It was winter when I started writing this, but writing posts about physics is hard, at least if you're not a physicist. This one was particularly hard because I had to re-learn what I thought I knew about the topic, and then realize that I'd never really understood it as well as I'd thought, then try to learn it correctly, then realize that I also needed to re-learn some of the prerequisites, which led to
a whole other post ... but just for the sake of illustration, let's pretend it's still winter.
If you live near a modest-sized pond or lake, you might (depending on the weather) see it freeze over at night and thaw during the day. Thermodynamically this can be described in terms of
energy (specifically heat) and
entropy. At night, the water is giving off heat into the surrounding environment and losing entropy (while its temperature stays right at freezing). The surrounding environment is taking on heat and gaining entropy. The surroundings gain at least as much entropy as the pond loses, and ultimately the Earth will radiate just that bit more heat into space. When you do all the accounting, the entropy of the universe increases by just a tiny bit, relatively speaking.
During the day, the process reverses. The water takes on heat and gains entropy (while its temperature still stays right at freezing). The surroundings give off heat, which ultimately came from the sun, and lose entropy. The water gains at least as much entropy as the surroundings lose*, and again the entropy of the universe goes up by just that little, tiny bit, relatively speaking.
So what is this entropy of which we speak? Originally entropy was defined in terms of heat and temperature. One of the major achievements of modern physics was to reformulate entropy in a more powerful and elegant form, revealing deep and interesting connections, thereby leading to both enlightenment and confusion. The connections were deep enough that Claude Shannon, in his founding work on information theory, defined a similar concept with the same name, leading to even more enlightenment and confusion.
The original thermodynamic definition relies on the distinction between
heat and
temperature. Temperature, at least in the situations we'll be discussing here, is a measure of how energetic individual particles -- typically atoms or molecules -- are on average. Heat is a form of energy, independent of how many particles are involved.
The air in an oven heated to 500K (that is, 500 Kelvin, about 227 degrees Celsius or 440 degrees Fahrenheit) and a pot full of oil at 500K are, of course, at the same temperature, but you can safely put your hand in the oven for a bit. The oil, not so much. Why? Mainly because there's a lot more heat in the oil than in the air. By definition the molecules in the oven air are just as energetic, on average, as a the molecules the oil, but there are a lot more molecules of oil, and therefore a lot more energy, which is to say heat.
At least, that's the quick explanation for purposes of illustration. Going into the real details doesn't change the basic point: heat is different from temperature and changing the temperature of something requires transferring energy (heat) to or from it. As in the case of the pond freezing and melting, there are also cases where you can transfer heat to or from something without changing its temperature. This will be important in what follows.
Entropy was originally defined as part of understanding the
Carnot cycle, which describes the ideal heat-driven engine (the efficiency of a real engine is usually given as a percentage of what the Carnot cycle would produce, not as a percentage of the energy it uses). Among the principal results in classical thermodynamics is that the Carnot cycle was as good as you can get even in principle, but not even it can ever be perfectly efficient, even in principle.
At this point it might be helpful to read
that earlier post on energy, if you haven't already. Particularly relevant parts here are that the state of the working fluid in a heat engine, such as the steam in a steam engine, can be described with two parameters, or, equivalently, as a point in a two-dimensional diagram, and that the cycle an engine goes through can be described by a path in that two-dimensional space.
Also keep in mind the ideal gas law: In an ideal gas, the temperature of a given amount of gas is proportional to pressure times volume. Here and in the rest of this post, "gas" means "a substance without a fixed shape or volume" and not what people call "gasoline" or "petrol".
If you've ever noticed a bicycle pump heat up as you pump up a tire, that's (more or less) why. You're compressing air, that is, decreasing its volume, so (unless the pump is able to spill heat with perfect efficiency, which it isn't) the temperature has to go up. For the same reason the air coming out of a can of compressed air is dangerously cold. The air is expanding rapidly so the temperature drops sharply.
