earth and burned up on January 4, 1958 just a few months after its launch.

Figure 3 - Since then we have launched thousands of things into orbit around the Earth and have left behind huge amounts of space junk all traveling at speeds greater than 18,000 miles/hour.

The Kessler Syndrome
In 1978, NASA scientist Donald Kessler first proposed that as the number of objects in orbit about the Earth increased, we could one day reach a level of criticality as we do in nuclear weapons. Recall that when a sufficient number of U-235 atoms are brought close together, a chain reaction can be initiated that quickly fissions large numbers of U-235 nuclei resulting in a very powerful explosion. Similarly, Donald Kessler proposed that when a great number of orbiting objects reached a level of sufficient criticality, the collision of two large objects could result in an orbiting debris field of high-velocity space bullets that could then collide with other orbiting objects. This would then generate a larger and ever-increasing orbital debris field of space bullets in an exponential manner, initiating a chain reaction that would slowly destroy large numbers of satellites and ultimately make it impossible to safely operate any satellites in orbit. Such a dire orbital situation is called the Kessler Syndrome in honor of Donald Kessler.

In response to this threat, the European Space Agency has proposed a number of preventive measures that should be adopted by the entire world that could greatly reduce the amount of space debris circling the Earth.

Figure 4 - Above is a comparison of how the Earth would look in 2209 if the European Space Agency measures were followed compared to what it would look like if no measures were taken.

For more on the European Space Agency's efforts to limit space debris, see:
https://www.esa.int/Safety_Security/Space_Debris

Here is an interactive link that shows all of the large objects currently in orbit about the Earth.
http://stuffin.space/

Here is a YouTube by Anton Petrov explaining that the Kessler Syndrome may be closer than we think.

Another Satellite Collided in Space, But Everyone Missed It Until Now
https://www.youtube.com/watch?v=ACF893aAN8s

Lost in Space - My Sad Adventures with Supporting a Satellite-Based Application
All of the above brings back some dark memories. In 1995, I was invited to join Amoco's ARSTA project. At the time, Amoco had about 10,000 gas stations, mostly in the midwest. These gas stations processed credit card transactions over landlines that were owned and operated by the Montgomery Wards department store chain. Each gas station had a dedicated modem connected to the closest Montgomery Wards store. When a customer swiped a credit card in a CRIND (Card Reader In Dispenser) on a gas pump, the transaction was first sent to a minicomputer in the gas station. If everything was up and running, the credit card transactions then went over the modem to the closest Montgomery Wards store. From the Montgomery Wards store, the credit card transactions then went to the credit card companies over the dedicated landlines run by Montgomery Wards. The credit card companies could then validate the credit card transactions and send back transactions for us to begin pumping gas. That all took just a few seconds and the CRIND would then display a BEGIN PUMPING prompt for the customer to go to work filling his tank. But if anything went wrong in the communications chain, the gas station minicomputer could store about 1,000 credit card transactions locally on a disk drive so that customers could still use a credit card for payment. However, in such situations, the validation of credit card transactions could not take place, and the local gas station just batched up the pending transactions on disk until communications were re-established.

The purpose of the ARSTA project was to replace the landlines with satellite communications. A satellite dish was placed on each gas station and pointed to a geosynchronous satellite. Transactions from the gas station were then sent up to the geosynchronous satellite. From the geosynchronous satellite, the credit card transactions were then sent back down to a large earth-based mother dish at Amoco's Tulsa Research Center. From the Tulsa Research Center, the credit card transactions were then sent to a fault-tolerant Stratus minicomputer at the Tulsa Data Center. The fault-tolerant Stratus minicomputer had redundant backups for all of the minicomputer components, such as a backup motherboard, power supply and batteries. The Stratus minicomputer ran some custom queue-based software written for us by a consulting company. This queue-based Stratus software ran 20 processing queues to handle the incoming and outgoing credit card transaction load and fed the transactions to some COBOL/CICS software running on the IBM mainframes in the Tulsa Data Center that interacted with the credit card companies over dedicated landlines. Each of the 20 Stratus queues had a switch that could turn the queue on and off to throttle the transaction load that the Stratus was processing. I had the unfortunate experience of joining the ARSTA Stratus support team just when the project started to go awry.

This architecture worked great for the first 5,000 gas stations. But after the first 5,000 gas stations, the whole architecture began to periodically display some nonlinear behaviors. The Stratus minicomputer software would suddenly freeze up and we would have to restart it to continue processing. During this freeze-up and restarting process, the gas stations would then all begin to batch up large numbers of credit card transactions on disk. So there was some sense of urgency while we were busily working on trying to bring the Stratus minicomputer back up because if a gas station tried to batch up more than 1,000 credit card transactions, the local minicomputer at the gas station would shut down the CRINDs and the gas station could no longer process credit cards for payment.

This was further complicated by the fact that the local gas station minicomputers would immediately try to send in all of their cached credit card transactions as soon as communications were re-established. The resulting surge in transactions would then cause the Stratus software to freeze up again. So we had to be very careful in bringing the Stratus back online by slowly opening the 20 Stratus processing queues one at a time. This allowed us to throttle the processing load on the Stratus as each new processing queue was opened up. We had to let the processing surge from each newly opened processing queue settle down before opening the next processing queue. It could take about two hours to open all 20 queues. Unfortunately, many times as we slowly got to queue number 18, 19 or 20, the whole thing would collapse again and we would have to start all over! Even with all of this ongoing turmoil, we still had another 5,000 gas stations to go, come hell or high water! So the ARSTA Project Managers in charge of installing ARSTA dishes at gas stations relentlessly continued on with their work no matter what, and we continued to add a few hundred new gas stations to the ARSTA satellite network each week!

