Thursday, April 7, 2016
Morality of physics & machines
In a godless world where we have no justification for selfishness for ourselves or our species (other than "it feels good" or "because we want to") I have to wonder if physics has something to say on the subject of "what is right". Of course, being godless, it can't be a moral "right", but rather the question is "in what direction is physical law heading". To my shock, "entropy always increases" is known to be a patently wrong statement of the 2nd law. It applies to only isolated systems and this does not exist in the universe. The universe has constant entropy on a comoving expanding volume basis, and entropy is conserved (See Weinberg's "First 3 Minutes"). Since entropy is conserved and constant on a comoving basis, it has to be decreasing on a fixed-volume basis like solar systems and galaxies. It seems Earth must emit more entropy than it takes in because of these two laws. Entropy on Earth seems to be decreasing "so that the universe can expand". I could not calculate an actual decrease from observable data because the structures we use in economics are releasing entropy as gases even as the structures are measurably and greatly a decrease in entropy. Economics is removing O2 from C, Si, metals, etc. The resulting structures are always intensely useful to economics, which is an explosive evolution. These stronger bonds mean more restricted states in the atoms' positions which is lower entropy. This means they are easier to control, easier to use for exerting control, stronger bonds, and better at turning light into energy. Being controlled and exerting control means motors and CPUs. The process is taking a recursive path which we call evolution. So, whatever morals people have, be they humanistic godless atheists or Muslims, in one way or another they are fighting out the battle to find the best way to lower entropy on Earth. Muslims seem incredibly bad at it because they hate the machines and want babies.Of course godless atheists have no desire to pollute the planet with more children and hatred, so they concentrate on creating the machines and teaching them how to work more cooperatively (protocols) and survivably (peer-to-peer). People aren't not directing the money wisely (for the lowering of entropy), so there's bitcoin. Laws, banks, and government are defunct, so there's Ethereum. If love means peace, working together, and no more pain, machines are worthy successors in this lowering of entropy.
Tuesday, April 5, 2016
Space ship travel at 1 g acceleration
Concerning the "traveler's speed" in this, there are some who argue there is a problem with "exceeding the speed of light" by a factor of 1,400 times (for example, as the chart shows) when travelling to the center of the galaxy like this. They will say "nothing can go faster than the speed of light", but this is a problematic statement because all observers from all frames of reference observe all photons as always going a speed of c, no matter how fast the observers are moving. What they mean is that no observer can observe any traveler going faster than c. All observers go zero meters/second relative to all photons. So, the chart shows the traveler's speed as the distance he covered as measured by him before and after taking the trip divided by the time it took him according to his clock, the same as everyone does when they are driving a car.
Friday, April 1, 2016
relation between physical and information entropy
The conversion factor from physical entropy to information entropy (in random bits) uses Landauer's limit: (physical entropy)=(information bits)*kb*ln(2). The number of yes/no questions that have to be asked to determine which state a physical system is in is equal to Shannon's entropy in bits, but not Shannon's intensive, specific entropy H, but his extensive, total entropy of a data-generating source: S=N*H where H=1 if the n bits are mutually independent.
Landauer's limit states that 1 bit of information irreversibly changing state releases entropy kb*ln(2), which is a heat energy reelase for a given T: Q=T*kb*S, implying there was a stored potential energy that was the bit. This shows that entropy is information entropy: the ln(2) converts from ln() to log2(). kb is a simple conversion factor from average kinetic energy per particle (definition of temperature) to heat joules which has units of joules/joules, i.e. unitless. If our T was defined in terms of joules of kinetic energy (average 1/2 mv^2 of the particles) instead of Kelvins, then kb=1. So kb is unitless joules/joules. It's not a fundamental constant like h. c also does not have fundamental units if you accept time=i*distance as Einstein mentioned in appendix 2 of his book, allowing use of the simpler Euclidean space instead of Minkoswki space without error or qualification and in keeping with Occam's razor.
Shannon's "entropy" (specific, intensive) is H=sum(-p*log(p)) and he stated 13 times in his paper that H has units of bits, entropy, or information PER SYMBOL, not bits (total entropy) as most people assume. An information source generates entropy S=N*H where N is the number of symbols emitted. H is a "specific entropy" based on the probability of "n" unique symbols out of N total symbols. H is not a "total entropy" as is usually believed, finding its physical parallel with So=entropy/mole. Physical S=N*So and information S=N*H. It is rare to find texts that explain this.
An ideal monoatomic gas (Sackur-Tetrode equation) has an entropy from N mutually independent gas particles of S=kb*sum(ln(total states/i^(5/2)) where the sum is over i=1 to N. This is approximated by Stirling's formula to be S=kb*N*[ln(states/particle)+5/2]. I can't derive that from Shannon's total entropy S=N*H even though I showed in the first paragraph the final entropies are exactly the same. You can't directly correlate an informatic "symbol" (such as the particles in a gas or the phonons in a solid) in a physical system to the symbols in Shannon entropy because physical entropy is constrained by total energy that can be distributed among fewer than the N available particles or phonons. Once you've characterized a source of symbols in Shannon entropy, you know the number of symbols and that is what you use to calculate the entropy. But the energy in a physical system can be distributed among N or fewer particles which results in a N! divisor instead of an N^N divisor in Shannon's N*H = N*log[(states in N symbols)/(N)] plus using a log rule. This gives physical entropy more possible ways to use the N particles than information can use N symbols. 1 particle carrying the total energy is a possible macrostate (not counting the minimal QM state for the others), but information entropy does not have a "constrained only by the sum" of an external variable like this to use fewer symbols. Physical entropy seems to always be S=kb*N*[ln(states/particle)+c] and the difference from information entropy is the c. But the c is generally not a huge factor and might become insignificant in bulk matter where the energy is spread equally between bulks, then physical entropy is then S=N*So. Information entropy is perfectly like this (S=N*H), but you can't derive So from H, but it's always true that Sbits=S/(kb*ln(2)) (i.e., the exact state a system is in can be specified by answering Sbits of yes/no questions.