In the Carnot cycle you first supply heat a to gas (the "working fluid", for example steam in a steam engine) while maintaining a perfectly constant temperature by expanding the container it's in. You're heating that gas, in the sense of supplying heat, but not in the sense of raising its temperature. Again, heat and temperature are two different things.
To continue the Carnot cycle, let the container keep expanding, but now in such a way that it neither gains nor loses heat (in technical terms,
adiabatically). In these first two steps, you're getting work out of the engine (for example, by connecting a rod to the moving part of a piston and attaching the other part of that rod to a wheel). The gas is losing energy since it's doing work on the piston, and it's also expanding, so the temperature and pressure are both dropping, but no
heat is leaving the container in the adiabatic step.
Work is force times distance, and force in this case is pressure times the area of the surface that's moving. Since the pressure, and therefore the force, is dropping during the second step you'll need to use calculus to figure out the exact amount of work, but people know how to do that.
The last two steps of the cycle reverse the first two. In step three you compress the gas, for example by changing the direction the piston is moving, while keeping the temperature the same. This means the gas is cooling in the sense of giving off heat, but not in the sense of dropping in temperature. Finally, in step four, compress the gas further, without letting it give off heat. This raises the temperature. The piston is doing work on the gas and the volume is decreasing. In a perfect Carnot cycle the gas ends up in the same state -- same pressure, temperature and volume -- as it began and you can start it all over.
As mentioned in the previous post, you end up putting more heat in at the start then you end up getting back in the third step, and you end up getting more work out in the first two steps than you put in in the last two (because the pressure is higher in the first two steps). Heat gets converted to work (or if you run the whole thing backwards, you end up with a refrigerator).
If you plot the Carnot cycle on a diagram of pressure versus volume, or the other two combinations of pressure, volume and temperature, you get a a shape with at least two curved sides, and it's hard to tell whether you could do better. Carnot proved that this cycle is the best you can do, in terms of how much work you can get out of a given amount of heat, by choosing two parameters that make the cycle into a rectangle. One is temperature -- steps one and three maintain a constant temperature.
The other needs to make the other two steps straight lines. To make this work out, the second quantity has to remain constant while the temperature is changing, and change when temperature is constant. The solution is to define a quantity -- call it entropy -- that changes, when temperature is constant, by the amount of heat transferred, divided by that temperature (ΔS = ΔQ/T -- the deltas (Δ) say that we're relating changes in heat and entropy, not absolute quantities; Q stands for heat and S stands for entropy, because reasons). When there's no heat transferred, entropy doesn't change. In step one, temperature is constant and entropy increases. In step two, temperature decreases while entropy remains constant, and so forth.
To be clear, entropy and temperature can, in general, both change at the same time. For example, if you heat a gas at constant volume, then pressure, temperature and entropy all go up. The Carnot cycle is a special case where only one changes at a time.
Knowing the definition of entropy, you can convert, say, a pressure/volume diagram to a temperature/entropy diagram and back. In real systems, the temperature/entropy version won't show absolutely straight vertical and horizontal lines -- that is, there will be at least some places where both change at the same time. The Carnot cycle is exactly the case where the lines are perfectly horizontal and vertical.
This definition of entropy in terms of heat and temperature says nothing at all about what's going on in the gas, but it's enough, along with some math I won't go into here (but which depends on the cycle being a rectangle), to prove Carnot's result: The portion of heat wasted in a Carnot cycle is the ratio of the cold temperature to the hot temperature (on an absolute temperature scale). You can only have zero loss -- 100% efficiency -- if the cold temperature is absolute zero. Which it won't be.
Any cycle that deviates from a perfect rectangle will be less efficient yet. In real life this is inevitable. You can come pretty close on all the steps, but not perfectly close. In real life you don't have an ideal gas, you can't magically switch from being able to put heat into the gas to perfectly insulating it, you won't be able to transfer all the heat from your heat source to the gas, you won't be able to capture all the heat from the third step of the cycle to reuse in the first step of the next cycle, some of the energy of the moving piston will be lost to friction (that is, dissipated into the surroundings as heat) and so on.