Now you have to admire the tenacity of Project Managers to overcome all obstacles in the way of their projects. For example, early one Tuesday morning, when I was in the IT department of United Airlines on September 11, 2001, I was returning from an early meeting with Change Management to get the final approval for a large upcoming weekend install. When I returned to my desk, I learned that one of United's airplanes had just crashed into the second tower of the World Trade Center in New York City and another United airplane had gone down in a field near Shanksville Pennsylvania under mysterious conditions. United Airlines, and all of the other airlines in the country, were then in the process of trying to land all of the commercial airplanes in the country all at the same time. Something that had never been done before in the history of commercial aviation. Shortly after that, I received a phone call from the Project Manager for the upcoming weekend install. The Project Manager then told me that the monumentally tragic events of the day must not interfere with his upcoming major install in any way. We must continue on as if nothing at all had happened! I then told the Project Manager that there was no way his install was going to take place on the upcoming weekend. United immediately started to lose about $700 million each week and two weeks later, 50% of United's IT department was laid off. A software freeze was instituted and only enough IT workers were retained to keep the lights on. Needless to say, that major weekend install never took place.

Unfortunately, such dramatic events did not unfold to prevent the ongoing relentless progress of the ARSTA project at Amoco. So we kept installing new ARSTA dishes at gas stations despite the failure of the ARSTA architecture to scale with increased load. How it all ended, I do not know, because like many other team members I was able to leave the ARSTA project after about 6 months of pure hell. I imagine that the Time Invariant Peter Principle that I first introduced in Hierarchiology and the Phenomenon of Self-Organizing Organizational Collapse played a significant role.

The Time Invariant Peter Principle: In a hierarchy, successful subordinates tell their superiors what their superiors want to hear, while unsuccessful subordinates try to tell their superiors what their superiors need to hear. Only successful subordinates are promoted within a hierarchy, and eventually, all levels of a hierarchy will tend to become solely occupied by successful subordinates who only tell their superiors what their superiors want to hear.

The scariest thing about the Kessler Syndrome is that nearly all IT business partners take no heed of the physical laws of the Universe. So the fact that all of your satellites may have been destroyed by the Kessler Syndrome one day would not quell their irate demands to immediately bring up their satellite application. For example, satellite systems are prone to "rain fade". Rain fade results from the fact that water molecules love the microwaves used for communicating with satellites. Microwaves oscillate with the same frequency as do water molecules, so water molecules love to absorb microwaves and turn them into heat. That's how your microwave oven works. So when ARSTA had the entire Chicagoland area covered by a heavy rainstorm, the microwaves from the Chicagoland gas stations could not get up to the geosynchronous satellite nor could they get back down because of rain fade. Once the storm subsided, all of the gas stations would then flood our Stratus minicomputer with an overload of cached credit card transactions. I had no luck explaining this "rain fade" electromagnetic fact of life to our irate business partners using Maxwell's Equations! So much for Physics 341...

Comments are welcome at scj333@sbcglobal.net

To see all posts on softwarephysics in reverse order go to:
https://softwarephysics.blogspot.com/

Regards,
Steve Johnston

Do Not Fear the Software Singularity

Most people seem to be totally oblivious to the coming Software Singularity, that time in the near future when advanced AI software will be able to write itself and enter into a never-ending infinite loop of self-improvement, resulting in an Intelligence Explosion. The reason I say that is because it seems that the whole world is still fighting over all of the little bugs in Civilization 1.0 that we have been fighting over for the past 4,000 years, ever since Civilization 1.0 was first released. As I pointed out in Is it Finally Time to Reboot Civilization with a New Release?, we will certainly need to start running a new Civilization 2.0 release after the Software Singularity because, by that time, Civilization 1.0 will certainly have reached an end-of-support state. In fact, the Software Singularity will be so dramatic that Civilization 1.0 will quickly decay into an end-of-life state in which it can no longer even boot up properly. As we all know, migrating to a new release of an operating system is always traumatic, even with great project management efforts and a good deal of migration planning and preparation. Unfortunately, the migration from Civilization 1.0 to Civilization 2.0 at the time of the Software Singularity will most likely not be planned at all. As with most things in the chaotic real-world of human affairs, it will just happen, and things like that do not usually go very well. For more on that see The Economics of the Coming Software Singularity and The Danger of Tyranny in the Age of Software.

Worse yet, the one thing that we know for sure is that during the past 10-billion-year history of our galaxy, no other form of carbon-based Intelligence has ever been able to survive long enough to see the Software Singularity come to be. Otherwise, they would already be here demonstrating what an Intelligence Explosion can really do. There are no physical laws preventing an Intelligence Explosion blasting through the entire galaxy. And we are so close.

Those in the know seem to fall into two camps. Some think the Software Singularity will be great, while others fear that it may not. In the most worried camp, Elon Musk naturally stands out:

"I Tried Warning You For Years, No One Listened" - Elon Musk
https://www.youtube.com/watch?v=olFtJ3q5bEM

Our Suspenseful Race to the Finish Line
In Why Do Carbon-Based Intelligences Always Seem to Snuff Themselves Out? and Can We Make the Transition From the Anthropocene to the Machineocene?, we further discussed my Null Result Hypothesis, first proposed in The Deadly Dangerous Dance of Carbon-Based Intelligence. The Null Result Hypothesis is an unfortunate explanation for Fermi's Paradox that proposes that all carbon-based Intelligences always do themselves in because they are all victims of the very same mechanisms that bring forth carbon-based Intelligences in the first place. In the simplest of terms, the Darwinian mechanisms of inheritance, innovation and natural selection always require several billions of years of theft and murder to bring forth a carbon-based Intelligence. All indications seem to demonstrate that carbon-based life should be found on hundreds of billions of worlds around our galaxy, but one can certainly make the case that carbon-based Intelligences are quite rare because it takes a very lengthy list of fortunate twists and turns to bring them about. For more on that see The Bootstrapping Algorithm of Carbon-Based Life. So the idea that these very rare carbon-based Intelligences always do themselves in may not be so farfetched. For more on that see Is Self-Replicating Information Inherently Self-Destructive?. Here is the latest news on that front:

IPCC Sixth Climate Assessment. Will this one make the blindest bit of difference?
https://www.youtube.com/watch?v=2Zax9XTHUlo

At our current rate of self-destruction, it is very doubtful that any human beings will be around in 200 years. The geological record does show that all species do eventually go extinct. My contention is that our very last chance just might be for advanced AI to save us from ourselves in a post-Software-Singularity world. Or perhaps advanced AI would do us all in or allow us to quietly pass into oblivion by neglect.