To show the exact equivalence between physical and informational entropy, I have to precisely define and constrain an informational situation to match physical entropy. It goes like this: the message to be sent will consist of 1 to N symbols. The number of states each symbol can have (the size of the "alphabet") is n to n/N as you go from 1 to N message length. In this concept I would like to correlate n with total energy, but disastrously to my desire for simplicity this is not so. The number of states in each N as you go from 1 to N depends on a combination of the size of the box and the total translational energy. To add more trouble, momentum is a v factor and energy is v^2 which results in a 5/2 factor (otherwise it would be a ^3 factor having to do with 3 dimensions).
The simplest way to view the exact correlation is to view a gas in a box as a sequence of messages of length 1 to N based on the number of particles carrying the total translational energy (heat) and then calculate the number of states (the size of the alphabet) they each may posses. So the correlation is a sum of the entropies of different messages of increasing length, with a decreasing alphabet size in each message. The way the alphabet size decreases from 1 to N is an equation determined by the size of the box and the total heat. It's nice to finally understand it, but I hate this conclusion! The energy is distributed in N particle velocities, and it may use less than N, and it's energy per particle times the time to cross the box that determines how many states are possible for each of the N that are carrying the energy.
So Shannon's entropy is a lot simpler and comes out to LESS entropy if you try to make N particles in a physical system equivalent to N unique symbols. The simplest physical entropy is of independent harmonic oscillators in 1D sharing a total energy but not necessarily evenly is S=kb*ln[(states/oscillator)^N / N!] which is S=N*[log(states/particle)+1] for large N. So even in the simplest case, the c remains. Shannon entropy is of a fundamentally different form: S~log((states/symbol)^N) = N*log(states/symbol) when each symbol is mutually independent (no patterns in the data and equal symbol probabilities). For example, for random binary data S=log2(2^N) = N bits. So it is hard to see the precise connection in the simplest case, even as they are immediately shown by true/false questions to be identical quantities with a simple conversion factor. Stirling's approximation is exact in the limit of N and Shannon's H depends in a way on an infinite N to get exact p's, so the approximation is not a problem to me.
I have not contradicted anything user346 (physics stackexchange question) has said but I wanted to show why the connection is not trivial except in the case of looking at specific entropy of bulk matter. QM uses S=sum(-p*log(p)) but Shannon entropy is S=N*sum(-p*log(p)). They come out the same because calculating the p's is different. Physical's p=(certain macrostate)/(total microstates) but the numerator and denominator are not simply determined by counting. Information's p=(distinct symbol count)/(total symbols) for a given source. And yet, they both require the same number of bits (yes/no questions) to identify the exact microstate (after applying kb*ln(2) conversion).
But there's a problem (in calling black hole entropy the maximum amount of informtion bits that can be stored) which was mentioned in the comments to his answer. In an information system we require the bits to be reliable. We can never get 100% reliability because of thermal fluctuations. At this limit of 1 bit = kb*ln(2) we have a 49.9999% probability of any particular bit not being in the state we expected. The Landuaer limit is definitely a limit. The energy required to break a bond that is holding one of these bits in a potential memory system is "just below" (actually equal) to the average kinetic energy of the thermal agitations. Landauer's limit assumes the energy required to break our memory-bond is E=T*kb*ln(2) which is slightly weaker than a van der waals bond which is about the weakest thing you can call a "bond" in the presence of thermal agitations.
So we have to decide what level of reliability we want our bits. Using the black hole limit also seems to add a problem of "accessibility". It is the information content of the system, but it is not an information storage system.
Landauer's limit states that 1 bit of information irreversibly changing state releases entropy kb*ln(2), which is a heat energy reelase for a given T: Q=T*kb*S, implying there was a stored potential energy that was the bit. This shows that entropy is information entropy: the ln(2) converts from ln() to log2(). kb is a simple conversion factor from average kinetic energy per particle (definition of temperature) to heat joules which has units of joules/joules, i.e. unitless. If our T was defined in terms of joules of kinetic energy (average 1/2 mv^2 of the particles) instead of Kelvins, then kb=1. So kb is unitless joules/joules. It's not a fundamental constant like h. c also does not have fundamental units if you accept time=i*distance as Einstein mentioned in appendix 2 of his book, allowing use of the simpler Euclidean space instead of Minkoswki space without error or qualification and in keeping with Occam's razor.