The problem-solving that goes into minimizing inefficiencies in real engines is why engineering came to be called engineering and why the hallmark of engineering is getting usefulness out of imperfection.
There are other cases where heat is transferred at a constant temperature, and we can define entropy in the same way as for a gas. For example, temperature doesn't change during a
phase change such as melting or freezing. As our pond melts and freezes, the temperature stays right at freezing until the pond completely freezes, at which point it can get cooler, or melts entirely, at which point it can get warmer.
If all you know is that some water is at the freezing point, you can't say how much heat it will take to raise the temperature above freezing without knowing how much of it is frozen and how much is liquid. The concept of entropy is perfectly valid here -- it relates directly to how much of the pond is liquid -- and we can define "entropy of fusion" to account for phase transitions.
There are plenty of other cases that don't look quite so much like the ideal gas case but still involve changes of entropy. Mixing two substances increases overall entropy. Entropy is a determining factor in whether a chemical reaction will go forward or backward and in ice melting when you throw salt on it.
Before I go any further about thermodynamic entropy, let me throw in that Claude Shannon's definition of entropy in information theory is, informally, a measure of the number of distinct messages that could have been transmitted in a particular situation. On the other blog, for example,
I've ranted about bits of entropy for passwords. This is exactly a measure of how many possible passwords there are in a given scheme for picking passwords.
What in the world does this have to do with transferring heat at a constant temperature? Good question.
Just as the concept of energy underwent several shifts in understanding on the way to its current formulation, so did entropy. The first major shift came with the development of
statistical mechanics. Here "mechanics" refers to the behavior of physical objects, and "statistical" means you've got enough of them that you're only concerned about their overall behavior.
Statistical mechanics models an ideal gas as a collection of particles bouncing around in a container. You can think of this as a bunch of tiny balls bouncing around in a box, but there's a key difference from what you might expect from that image. In an ideal gas, all the collisions are perfectly
elastic, meaning that the energy of motion (called
kinetic energy) remains the same before and after. In a real box full of balls, the kinetic energy of the balls gets converted to heat as the balls bump into each other and push each other's molecules around, and sooner or later the balls stop bouncing.
But the whole point of the statistical view of thermodynamics is that heat is just the kinetic energy of the particles the system is made up of. When actual bouncing balls lose energy to heat, that means that the kinetic energy of the large-scale motion of the balls themselves is getting converted into kinetic energy of the small-scale motion of the molecules the balls are made of, and of the air in the box, and of the walls of the box, and eventually the surroundings. That is, the large scale motion we can see is getting converted into a lot of small-scale motion that we can't, which we call heat.
When two particles, say two oxygen molecules, bounce off each other, the kinetic energy of the moving particles just gets converted into kinetic energy of differently-moving particles, and that's it. In the original formulation of statistical mechanics, there's simply no other place for that energy to go, no smaller-scale moving parts to transfer energy to (assuming there's no chemical reaction between the two -- if you prefer, put pure helium in the box).
When a particle bounces off the wall of the container, it imparts a small
impulse -- an instantaneous force -- to the walls. When a whole lot of particles continually bounce off the walls of a container, those instantaneous forces add up to (for all practical purposes) a continuous force, that is, pressure.
Temperature is the average kinetic energy of the particles and volume is, well, volume. That gives us our basic parameters of temperature, pressure and volume.
But what is entropy, in this view? In statistical mechanics, we're concerned about the large-scale (
macroscopic) state of the system, but there are many different small-scale (
microscopic) states that could give the same macroscopic picture.
Once you crank through all the math, it turns out that entropy is a measure of
how many different microscopic states, which we can't measure, are consistent with the macroscopic state, which we can measure. In fuller detail, entropy is actually proportional to the logarithm of that number -- the number of digits, more or less -- both because the raw numbers are ridiculously big, and because that way the entropy of two separate systems is the sum of the entropy of the individual systems.