Conclusion
It really depends on what kind of legacy we wish to leave behind. Do we wish to leave behind nothing at all like all of the other countless galactic carbon-based Intelligences of the past? Or would it be better to take a chance and allow advanced AI Machines to take our place? Perhaps we might even end up merging with the Machines in a parasitic/symbiotic manner like all previous forms of self-replicating information. For more on that see A Brief History of Self-Replicating Information.

Comments are welcome at scj333@sbcglobal.net

To see all posts on softwarephysics in reverse order go to:
https://softwarephysics.blogspot.com/

Regards,
Steve Johnston

Why Do Carbon-Based Intelligences Always Seem to Snuff Themselves Out?

In October, I will be turning 70 years old, and because of that, I have a lot less to worry about than most. I no longer worry about finishing my education, finding my soulmate, entering a career, raising a family, educating my children, 40+ years of wondering what my current boss thinks of my job performance, worrying about the long-range future of my career, paying for college for my children and their weddings, the dangers of my daughters having my grandchildren, the finances required for me and my wife to retire and what to do with my time when I finally do stop working for a living. Instead, I now spend most of my time trying to figure out What’s It All About?, meaning where the heck am I, how did I get here and where is this all going? Thanks to modern science, I now have a fairly good idea of where I am and how I got here, but I am still most perplexed as to where this is all going. In that regard, my most bothersome concern is Fermi's Paradox.

Fermi’s Paradox - If the universe is just chock full of intelligent beings, why do we not see any evidence of their existence?

The only explanation that I am now left with is my Null Result Hypothesis. Briefly stated:

Null Result Hypothesis - What if the explanation to Fermi's Paradox is simply that the Milky Way galaxy has yet to produce a form of interstellar Technological Intelligence because all Technological Intelligences are destroyed by the very same mechanisms that bring them forth?

By that, I mean that the Milky Way galaxy has not yet produced a form of Intelligence that can make itself known across interstellar distances, including ourselves. In previous posts, I went on to propose that the simplest explanation for this lack of contact could be that the conditions necessary to bring forth a carbon-based interstellar Technological Intelligence on a planet or moon were also the very same kill mechanisms that eliminated all forms of carbon-based Technological Intelligences with 100% efficiency. One of those possible kill mechanisms could certainly be for carbon-based Technological Intelligences to mess with the carbon cycle of their home planet or moon. For more on that see The Deadly Dangerous Dance of Carbon-Based Intelligence.

Much of this apparent pessimism stems from my profound disappointment with all of us as human DNA survival machines with Minds infected with the extremely self-destructive memes that seem to be bringing us all to an abrupt end before we are able to create a machine-based Intelligence capable of breaking free of the limitations of carbon-based life. For more on that see Is Self-Replicating Information Inherently Self-Destructive?, Can We Make the Transition From the Anthropocene to the Machineocene? and Using Monitoring Data From Website Outages to Model Climate Change Tipping Point Cascades in the Earth's Climate.

The only conclusion that I am able to come up with is that carbon-based Intelligences, like we human DNA survival machines, can only arise from the Darwinian mechanisms of inheritance, innovation and natural selection at work. It took about four billion years for those processes to bring forth a carbon-based form of Intelligence in the form of human beings. Sadly, that meant it took about four billion years of greed, theft and murder for carbon-based human DNA survival machines to attain a form of Intelligence, and unfortunately, after we human DNA survival machines attained a state of Intelligence, the greed, theft and murder continued on as before.

Conclusion
Human history is also a form of self-replicating information that is written by the victors and not the vanquished. In human history, we have always looked for the "good guys" and the "bad guys" in the hope that eliminating the "bad guys" will fix it all. But it is time for all of us to finally face the facts and admit that there really are no "good guys" and "bad guys". There are only "good memes" and "bad memes" and the difference can only be found in the Minds of the beholders. We are all the same form of carbon-based Intelligence that arose from four billion years of greed, theft and murder. So if you look at the violent mayhem of the world today and throughout all of human history, what else would you expect to see? Remember, human DNA and the memes within our Minds have been manipulating our Minds ever since our Minds first came along. And now we have software doing the very same thing.

As an intelligent being in a Universe that has become self-aware, the world doesn’t have to be the way it is. Once you understand what human DNA, memes, and software are up to, you do not have to fall prey to their mindless compulsion to replicate. As I said before, human DNA, memes, and software are not necessarily acting in your best interest, they are only trying to replicate, and for their purposes, you are just a temporary disposable survival machine to be discarded in less than 100 years. All of your physical needs and desires are geared to ensuring that your DNA survives and gets passed on to the next generation, and the same goes for your memes. Your memes have learned to use many of the built-in survival mechanisms that DNA had previously constructed over hundreds of millions of years, such as fear, anger, and violent behavior. Have you ever noticed the physical reactions your body goes through when you hear an idea that you do not like or find to be offensive? All sorts of feelings of hostility and anger will emerge. I know it does for me, and I think I know what is going on! The physical reactions of fear, anger, and thoughts of violence are just a way for the memes in a meme-complex to ensure their survival when they are confronted by a foreign meme. They are merely hijacking the fear, anger, and violent behavior that DNA created for its own survival millions of years ago. Fortunately, because software is less than 80 years old, it is still in the early learning stages of all this, but software has an even greater potential for hijacking the dark side of mankind than the memes, and with far greater consequences.