Shannon's "entropy" (specific, intensive) is H=sum(-p*log(p)) and he stated 13 times in his paper that H has units of bits, entropy, or information PER SYMBOL, not bits (total entropy) as most people assume. An information source generates entropy S=N*H where N is the number of symbols emitted. H is a "specific entropy" based on the probability of "n" unique symbols out of N total symbols. H is not a "total entropy" as is usually believed, finding its physical parallel with So=entropy/mole. Physical S=N*So and information S=N*H. It is rare to find texts that explain this.
An ideal monoatomic gas (Sackur-Tetrode equation) has an entropy from N mutually independent gas particles of S=kb*sum(ln(total states/i^(5/2)) where the sum is over i=1 to N. This is approximated by Stirling's formula to be S=kb*N*[ln(states/particle)+5/2]. I can't derive that from Shannon's total entropy S=N*H even though I showed in the first paragraph the final entropies are exactly the same. You can't directly correlate an informatic "symbol" (such as the particles in a gas or the phonons in a solid) in a physical system to the symbols in Shannon entropy because physical entropy is constrained by total energy that can be distributed among fewer than the N available particles or phonons. Once you've characterized a source of symbols in Shannon entropy, you know the number of symbols and that is what you use to calculate the entropy. But the energy in a physical system can be distributed among N or fewer particles which results in a N! divisor instead of an N^N divisor in Shannon's N*H = N*log[(states in N symbols)/(N)] plus using a log rule. This gives physical entropy more possible ways to use the N particles than information can use N symbols. 1 particle carrying the total energy is a possible macrostate (not counting the minimal QM state for the others), but information entropy does not have a "constrained only by the sum" of an external variable like this to use fewer symbols. Physical entropy seems to always be S=kb*N*[ln(states/particle)+c] and the difference from information entropy is the c. But the c is generally not a huge factor and might become insignificant in bulk matter where the energy is spread equally between bulks, then physical entropy is then S=N*So. Information entropy is perfectly like this (S=N*H), but you can't derive So from H, but it's always true that Sbits=S/(kb*ln(2)) (i.e., the exact state a system is in can be specified by answering Sbits of yes/no questions.
To show the exact equivalence between physical and informational entropy, I have to precisely define and constrain an informational situation to match physical entropy. It goes like this: the message to be sent will consist of 1 to N symbols. The number of states each symbol can have (the size of the "alphabet") is n to n/N as you go from 1 to N message length. In this concept I would like to correlate n with total energy, but disastrously to my desire for simplicity this is not so. The number of states in each N as you go from 1 to N depends on a combination of the size of the box and the total translational energy. To add more trouble, momentum is a v factor and energy is v^2 which results in a 5/2 factor (otherwise it would be a ^3 factor having to do with 3 dimensions).
The simplest way to view the exact correlation is to view a gas in a box as a sequence of messages of length 1 to N based on the number of particles carrying the total translational energy (heat) and then calculate the number of states (the size of the alphabet) they each may posses. So the correlation is a sum of the entropies of different messages of increasing length, with a decreasing alphabet size in each message. The way the alphabet size decreases from 1 to N is an equation determined by the size of the box and the total heat. It's nice to finally understand it, but I hate this conclusion! The energy is distributed in N particle velocities, and it may use less than N, and it's energy per particle times the time to cross the box that determines how many states are possible for each of the N that are carrying the energy.
So Shannon's entropy is a lot simpler and comes out to LESS entropy if you try to make N particles in a physical system equivalent to N unique symbols. The simplest physical entropy is of independent harmonic oscillators in 1D sharing a total energy but not necessarily evenly is S=kb*ln[(states/oscillator)^N / N!] which is S=N*[log(states/particle)+1] for large N. So even in the simplest case, the c remains. Shannon entropy is of a fundamentally different form: S~log((states/symbol)^N) = N*log(states/symbol) when each symbol is mutually independent (no patterns in the data and equal symbol probabilities). For example, for random binary data S=log2(2^N) = N bits. So it is hard to see the precise connection in the simplest case, even as they are immediately shown by true/false questions to be identical quantities with a simple conversion factor. Stirling's approximation is exact in the limit of N and Shannon's H depends in a way on an infinite N to get exact p's, so the approximation is not a problem to me.
I have not contradicted anything user346 (physics stackexchange question) has said but I wanted to show why the connection is not trivial except in the case of looking at specific entropy of bulk matter. QM uses S=sum(-p*log(p)) but Shannon entropy is S=N*sum(-p*log(p)). They come out the same because calculating the p's is different. Physical's p=(certain macrostate)/(total microstates) but the numerator and denominator are not simply determined by counting. Information's p=(distinct symbol count)/(total symbols) for a given source. And yet, they both require the same number of bits (yes/no questions) to identify the exact microstate (after applying kb*ln(2) conversion).
But there's a problem (in calling black hole entropy the maximum amount of informtion bits that can be stored) which was mentioned in the comments to his answer. In an information system we require the bits to be reliable. We can never get 100% reliability because of thermal fluctuations. At this limit of 1 bit = kb*ln(2) we have a 49.9999% probability of any particular bit not being in the state we expected. The Landuaer limit is definitely a limit. The energy required to break a bond that is holding one of these bits in a potential memory system is "just below" (actually equal) to the average kinetic energy of the thermal agitations. Landauer's limit assumes the energy required to break our memory-bond is E=T*kb*ln(2) which is slightly weaker than a van der waals bond which is about the weakest thing you can call a "bond" in the presence of thermal agitations.