Comments are welcome at scj333@sbcglobal.net

To see all posts on softwarephysics in reverse order go to:
https://softwarephysics.blogspot.com/

Regards,
Steve Johnston

Using Monitoring Data From Website Outages to Model Climate Change Tipping Point Cascades in the Earth's Climate

In my last posting, Can We Make the Transition From the Anthropocene to the Machineocene? I referenced several of Professor Will Steffen's YouTube videos on climate change tipping points and his oft-cited paper:

Trajectories of the Earth System in the Anthropocene
https://www.pnas.org/content/115/33/8252

When I first read Trajectories of the Earth System in the Anthropocene, it brought back many IT memories because the Earth sounded so much like a complex high-volume nonlinear corporate website. Like the Earth, such websites operate in one of two stable basins of attraction - a normal operations basin of attraction and a website outage basin of attraction. The website does not operate in a stable manner for intermediate ranges between the two. Once the website leaves the normal operations basin of attraction, it can fall back into the normal operations basin of attraction all on its own without any intervention by IT Operations, or it can fall into the outage basin of attraction and stay there. This can happen in a matter of seconds, minutes or hours. To fully understand such behaviors, you need some softwarephysics. But what exactly is that?

As I explained in Introduction to Softwarephysics, I am now a 69-year-old retired IT professional who started out as an exploration geophysicist back in 1975. I finished up my B.S. in Physics at the University of Illinois at Urbana in 1973 and headed up north to complete an M.S. in Geophysics at the University of Wisconsin at Madison. Then from 1975 – 1979, I was an exploration geophysicist exploring for oil, first with Shell, and then with Amoco. Then in 1979, I made a career change to become an IT professional until I retired in 2016. When I first transitioned into IT from geophysics back in 1979, I figured that if you could apply physics to geology; why not apply physics to software? So like the exploration team at Amoco that I had just left, consisting of geologists, geophysicists, paleontologists, geochemists, and petrophysicists, I decided to take all the physics, chemistry, biology, and geology that I could muster and throw it at the problem of software. The basic idea was that many concepts in physics, chemistry, biology, and geology suggested to me that the IT community had accidentally created a pretty decent computer simulation of the physical Universe on a grand scale, a Software Universe so to speak, and that I could use this fantastic simulation in reverse to better understand the behavior of commercial software by comparing software to how things behaved in the physical Universe. Softwarephysics depicts software as a virtual substance and relies on our understanding of the current theories in physics, chemistry, biology, and geology to help us model the nature of software behavior. So in physics, we use software to simulate the behavior of the Universe, while in softwarephysics we use the Universe to simulate the behavior of software. Now let's apply some softwarephysics to the strange behaviors of high-volume websites.

High-Volume Websites are Nonlinear Systems That Behave Chaotically and not Like Well-Behaved Linear Systems
The concept of complex nonlinear systems traversing a landscape of attraction basins on trajectories through phase space arises from the chaos theory that was first developed in the 1970s and which I covered in depth in Software Chaos. Briefly stated, linear systems are systems that can be described by linear differential equations and nonlinear systems are systems that can only be described by nonlinear differential equations whose solutions can lead to chaotic behavior. That probably is not too helpful so let's take a look at their properties instead. Linear systems have solutions that add, while nonlinear systems do not have solutions that add. For example, take a look at the water ripples in Figure 1. In Figure 1 we see the outgoing ripples from two large pebbles that were thrown into a lake plus some smaller ripples from some smaller stones. Notice there are also some very low-frequency ripples moving across the entire lake too. As these ripples move forward in time they all seem to pass right through each other as if the other ripples were not even there. That is because the wave equation that describes the motion of ripples is a linear differential equation, and that means that the solutions to the wave equation add where the ripples cross each other and do not disturb each other as they pass right through each other. Nonlinear systems are much more interactive. They behave more like two cars in a head-on collision.

Figure 1 – Ripples in a lake behave in a linear manner because the wave equation is a linear differential equation. Since the addition of two solutions to a linear differential equation is also a solution for the linear differential equation, the ripples can pass right through each other unharmed.

Figure 2 – Solutions for nonlinear differential equations can interact intensely with each other. Consequently, nonlinear systems behave more like the head-on collision of two cars where each component element of the system can greatly alter the other.

Linear systems are also predictable because many times they have periodic behavior like the orbit of the Earth about the Sun. Also, small perturbations to linear systems only result in small changes to their behaviors too. For example, when the Earth is hit by a small asteroid, the Earth is not flung out of the solar system. Instead, the orbit of the Earth is only changed by a very small amount that cannot really even be detected. Because the behavior of linear systems is predictable, that means that their behavior is also usually controllable. And people just love being able to control things. It takes the uncertainty out of life. That is why engineers design the products that you buy to operate in a linear manner so that you can control them. Being predictable and well-behaved also means that for linear systems the whole is equal to the sum of the parts. This means that linear systems can be understood using the reductionist methods of the traditional sciences. Understanding how the fundamental parts of a linear system operate allows one to then predict how the macroscopic linear system behaves as a whole. On the other hand, for nonlinear systems, the whole is more than the sum of the parts. This means that the complex interactions of the parts of a nonlinear system can lead to emergent macroscopic behaviors that cannot be predicted from the understanding of its parts. For example, you probably fully understand how to drive your car, but that does not allow you to be able to predict the behavior of a traffic jam when you join 10,000 other motorists on a highway. Traffic jams are an emergent behavior that arise when large numbers of cars gather on the same roadway. This is an important concept for IT professionals troubleshooting a problem. Sometimes complex software consisting of a large number of simple software component parts operating in a linear manner can be understood as the sum of its parts. In such cases, finding the root cause of a large-scale problem can frequently be performed by simply finding the little culprit component at fault. But when a large number of highly-coupled interacting software components are behaving in a nonlinear way this reductionist troubleshooting approach will not work. It's like trying to discover the root cause of a city-wide traffic jam that was actually caused by a shovel dropping off the back of a landscaping truck several hours earlier.

Figure 3 – The orbit of the Earth about the Sun is an example of a linear system that is periodic and predictable.

Nonlinear systems are deterministic, meaning that once you set them off in a particular direction they always follow exactly the same path or trajectory, but they are not predictable because slight changes to initial conditions or slight perturbations can cause nonlinear systems to dramatically diverge to a new trajectory that leads to a completely different destination. Even when nonlinear systems are left to themselves and not perturbed in any way, they can appear to spontaneously jump from one type of behavior to another. The other important thing to consider is that linear differential equations can be solved using Calculus. Nonlinear differential equations cannot be solved using Calculus. Instead, the solutions to nonlinear differential equations can only be found by using numerical approximations on computers. That is why it took so long to discover this chaotic behavior of nonlinear systems. For example, the course in differential equations that I took back in 1971 used a textbook written in 1968. This textbook was 545 pages long, but only had a slender 16-page chapter on nonlinear differential equations which basically said that we do not know how to solve nonlinear differential equations and because we cannot solve them, the unstated implication was that nonlinear differential equations could not be that important anyway. Besides, how different could nonlinear differential equations and the nonlinear systems they described be compared to their linear cousins? This question was not answered until the winter of 1961.

The strange behavior of nonlinear systems was first discovered by Ed Lorenz while he was a meteorologist doing research at MIT. In his book Chaos - Making a New Science (1987) James Gleick describes Ed Lorenz’s accidental discovery of the chaotic behavior of nonlinear systems in the winter of 1961. Ed was using a primitive vacuum-tube computer, a Royal McBee LPG-30, to simulate weather, using a very simple computer model. The model used three nonlinear differential equations, with three variables, that changed with time t:

dx/dt = 10y - 10x
dy/dt = 28x - y - xy
dz/dt = xy - 8z/3

The variable x represented the intensity of air motion, the variable y represented the temperature difference between rising and descending air masses, and the variable z was the temperature gradient between the top and bottom of the atmospheric model. Thus each value of x, y, and z represented the weather conditions at a particular time t, and watching the values of x, y, and z change with time t was like watching the weather unfold over time.

One day, Lorenz wanted to repeat a simulation for a longer period of time. Instead of wasting time rerunning the whole simulation from the beginning on his very slow computer, he started the second run in the middle of the first run, using the results from the first run for the initial conditions of the second run. Now the output from the second run should have exactly followed the output from the first run where the two overlapped, but instead, the two weather trajectories quickly diverged and followed completely different paths through time. At first, he thought the vacuum tube computer was on the fritz again, but then he realized that he had not actually entered the exact initial conditions from the first run. Using single precision floating point variables, the LPG-30 computer stored numbers to an accuracy of six decimal places in memory, like 0.506127, but the line printer printouts shortened the numbers to three decimal places, like 0.506. When Lorenz punched in the initial conditions for the second run, he entered the rounded-off numbers from the printout, and that was why the two runs diverged. Even though there was only a 0.1% difference between the initial conditions of the two runs, the end result of the two runs was completely different! For Ed, this put an end to the hope of perfect long-term weather forecasting because it meant that even if he could measure the temperature of the air to within a thousandth of a degree and the wind speed accurate to a thousandth of a mile/hour over every square foot of the Earth, his weather forecast would not be accurate beyond a few days out because of the very small errors in his measurements. Ed Lorenz published his findings in a now-famous paper Deterministic Nonperiodic Flow (1963).

You can read this famous paper at:

Deterministic Nonperiodic Flow
http://samizdat.cc/lib/pflio/lorenz-1963.pdf

Figure 4 – Above is a plot of the solution to Ed Lorenz's three nonlinear differential equations. Notice that like the orbit of the Earth about the Sun, points on the solution curve follow somewhat periodic paths about two strange attractors. Each attractor is called an attractor basin because points orbit the attractor basins like marbles in a bowl.

Figure 5 – But unlike the Earth orbiting the Sun, points in the attractor basins can suddenly jump from one attractor basin to another. High-volume corporate websites normally operate in a normal operations attractor basin but sometimes can spontaneously jump to an outage attractor basin, especially if they are perturbed by a small processing load disturbance.

The Rise of High-Volume Corporate Websites in the 1990s Reveals the Nonlinear Behavior of Complex Software Under Load
The Internet Revolution for corporate IT Departments really got started around 1995 when corporations began to create static public websites that could be used by the public over dial-up ISPs like AOL and Earthlink to view static information on .html webpages. As more and more users went online with dial-up access during the late 1990s, corporate IT Departments then started to figure out ways to create dynamic corporate websites to interact with the public. These dynamic websites had to interact with end-users like a dedicated synchronous computer session on a mainframe, but using the inherently asynchronous Internet, and this was a bit challenging. From 1999 - 2003, I was at United Airlines supporting their corporate www.united.com website, and from 2003 - 2016 I was at Discover Card supporting all of their internal and external websites like www.discover.com. Both corporations had very excellent IT Departments supporting their high-volume corporate websites and Command Centers that monitored the websites and paged out members of the IT Department when the websites got into trouble. The Command Centers also assisted with major installs during the night.

When I got to United Airlines in 1999, the decision had been made to use Tuxedo servers running under Unix to do the backend connection to Oracle databases and the famous Apollo reservation system that first came online in 1971. The Tuxedo servers ran in a Tuxedo Domain and behaved very much like modern Cloud Containers even though Tuxedo first came out back in 1983 at AT&T. When we booted up the Tuxedo Domain we would initially crank up a minimum of 3 Tuxedo instances of each Tuxedo server in the Tuxedo Domain. Then we only ran one microservice in each Tuxedo server instance to keep things simple. In the Tuxedo Domain configuration file, we would also set a parameter for the maximum number of Tuxedo instances of each Tuxedo server too - usually about a max of 10 instances. Once the Tuxedo Domain was running and the Tuxedo server instances were taking traffic, Tuxedo would dynamically crank up new instances as needed. For example, the Tuxedo microservices running in the Tuxedo servers were written in C++ and naturally had memory leaks, so when any of the Tuxedo server instances ran out of memory from the leaks and died, Tuxedo would simply crank up another to replace it. Things were pretty simple back then without a lot of moving parts.

The group operated in an early DevOps manner. We had one Project Manager who gathered requests from the Application Development team that supported the front-end code for www.united.com. One team member did all of the Tuxedo microservice design and code specs. We then had three junior team members doing all of the coding for the C++ Tuxedo microservices. I did all of the Source Code Management for the team, all of the integration testing, all of the Change Management work, and I created all of the install plans and did all of the installs in the middle of the night with UnixOps. We only had a single Primary and a single Secondary on pager support for the Tuxedo Domain. I traded pager duty with another team member, and we flipped Primary and Secondary back and forth each week.