So we have to decide what level of reliability we want our bits. Using the black hole limit also seems to add a problem of "accessibility". It is the information content of the system, but it is not an information storage system.
Tuesday, March 29, 2016
Entropy: photons, gravity field, black hole entropy, life, universe, economics (Quora answer)
It is often said by experts that the entropy of the universe is not a well defined concept, so it's hard to discuss and is speculative (see Wikipedia "heat death of universe"). But I have included uncontested references as support of most the following statements.
The basis of all standard models of the universe that begin with a big bang is that the entropy of the universe is constant per large-scale expanding volume of the universe . See Stephen Weinberg's 1973ish popular book "The First Three Minutes" where he says this entropy constant is more fundamental than the energy+mass constant of the expanding volume. Entropy is thereby said to be conserved on a "comoving" volume basis. This means the average entropy of very large fixed volumes of the universe (where you do not let the meters expand with time due to Hubble's constant) is decreasing. Entropy in "empty" space per fixed volume is decreasing. Gravitational systems where mass is concentrated (like solar systems, black holes, and galaxies) are always emitting and thereby lowering their local entropy (I think of this emitted entropy as "allowing" the universe to expand).
"Entropy always increases" only applies to isolated systems that do not let energy or mass to be exchanged with the surrounding environment. But there is no such thing as an ideally isolated system in nature (see Wikipedia on "isolated system"). "Entropy always increases" is not an exact statement of the second law (reference: search "Feynman entropy"). The exact statement is "W=Q1-Q2" where W is the maximum work that can be extracted from heat reservoirs at T1 and T2 delivering heat Q1 and Q2 which are at different temperatures. For an isolated system that includes the reservoirs, 0=Q1-Q2-W. But any fixed walls surrounding it will have a temperature that will emit radiation (heat) energy and thereby lower their entropy. An isolated system with mass inside may have a lower-than universal average entropy and may internally increase in entropy as well as release entropy. Gravity therefore must cause a decrease in local fixed-volume entropy as mass concentrates, and mass concentrating is a direct lowering of entropy. But not only is the mass coming together, but the space-time 4D volume is decreasing from a gravitational effect, further reducing entropy compared to outside meter and time sticks. The number of x*(m*v) states decreases as x decreases, increases as mass increases, and the m/s of v cancels, so gravity space-time warping does not change entropy. I am thinking of the atoms only in terms of a gaseous entropy since the solid state is more complicated, and prior to complete black hole collapse, but these assumptions should lead towards the limits in the right direction.
Why is the entropy of a black hole begin with the same quantity as the entropy of the star that collapses? (As I think is the common view.) Particles closer together is less entropy and I just showed the gravity field change does not have an effect. Imagine 2 types of particles of a monoatomic gas (no rotational energy to keep things simple), one with positive charge and the other with negative, and they begin as randomly distributed. As time goes on, let's say they attract and stick, creating a solid which has about 1/10 as much entropy. Apparently, a potential energy gradient decreasing with distance causing an attractive force is negative entropy (since entropy is conserved). -d(P.E.) = tdS. This agrees with the two equations I have for force: F=ma= -1*d(PE) and F=+TdS. The energy in a gravity field decreases as particles come together, which apparently is a direct cause to increase entropy (potential energy is converted to entropy without causing heat). This causes any view of the gravitational field affecting entropy by supposedly affecting space-time to be very problematic since charges are not doing the same.
Why is the entropy of a black hole begin with the same quantity as the entropy of the star that collapses? (As I think is the common view.) Particles closer together is less entropy and I just showed the gravity field change does not have an effect. Imagine 2 types of particles of a monoatomic gas (no rotational energy to keep things simple), one with positive charge and the other with negative, and they begin as randomly distributed. As time goes on, let's say they attract and stick, creating a solid which has about 1/10 as much entropy. Apparently, a potential energy gradient decreasing with distance causing an attractive force is negative entropy (since entropy is conserved). -d(P.E.) = tdS. This agrees with the two equations I have for force: F=ma= -1*d(PE) and F=+TdS. The energy in a gravity field decreases as particles come together, which apparently is a direct cause to increase entropy (potential energy is converted to entropy without causing heat). This causes any view of the gravitational field affecting entropy by supposedly affecting space-time to be very problematic since charges are not doing the same.
The Earth's surface is an open system receiving Sunlight energy, frictional heat energy from the moon's gravity forces, and nuclear decay energy from the core, while releasing a lot of entropy to the universe in the form of photons. Earth's surface might be increasing, decreasing, or constant in its entropy (I can't find an answer and delve into the effect of life in the next paragraph). A geologically dead planet receiving sunlight has a constant amount of entropy, but it is increasing the universe's entropy by turning directed high-energy sunlight photons into a much larger number of undirected low energy photons by being heated up by the Sun. A photon of lower energy has the same amount of entropy as a high energy photon because its lower momentum is offset by it being in a larger region of space (# of states=x*p). So the undirected and larger number are what makes the re-radiated photons (of equal total energy to the incoming photons) have more entropy. See Wikipedia "photon gas" where S=4/3*U/T and since T is randomly directed kinetic energy per particle (see "ideal gas" temperature derivation) and U is total energy, the entropy of randomly directed photons is proportional to their number and inversely proportional to their degree of randomization and not individual energy.