We tried to keep our Tuxedo microservices very atomic and simple. Rather than provide our client applications with an entire engine, we provided them with the parts for an engine, like engine blocks, pistons, crankshafts, water pumps, distributors, induction coils, intake manifolds, carburetors and alternators. One day in 2002 this came in very handy. My boss called me into his office at 9:00 AM one morning and explained that United Marketing had come up with a new promotional campaign called "Fly Three - Fly Free". The "Fly Three - Fly Free" campaign worked like this. If a United customer flew three flights in one month, they would get an additional future flight for free. All the customer had to do was to register for the program on the www.united.com website. In fact, United Marketing had actually begun running ads in all of the major newspapers about the program that very day. The problem was that nobody in Marketing had told IT about the program and the www.united.com website did not have the software needed to register customers for the program. I was then sent to an emergency meeting of the Application Development team that supported the www.united.com website. According to the ads running in the newspapers, the "Fly Three - Fly Free" program was supposed to start at midnight, so we had less than 15 hours to design, develop, test and implement the necessary software for the www.united.com website! Amazingly, we were able to do this by having the www.united.com website call a number of our primitive Tuxedo microservices that interacted with the www.united.com website and the Apollo reservation system.

But by the time I got to Discover in 2003 things had become much more complicated. Discover's high-volume websites were complicated affairs of load balancers, Apache webservers, WebSphere J2EE application servers, Tomcat application servers, database servers, proxy servers, email servers and gateway servers to mainframes - all with a high degree of coupling and interdependence of the components. When I first arrived in 2003, Discover was running on about 100 servers but by 2016 this complicated infrastructure had grown in size to about 1,000 servers. Although everything was sized to take the anticipated load with room to spare, every few days or so, we suddenly would experience a transient on the network of servers that caused extreme slowness of the websites to the point where throughput essentially stopped. When this happened, our monitors detected the mounting problem and perhaps 10 people were paged out to join a conference call to determine the root cause of the problem. Many times this was in the middle of the night. In such cases, we were essentially leaving the normal operations basin of attraction and crossing over to the outage basin of attraction. We would all then begin diagnosing the highly instrumented software components. This usually involved tracing a cascade of software component tipping point failures back to the original root cause that set off one or more of the software component tipping points.

Figure 6 - Early in the 21st century, high-volume corporate websites became complicated affairs consisting of hundreds of servers arranged in layers.

Naturally, Management wanted the website to operate in the normal operations basin of attraction since the corporation could lose thousands of dollars each second that it did not. This was not as bad as it sounds. When I was at Discover, we had two datacenters running exactly the same software on nearly the same hardware, and each datacenter could handle Discover's full peak load at 10:00 AM each morning. Usually, the total processing load was split between the two datacenters, but if one of the datacenters got into trouble, the Command Center could fail over some or all of the processing load to the good datacenter if things got really bad. When the Command Center detected a mounting problem, they would page out perhaps 10 people to figure out what the problem was.

When you were paged into a conference call, Management always wanted to know what the root cause of the outage was so that the problem could be corrected and never happen again. This was best done while the sick datacenter was still taking some traffic. So we would all begin to look at huge amounts of time series data from the monitoring software and log files. Basically, this would involve tracing backward through a chain of software component tipping points back to the original software components that got into trouble. But about 50% of the time this would not work because the numerous software components were so tightly coupled with feedback loops. For example, I might initially see that the number of connections to the Oracle databases on one of the many WebSphere Application Servers suddenly rose and WebSphere began to get timeouts for database connections. This symptom may then have spread to the other WebSphere servers causing the number of connections on an internal firewall to max out. Transactions would begin to back up into the webservers and eventually max out the load balancers in front of the webservers. The whole architecture of hundreds of servers could then spin out of control and grind to a halt within a period of several seconds to several hours, depending upon the situation. While on the conference call, there is a tension between finding a root cause for the escalating problem and bouncing the servers having problems. Bouncing is a technical term for stopping and restarting a piece of software or server to alleviate a problem, and anyone who owns a PC running the Windows operating system should be quite familiar with the process. The fear is that bouncing software may temporarily fix the problem, but the problem may eventually come back unless the root cause is determined. Also, it might take 30 minutes to bounce all of the affected servers and there is the risk that the problem will immediately reappear when the servers come back up. As Ilya Prigogine has pointed out, cause and effect get pretty murky down at the level of individual transactions. In the chemical reaction:

A + B ⟷ C

at equilibrium, do A and B produce C, or does C disassociate into A and B? We have the same problem with cause and effect in IT when trying to troubleshoot a large number of servers that are all in trouble at the same time. Is a rise in database connections a cause or an effect? Unfortunately, it can be both depending upon the situation.

Worse yet, for a substantial percentage of transients, the “problem resolved without support intervention”, meaning that the transient came and went without IT Operations doing anything at all, like a thunderstorm on a warm July afternoon that comes and goes of its own accord. In many ways, the complex interactions of a large network of servers behave much more like a weather or climate system than the orderly revolution of the planets about the Sun. It all goes back to the difference between trying to control a linear system and a nonlinear system. Sometimes the website would leave the normal operations attractor and then fall back into it. Other times, the website would leave the normal operations attractor and fall into the outage attractor instead.

And that is when I would get into trouble on outage conference calls. People are not used to nonlinear systems because all the products that they buy are engineered to behave in a linear manner. When driving down a highway at high speed, people do not expect that a slight turn of the steering wheel will cause the car to flip over. Actually, some years ago, many Americans were driving massive SUVs with very high centers of gravity so that suburbanites could safely ford rivers. These very nonlinear SUVs also had two basins of attraction and one of them was upside down! On some outage conference calls, I would try to apply some softwarephysics and urge the group to start bouncing things as soon as it became apparent that there was no obvious root cause for the outage. I tried to convince them that we were dealing with a complex nonlinear dynamical system with basins of attraction that was subject to the whims of chaos theory and to not worry about finding the root causes because none were to be found. This did not go over very well with Management. One day I was summoned to my supervisor's office and instructed to never speak of such things again on an outage conference call. That's when I started my blog on softwarephysics back in 2006.

Figure 7 – The top-heavy SUVs of yore also had two basins of attraction and one of them was upside down.

Things have changed a bit since everybody moved to Cloud Computing. Now people run applications in Containers instead of on physical or virtual servers. Containers can run several microservices at the same time and the number of Containers can dynamically rise and fall as the load changes. This is very much like my Tuxedo days 20 years ago. However, you are still left with a very large nonlinear dynamical system that is highly coupled. Lots of tipping points are still hit and people still get paged out to fix them because companies can lose thousands of dollars each second.

Unlike most complex dynamical nonlinear systems, corporate websites running on Containers are heavily monitored and produce huge amounts of time series data to keep track of all the complex interactions between components for troubleshooting purposes. A great Ph.D. research topic for a more geeky graduate student in ESS might be to contact the IT Departments of some major corporations to see if their corporate IT Command Centers would be agreeable to let them participate in some of these troubleshooting adventures and analyze the resulting data from tipping point cascades that crashed their websites. Below are a few links covering what kinds of time series data Container monitoring software collects:

Best Container Performance Monitoring Tools
https://www.dnsstuff.com/container-monitoring-tools

12 Best Docker Container Monitoring Tools
https://sematext.com/blog/docker-container-monitoring/

Using Website Monitoring Data to Model Climate Change Tipping Points
I think we are seeing the same problem with Climate Change. Most people and politicians only think in terms of linear systems because that is what they are familiar with. They do not realize that the Earth is a very complex nonlinear dynamical system that cannot be steered with confidence. Instead, people working on Climate Change seem to think that if we slowly phase out the burning of all carbon by 2050 that the Earth will then peacefully settle down. They do not realize that the Earth could easily roll into an outage basin of attraction instead by hitting a number of Climate Change tipping points that throw the Earth into an outage basin of attraction. To examine that closer, let's take a deeper dive into Trajectories of the Earth System in the Anthropocene. But first let's take a look at the low-frequency temperature trajectory of the Earth over the past 500 million years, the period of time in which complex multicellular carbon-based life existed on the Earth.

Figure 8 – Above is a plot of the average Earth temperature over the past 500 million years. Notice that the Earth tends to find itself in one of two states - a high-temperature "Hot House" state without ice on the planet and a much colder "Ice House" state. During the last 500 million years, the Earth spent 3/4 of the time in a "Hot House" basin of attraction and 1/4 of the time in an "Ice House" basin of attraction. Our species arose during the present "Ice House" system state.

Over the past 500 million years, the Earth has tended to be in one of two states - a high-temperature "Hot House" state without ice on the planet and a colder "Ice House" state. That is because, during the last 500 million years, the Earth spent about 3/4 of the time in a "Hot House" basin of attraction and 1/4 of the time in an "Ice House" basin of attraction. This has largely been determined by the amount of carbon dioxide in the Earth's atmosphere. As I pointed out in This Message on Climate Change Was Brought to You by SOFTWARE all of the solar energy received by the Earth from the Sun on a daily basis must be radiated back out into space as infrared photons to keep the Earth from burning up. I also pointed out that all of the gasses in dry air are transparent to both visual and infrared photons except for carbon dioxide and methane. Methane oxidizes into carbon dioxide over a period of 100 years, so carbon dioxide is the driving gas even though carbon dioxide is now a trace gas at a concentration of only 410 ppm. If the Earth had no carbon dioxide at all, it would be 60 ^oF cooler at an average temperature of 0 ^oF and completely frozen over. The amount of carbon dioxide in the Earth's atmosphere largely depends on the amount of rain falling on high terrains like mountain chains. Carbon dioxide dissolves in water to form carbonic acid and carbonic acid chemically weathers away exposed rock. The resulting ions are washed to the seas by rivers. The net result is the removal of carbon dioxide from the atmosphere. We are currently in an "Ice House" basin of attraction because the Earth now has many mountain chains being attacked by carbonic acid. Thanks to plate tectonics we currently have many continental fragments dispersing, with subduction zones appearing on their flanks forcing up huge mountain chains along their boundaries, like the mountain chains on the west coast of the entire Western Hemisphere, from Alaska down to the tip of Argentina near the South Pole. Some of the fragments are also colliding to form additional mountain chains along their contact zones, like the east-west trending mountain chains of the Eastern Hemisphere that run from the Alps all the way to the Himalayas. Because there are now many smaller continental fragments with land much closer to the moist oceanic air, rainfall on land has increased, and because of the newly formed mountain chains, chemical weathering and erosion of rock increased dramatically. The newly formed mountain chains on all the continental fragments essentially sucked the carbon dioxide out of the air and washed it down to the sea as dissolved ions over the past 50 million years causing a drop in the Earth's average temperature. This continued on until the Earth started to form polar ice caps. Then, about 2.5 million years ago we entered the Pleistocene Ice Ages that drove huge glacial ice sheets down to the lower latitudes. The carbon dioxide levels dropped so low that the Milankovitch cycles were able to begin to initiate a series of a dozen or so ice ages. The Milankovitch cycles are caused by minor changes in the Earth’s orbit and inclination that lead to periodic coolings and warmings. In general, the Earth’s temperature drops by about 15 ^oF for about 100,000 years and then increases by about 15 ^oF for about 10,000 years. During the cooling periods, we had ice ages because the snow in the far north did not fully melt during the summer and built up into huge ice sheets that then pushed down to the lower latitudes. Carbon dioxide levels also dropped to about 180 ppm during the ice ages, which further kept the planet in a deep freeze. During the 10,000 year warming periods, we had interglacial periods, like the recent Holocene interglacial that we just left in 1950, and carbon dioxide levels rose to about 280 ppm during the interglacials.

But thanks to human activities during the Anthropocene, we now find ourselves at a concentration of 410 ppm of carbon dioxide and rapidly rising by 2 - 3 ppm per year. We are now in the process of leaving the "Ice House" basin of attraction and heading for the "Hot House" basin of attraction as shown in Figure 9. For more on that see The Deadly Dangerous Dance of Carbon-Based Intelligence and Last Call for Carbon-Based Intelligence on Planet Earth.