Life is the result of an influx of Gibbs free energy from the Sun, moon, core, and pre-existing geology which produces spontaneous chemical reactions . "Genes" have no physical force in and of themselves, but are durable physical-matter catalysts that are the result of the past dynamics of the available matter under the physical-force influence of the pre-existing and continuing influx of Gibbs free energy. Genes have a continuing effect on the remaining non-gene matter because of the continuing influx of Gibbs free energy. "Life creates" (more correctly: Gibb's free energy produces) solid structures which have lower entropy but it also emits gases (such as O2 can CO2) that have high entropy which approximately cancel the effect (according to my summing of the specific entropy (entropy/mole) of the products and reactants). But the products of these reactions that we call life and find useful in economics are the parts that have lower entropy per mass compared to the original ores or gases that we used as inputs.
Structures under higher and higher economic (thinking, cooperative) control have lower and lower entropy because having lower entropy means they are increasingly in "known" states which allows more control giving rise to steel, motors, solar cells, carbon fiber, nanotubes, and computer chips, in concert with pre-existing DNA crystals, bones, shells, and teeth. Stronger bonds almost always means lower entropy because the atoms can't jiggle as far away to different states (states ~ momentum times position=x*p). Entropy per mole of a material = a*ln(x*p)+b where a and b are constants for a given phase (gas, liquid, solid) of a given set of molecules or atoms. x*p depends on volume and temperature, and "a" and "b" depend on mass per particle, ratio of internal energy to temperature (random kinetic energy) of each molecule or atom, and the degree of dependency of the x*p states of each molecule or atom on each other (see "phonons").
Saturday, March 19, 2016
entropy as a force, evolution, economics, dynamics
He does not explain the variables clear enough for me to understand or use. Your summary of it, which he states in a similar way, is a common tactic in competition against others or nature when the future is less predictable. But in well defined problems that you can model completely, there is a specific path chosen that can greatly violate this rule (as viewed from the perspective of someone with less knowledge). But from an omniscient view, knowing the best path is like never having an option except to choose that path. Not knowing or being able to control the future is intrinsic to wanting to keep options open. "Options" depends on amount of knowledge like "order" and entropy. "Entropy" is a measurable thing not subject to opinion, but it is a willful blinding of the most of the data: it throws out the details of the exact momentum and position of each particle and relies only on the bulk measurements of T, P, N, and V.
I believe "keeping options open" is equal to not spending Gibbs free energy which a combination of potential energy and pre-existing order. He shows a weight on a stick that automatically balances. I do not know how he got from his equation to that, but maintaining potential energy achieves the same thing. It is also the lowest-entropy state: we can see it is straight up which is a defined position, but it may fall in many different directions. It is keeping options open, and yet it is preventing entropy from being increased. As you've listed the equation, the standard entropy force, it should immediately fall. This is not exactly the equation he uses. His subscripts are saying max entropy gradient over a certain time, or something like that. It seems his equation is maintaining the gradient at a max which is right before it "decides" which way to fall.
We keep assets (potential energy in a low entropy state) that we believe will maintain value (be convertible to work energy with minimal entropy production, aka efficient) in times of turmoil. It could be dollars, gold, bitcoin, skill, or social contacts. But if we know the future, we spend it on other things that will result in the most long term profit (acquisition of other low entropy potential energy assets like a stock that may fluctuate wildly in this value. The end goal is supposedly to transfer the potential energy gains to our offspring so they can survive in the future, where "offspring" could be children, ideas, machines, or the greater community.
You have cast this physics idea as under the control of intelligence, but I believe the physics of matter causes intelligence to occur. I believe the "meaning of life" (the goal of godless, mindless dynamics) is to emit entropy to the universe while decreasing it locally and increasing local potential energy. For example, biology seems to be replacing itself with more efficient machines that depend on very strong bonds in order to acquire sunlight energy and to use that energy to move matter, make structures, and to think about how to do it most efficiently and profitably (more potential energy and lower entropy in the end). These very strong bonds in today's society depend on oxygen atoms being removed from carbon (nanotubes, graphite, carbon fiber), metal ores, and silicon (CPUs and Solar cells). I do not know the chemistry of cement well enough to include it. Imagine society if the silicon, metals, and carbons did not exist (or they still had their natural oxygens attached). Look at the exponential trends of these increasing as biology decreases in relevance to the economic (economizing) machine. Economizing means spending energy and order (ores in a vien is pre-existing low entropy) effieicntly, but what is economics efficiently trying to do? The will of people? No. That assumes mind controls matter, but mind is not seperable from body, and mind has no rpe-existing force dynamics did not give it. Believing mind controls us is like believing in a soul. It's a handy but false model like a "selfish" gene. Mind and genes are implementing physical dynamics. Genes are the physical memory of past dynamics. Mind is a chemical reaction, not a pre-existing or fundamental force.
Evolution is the result of the dynamics of matter. Matter moves as a result of energy potentials (F=-dU) and low entropy (F=TdS). We think mind controls, but it is the expression of past dynamics under these two forces. Schrodinger initially said "negative entropy" was key to life, but in an update he corrected himself to say it was Gibb's free energy, dG=dU+pdV-TdS. For Earth's surface, p, V, and T are kind of constant, and the remaining dU and dS are the two forces I've just mentioned. The minus sign works out because here we have F=T*dS and all other forces are the result of F=-dU. F=ma implies an intelligence behind the F to move the m, but there it is ultimately sourced from a -dU and TdS. -dU+TdS=F=ma, not Mind+genes=F=ma.