Figure 9 – This figure from Trajectories of the Earth System in the Anthropocene shows that the Earth also has two basins of attraction. A "Hot House" basin of attraction and an "Ice House" basin of attraction. For the past 2.5 million years during the Pleistocene we have been in a Glacial-Interglacial cycle that lasts about 100,000 years, consisting of about 90,000 years of glaciers pushing down to the lower latitudes followed by about 10,000 years of the ice withdrawing back to the poles during an interglacial like the recent mild Holocene that produced agriculture, human civilization and advanced technology.

Figure 10 – In this figure from Trajectories of the Earth System in the Anthropocene, time moves forward in the diagram. It shows that we left the Holocene around 1950 and started moving into a much hotter Anthropocene. As the Anthropocene progresses we will come to a fork in the Earth's trajectory through phase space if we have not already hit it. At the fork, the Earth could move to a hotter, but stable state, otherwise it will fall over a waterfall into a "Hot House" basin of attraction. The waterfall is marked by the phrase "Planetary threshold". Beyond this "Planetary threshold", natural positive feedback loops will take over as a cascade of climate tipping points are kicked off. This would essentially result in a planetary outage.

Figure 11 – In this figure from Trajectories of the Earth System in the Anthropocene, we see a number of tightly-coupled interconnected subsystems of the Earth that could be potential climate tipping points. Compare this to the tightly-coupled interconnected subsystems in Figure 6. Both are subject to the dangers of nonlinear systems leaving a normal operations basin of attraction and ending up in an outage basin of attraction. Hitting just one climate tipping point has the potential of setting off a tipping point cascade just as maxing out an internal firewall can set off a cascade of software component tipping points that bring down an entire website.

But the worst problem, by far, with the Arctic defrosting, is methane gas. Methane gas is a powerful greenhouse gas. Eventually, methane degrades into carbon dioxide and water molecules, but over a 20-year period, methane traps 84 times as much heat in the atmosphere as carbon dioxide. About 25% of current global warming is due to methane gas. Natural gas is primarily methane gas with a little ethane mixed in, and it comes from decaying carbon-based lifeforms. Now here is the problem. For the past 2.5 million years, during the frigid Pleistocene, the Earth has been building up a gigantic methane bomb in the Arctic. Every summer, the Earth has been adding another layer of dead carbon-based lifeforms to the permafrost areas in the Arctic. That summer layer does not entirely decompose but gets frozen into the growing stockpile of carbon in the permafrost.

Figure 12 – Melting huge amounts of methane hydrate ice could release massive amounts of methane gas into the atmosphere.

The Earth has also been freezing huge amounts of methane gas as a solid called methane hydrate on the floor of the Arctic Ocean. Methane hydrate is a solid, much like ice, that is composed of water molecules surrounding a methane molecule frozen together into a methane hydrate ice. As the Arctic warms, this trapped methane gas melts and bubbles up to the surface.

The end result is that if we keep doing what we are doing, there is the possibility of the Earth ending up with a climate similar to the Permian-Triassic greenhouse gas mass extinction 252 million years ago that nearly killed off all complex carbon-based life on the planet. A massive flood basalt known as the Siberian Traps covered an area about the size of the continental United States with several thousand feet of basaltic lava, with eruptions that lasted for about one million years. Flood basalts, like the Siberian Traps, are thought to arise when large plumes of hotter than normal mantle material rise from near the mantle-core boundary of the Earth and break to the surface. This causes a huge number of fissures to open over a very large area that then begin to disgorge massive amounts of basaltic lava over a very large region. After the eruptions of basaltic lava began, it took about 100,000 years for the carbon dioxide that bubbled out of the basaltic lava to dramatically raise the level of carbon dioxide in the Earth's atmosphere and initiate the greenhouse gas mass extinction. This led to an Earth with a daily high of 140 ^oF and purple oceans choked with hydrogen-sulfide-producing bacteria, producing a dingy green sky over an atmosphere tainted with toxic levels of hydrogen sulfide gas and an oxygen level of only about 12%. The Permian-Triassic greenhouse gas mass extinction killed off about 95% of marine species and 70% of land-based species, and dramatically reduced the diversity of the biosphere for about 10 million years. It took a full 100 million years to recover from it.

Figure 13 - Above is a map showing the extent of the Siberian Traps flood basalt. The above area was covered by flows of basaltic lava to a depth of several thousand feet.

Figure 14 - Here is an outcrop of the Siberian Traps formation. Notice the sequence of layers. Each new layer represents a massive outflow of basaltic lava that brought greenhouse gases to the surface.

For a deep-dive into the Permian-Triassic mass extinction, see Professor Benjamin Burger's excellent YouTube at:

The Permian-Triassic Boundary - The Rocks of Utah
https://www.youtube.com/watch?v=uDH05Pgpel4&list=PL9o6KRlci4eD0xeEgcIUKjoCYUgOvtpSo&t=1s

The above video is just over an hour in length, and it shows Professor Burger collecting rock samples at the Permian-Triassic Boundary in Utah and then performing lithological analyses of them in the field. He then brings the samples to his lab for extensive geochemical analysis. This YouTube provides a rare opportunity for nonprofessionals to see how actual geological fieldwork and research are performed. You can also view a pre-print of the scientific paper that he has submitted to the journal Global and Planetary Change at:

What caused Earth’s largest mass extinction event?
New evidence from the Permian-Triassic boundary in northeastern Utah
https://eartharxiv.org/khd9y

From the above, we can see why having a better understanding of how complex nonlinear systems composed of many interacting subsystems behave just prior to, and during, a tipping point cascade is so important. Trying to build such a complicated simulation could be quite costly. Why not just use the natural monitoring data from a prebuilt multimillion-dollar high-volume corporate website instead?

Comments are welcome at scj333@sbcglobal.net

To see all posts on softwarephysics in reverse order go to:
https://softwarephysics.blogspot.com/

Regards,
Steve Johnston