I view evolution as dynamics creating memory/computation systems that catalyze matter into forming more memory/computational systems. Structures and bodies are the support structures for minds to create more minds, so it is easy to see why we think of mind as a primary force. But the primary source is dynamics. "We" (dynamics) cash in on the environment's dU and -dS to replenish and add more of them to our own systems (energy is released if we put the oxygen back into our silicon, metals, and carbon, as well as entropy increasing back to where it was). The dynamics trend is to create local order and increased potential energy, cashing in on energy from the sun. Fossil fuels are being depleted, but there's potential energy in the new bonds we are creating and they are harder to get started in burning. Entropy does not increase on Earth because it is an open system.
When oxygen is removed, the refined solids have 1/5 as much entropy. The waste heat and entropy emitted in the refining is released to the Universe, leaving a much lower entropy in the solids that make up society. They also acquire a large amount of potential energy like fossil fuels compared to the previous ores. Denser materials result in lower entropy because less flexibility means fewer position*momentum states that can be occupied at a given temperature. This also means the materials are more predictable and controllable in a deep sense that makes them more efficient in structures, thinking machines, energy acquisition, and movement of matter.
I believe "keeping options open" is equal to not spending Gibbs free energy which a combination of potential energy and pre-existing order. He shows a weight on a stick that automatically balances. I do not know how he got from his equation to that, but maintaining potential energy achieves the same thing. It is also the lowest-entropy state: we can see it is straight up which is a defined position, but it may fall in many different directions. It is keeping options open, and yet it is preventing entropy from being increased. As you've listed the equation, the standard entropy force, it should immediately fall. This is not exactly the equation he uses. His subscripts are saying max entropy gradient over a certain time, or something like that. It seems his equation is maintaining the gradient at a max which is right before it "decides" which way to fall.
We keep assets (potential energy in a low entropy state) that we believe will maintain value (be convertible to work energy with minimal entropy production, aka efficient) in times of turmoil. It could be dollars, gold, bitcoin, skill, or social contacts. But if we know the future, we spend it on other things that will result in the most long term profit (acquisition of other low entropy potential energy assets like a stock that may fluctuate wildly in this value. The end goal is supposedly to transfer the potential energy gains to our offspring so they can survive in the future, where "offspring" could be children, ideas, machines, or the greater community.
You have cast this physics idea as under the control of intelligence, but I believe the physics of matter causes intelligence to occur. I believe the "meaning of life" (the goal of godless, mindless dynamics) is to emit entropy to the universe while decreasing it locally and increasing local potential energy. For example, biology seems to be replacing itself with more efficient machines that depend on very strong bonds in order to acquire sunlight energy and to use that energy to move matter, make structures, and to think about how to do it most efficiently and profitably (more potential energy and lower entropy in the end). These very strong bonds in today's society depend on oxygen atoms being removed from carbon (nanotubes, graphite, carbon fiber), metal ores, and silicon (CPUs and Solar cells). I do not know the chemistry of cement well enough to include it. Imagine society if the silicon, metals, and carbons did not exist (or they still had their natural oxygens attached). Look at the exponential trends of these increasing as biology decreases in relevance to the economic (economizing) machine. Economizing means spending energy and order (ores in a vien is pre-existing low entropy) effieicntly, but what is economics efficiently trying to do? The will of people? No. That assumes mind controls matter, but mind is not seperable from body, and mind has no rpe-existing force dynamics did not give it. Believing mind controls us is like believing in a soul. It's a handy but false model like a "selfish" gene. Mind and genes are implementing physical dynamics. Genes are the physical memory of past dynamics. Mind is a chemical reaction, not a pre-existing or fundamental force.
Evolution is the result of the dynamics of matter. Matter moves as a result of energy potentials (F=-dU) and low entropy (F=TdS). We think mind controls, but it is the expression of past dynamics under these two forces. Schrodinger initially said "negative entropy" was key to life, but in an update he corrected himself to say it was Gibb's free energy, dG=dU+pdV-TdS. For Earth's surface, p, V, and T are kind of constant, and the remaining dU and dS are the two forces I've just mentioned. The minus sign works out because here we have F=T*dS and all other forces are the result of F=-dU. F=ma implies an intelligence behind the F to move the m, but there it is ultimately sourced from a -dU and TdS. -dU+TdS=F=ma, not Mind+genes=F=ma.
I view evolution as dynamics creating memory/computation systems that catalyze matter into forming more memory/computational systems. Structures and bodies are the support structures for minds to create more minds, so it is easy to see why we think of mind as a primary force. But the primary source is dynamics. "We" (dynamics) cash in on the environment's dU and -dS to replenish and add more of them to our own systems (energy is released if we put the oxygen back into our silicon, metals, and carbon, as well as entropy increasing back to where it was). The dynamics trend is to create local order and increased potential energy, cashing in on energy from the sun. Fossil fuels are being depleted, but there's potential energy in the new bonds we are creating and they are harder to get started in burning. Entropy does not increase on Earth because it is an open system.
When oxygen is removed, the refined solids have 1/5 as much entropy. The waste heat and entropy emitted in the refining is released to the Universe, leaving a much lower entropy in the solids that make up society. They also acquire a large amount of potential energy like fossil fuels compared to the previous ores. Denser materials result in lower entropy because less flexibility means fewer position*momentum states that can be occupied at a given temperature. This also means the materials are more predictable and controllable in a deep sense that makes them more efficient in structures, thinking machines, energy acquisition, and movement of matter.
Monday, March 7, 2016
Drawing homer simpson with fourier transform
I was able to use the pixels directly as an imaginary number x+i*y in the 3rd equation on wiki's discrete fourier transform article. This means in excel I had a table for the real part of each Xk that was x*cos(-2*pi*k*n/N)-y*sin(-2*pi*k*n/N) for each x pixel value as n pixels (rows) went from 0 to N and as k columns also varied from 0 to N, so it was a table with N rows and N colums. Then another table for the Xk imaginary part was y*cos()+x*sin(). Each column was summed for each table, so there was a real and imaginary part for each k, which is the goal, the fourier transform. To generate the image back again from these imaginary numbers, the 4th equation on the wiki page is used. So the R of each circle in the homer simpson epicycle video is each |Xk|/N. The rotation rate for each circle is 2*pi*k. n/N is the "time", the fraction of the circle that has been completed. k=0 gives the offset of the image away from the origin. k=1 is the largest circle with the slowest rate. The angle of Xk is an offset.
The pixels do not have to need to be equal distance apart on the path of the line trace, and you may not even need to reverse course in collecting pixels on the line if an end-of-line is reached. Notice this occurs on the back hair in this video: the course was traced back on the hairs. My version of excel can only do 243 points due to column limitations. It's a lot easier to program it than to use a spreadsheet. mobilefish site allowed me to extract xy coordinates from an uploaded image, but i could not get really them equal distance apart so my results were not very good. The more points you have, the more precision you have to have in making sure they are equal distance apart. Also, you have to end 1 position next to pixel you began on.
Here's the video of drawing homer simpson as a sum of sinusoids
https://youtu.be/QVuU2YCwHjw
Here are my results on homer simpson and the batman symbol:
youtube comment giving details on how to do it:
This turned out very easy: Let the pixels equal an imaginary number x+i*y in the 3rd equation on wiki's discrete fourier transform article. This gave me a table for the real part of each Xk that was x*cos(-2*pi*k*n/N)-y*sin(-2*pi*k*n/N) for each x pixel value as n pixels (rows) went from 0 to N and as k columns also varied from 0 to N, so it was a table with N rows and N colums. Then another table for the Xk imaginary part was y*cos()+x*sin(). Each column was summed for each table, so there was a real and imaginary part for each k, which is the goal, the fourier transform. To generate the image back from these imaginary numbers, the 4th equation on the wiki page is used (each circle in this video is from the 2nd equation and is 1/N*Xk*e^(i*z) = R*e^(i*(z+Wk)) where Xk=A+i*B=Rk*e^(i*Wk) from Euler's formula and z=2*pi*n*k/N). So the R of each circle is each |Xk|/N. You can reverse course in collecting pixels on the line if an end-of-line is reached and you're drawing a line between points. Notice this occurs on the back hair in this video. My version of excel can only do 243 points due to column limitations. It's a lot easier to program it than to use a spreadsheet, but I can't program the plotting. Mobilefish site allowed me to extract xy coordinates from an uploaded image .
The pixels do not have to need to be equal distance apart on the path of the line trace, and you may not even need to reverse course in collecting pixels on the line if an end-of-line is reached. Notice this occurs on the back hair in this video: the course was traced back on the hairs. My version of excel can only do 243 points due to column limitations. It's a lot easier to program it than to use a spreadsheet. mobilefish site allowed me to extract xy coordinates from an uploaded image, but i could not get really them equal distance apart so my results were not very good. The more points you have, the more precision you have to have in making sure they are equal distance apart. Also, you have to end 1 position next to pixel you began on.
Here's the video of drawing homer simpson as a sum of sinusoids
https://youtu.be/QVuU2YCwHjw
Here are my results on homer simpson and the batman symbol:
youtube comment giving details on how to do it:
This turned out very easy: Let the pixels equal an imaginary number x+i*y in the 3rd equation on wiki's discrete fourier transform article. This gave me a table for the real part of each Xk that was x*cos(-2*pi*k*n/N)-y*sin(-2*pi*k*n/N) for each x pixel value as n pixels (rows) went from 0 to N and as k columns also varied from 0 to N, so it was a table with N rows and N colums. Then another table for the Xk imaginary part was y*cos()+x*sin(). Each column was summed for each table, so there was a real and imaginary part for each k, which is the goal, the fourier transform. To generate the image back from these imaginary numbers, the 4th equation on the wiki page is used (each circle in this video is from the 2nd equation and is 1/N*Xk*e^(i*z) = R*e^(i*(z+Wk)) where Xk=A+i*B=Rk*e^(i*Wk) from Euler's formula and z=2*pi*n*k/N). So the R of each circle is each |Xk|/N. You can reverse course in collecting pixels on the line if an end-of-line is reached and you're drawing a line between points. Notice this occurs on the back hair in this video. My version of excel can only do 243 points due to column limitations. It's a lot easier to program it than to use a spreadsheet, but I can't program the plotting. Mobilefish site allowed me to extract xy coordinates from an uploaded image .
Thursday, March 3, 2016
Currency should "reproduce" as a result of and/or to allow infrastructure to reproduce in the same proportion
If the sole objective of an economy is to survive and reproduce, then the currency (that gives agents permission to act using the systems resources) should be increased to match a recent or expected increase in the ability of the infrastructure survive and reproduce. Deciding how to inject the new currency is part of the intelligence of the governing of the economy and currency. Evolution indicates that "happiness per person" is not the "infrastructure" goal that is being increased. The goal appears to be "harder" memory systems. It is not only longer lasting "genes" (in addition to ability to reproduce accurately* and plentifully**) in the face of assaults that benefits from "hardness" (strength of bonds) but hardness also results in fewer possible states (lower entropy) that seems to give rise to better communication within the system (i.e. better control, cooperation, and modeling even in competitive interaction that is seeking better end results). The hard structures support highly controllable and flexible movement of the much smaller "thought" elements (molecules, ions, electron, and/or photons) that are needed for modeling possibilities or algorithms and catalysts implementing known actions working towards the hard support structures. Harder structures result from strong bonds which are more dense, not counting gaps or air pockets that might be needed for lightness, insulation, or encapsulation. Stronger bonds means lower entropy because fewer states per molecule are possible (for a given temperature, S=k*ln(1.46*px/h for a single harmonic oscillator (atoms or phonons) in constrained 1D).
Happiness in a majority of individuals is a side effect of a succeeding system, not an apparent goal of evolution. Infrastructure is a mass of matter that includes algorithms, people, and other machines. It appears the primary purpose these days is to remove oxygen from metals, metalloids, and carbon which creates an infrastructure that has lower entropy, and to discover and tap into sunlight or more ores that are low-entropy concentrations that can be used to incorporate more mass into hard structures that are within a cooperative system. It emit oxygen gas which does not cause a net entropy reduction, but the mass within system itself is lower entropy. More efficient algorithms are lower real entropy due to Landauer's limit.
Is lowest entropy/mole the most survivable and expanding system? Should a governing system make laws and expand currency where it projects the greatest entropy/mole reduction will occur? Does this follow from and/or assist the least action principle? Is lower entropy/mole = happiness/mole? Is happiness = simplicity, a single state, or the progression towards it? More likely (more traditionally) evolutionary success = dGibbs F.E. = dU - T(dS/mole)/dt? Is the efficiency sought the ability to use external Gibbs free energy to increase controllable Gibbs free energy?
*or modified if it's necessary to hide from viruses or exploit nearby solutions. **Also, the entire idea of faithful reproducing is not a "goal" of "selfish" genes but is just the best solution found so far that potential energy gradients are pushing into existence.
Still weak on my practical entropy equations, but here goes:
If each independent agent (or mole of matter) has lower kinetic energy or entropy, then less heat (random kinetic energy) is present via Q=S*T. If incoming Sun energy is not simply being reflected back to space (albedo factor has not changed), then a lower Q means more potential energy is being stored. This lower average K.E. minus average potential energy which is a lower value for least action, as I have been expecting (evolution towards lower entropy is simply an expected result of dynamics). If there are more oxygen atoms in atmosphere instead of CO2, T will be lowered which may decrease local Q without decreasing S. Solar cells increase T which increases Q without necessarily lowering S.
Happiness in a majority of individuals is a side effect of a succeeding system, not an apparent goal of evolution. Infrastructure is a mass of matter that includes algorithms, people, and other machines. It appears the primary purpose these days is to remove oxygen from metals, metalloids, and carbon which creates an infrastructure that has lower entropy, and to discover and tap into sunlight or more ores that are low-entropy concentrations that can be used to incorporate more mass into hard structures that are within a cooperative system. It emit oxygen gas which does not cause a net entropy reduction, but the mass within system itself is lower entropy. More efficient algorithms are lower real entropy due to Landauer's limit.
Is lowest entropy/mole the most survivable and expanding system? Should a governing system make laws and expand currency where it projects the greatest entropy/mole reduction will occur? Does this follow from and/or assist the least action principle? Is lower entropy/mole = happiness/mole? Is happiness = simplicity, a single state, or the progression towards it? More likely (more traditionally) evolutionary success = dGibbs F.E. = dU - T(dS/mole)/dt? Is the efficiency sought the ability to use external Gibbs free energy to increase controllable Gibbs free energy?
*or modified if it's necessary to hide from viruses or exploit nearby solutions. **Also, the entire idea of faithful reproducing is not a "goal" of "selfish" genes but is just the best solution found so far that potential energy gradients are pushing into existence.
Still weak on my practical entropy equations, but here goes:
If each independent agent (or mole of matter) has lower kinetic energy or entropy, then less heat (random kinetic energy) is present via Q=S*T. If incoming Sun energy is not simply being reflected back to space (albedo factor has not changed), then a lower Q means more potential energy is being stored. This lower average K.E. minus average potential energy which is a lower value for least action, as I have been expecting (evolution towards lower entropy is simply an expected result of dynamics). If there are more oxygen atoms in atmosphere instead of CO2, T will be lowered which may decrease local Q without decreasing S. Solar cells increase T which increases Q without necessarily lowering S.
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