The actual formula is
S = k ln(W), where
k is Boltzmann's constant and
W is the total number of possible microstates, assuming they're all equally probable. There's a slightly bigger formula if they're not. Note that, unlike the original thermodynamic definition, this formula deals in absolute quantities, not changes.
When ice melts, entropy increases. Water molecules in ice are confined to fixed positions in a crystal. We may not know the exact energy of each individual molecule, but we at least know more or less where it is, and we know that if the energy of such a molecule is too high, it will leave the crystal (if this happens on a large scale, the crystal melts). Once it does, we know much less about its location or energy.
Even without a phase change, the same sort of reasoning applies. As temperature -- the average energy of each particle -- increases, the range of energies each particle can have increases. How to translate this continuous range of energies into a number we can count is a bit of a puzzle, but we can handwave around that for now.
Entropy is often called a measure of disorder, but more accurately it's a measure of uncertainty (as theoretical physicist Sabine Hossenfelder puts it: "
a measure for unresolved microscopic details"), that is, how much we don't know. That's why Shannon used the same term in information theory. The entropy of a message measures how much we don't know about it just from knowing its size (and a couple of other macroscopic parameters). Shannon entropy is also logarithmic, for the same reasons that thermodynamic entropy is.
The formula for Shannon entropy in the case that all possible messages are equally probable is
H = k ln(M), where
M is the number of messages. I put
k there to account for the logarithm usually being base 2 and because it emphasizes the similarity to the other definition. Again, there's a slightly bigger formula if the various messages aren't all equally probable, and it too looks an awful lot like the corresponding formula for thermodynamic entropy.
The original formulation of statistical mechanics assumed that physics at the microscopic scale followed Newton's laws of motion. One indication that statistical mechanics was on to something is that when quantum mechanics completely reformulated what physics looks like at the microscopic scale, the statistical formulation not only held up, but became more accurate with the new information available.
In our current understanding, when two oxygen molecules bounce off each other, their electron shells interact (there's more going on, but let's start there), and eventually their energy gets redistributed into a new configuration. This can mean the molecules traveling off in new paths, but it could also mean that some of the kinetic energy gets transferred to the electrons themselves, or some of the electrons' energy gets converted into kinetic energy.
Macroscopically this all looks the same as the old model, if you have huge numbers of molecules, but in the quantum formulation we have a more precise picture of entropy. This makes a difference in extreme situations such as extremely cold crystals. Since energy is quantized, there is a finite (though mind-bendingly huge) number of possible quantum states a typical system can have, and we can stop handwaving about how to handle ranges of possible energy. This all works whether you have a gas, a liquid, an ordinary solid or some weird Bose-Einstein condensate. Entropy measures that number of possible quantum states.
Thermodynamic entropy and information theoretic entropy are measuring basically the same thing, namely the number of specific possibilities consistent with what we know in general. In fact, the modern definition of thermodynamic entropy specifically starts with a raw number of possible states and includes a constant factor to convert from the raw number to the units (energy over temperature) of classical thermodynamics.
This makes the two notions of entropy look even more alike -- they're both based on a count of possibilities, but with different scaling factors. Below I'll even talk, loosely, of "bits worth of thermodynamic entropy" meaning the number of bits in the binary number for the number of possible quantum states.
Nonetheless, they're not at all the same thing in practice.
Consider a molecule of DNA. There are dozens of atoms, and hundreds of subatomic particles, in a base pair. I really don't know how many possible states a phosphorous atom (say) could be in under typical conditions, but I'm going to guess that there are thousands of bits worth of entropy in a base pair at room temperature. Even if each individual particle can only be on one of two possible states, you've still got hundreds of bits.
From an information-theoretic point of view, there are four possible states for a base pair, which is two bits, and because the genetic code actually includes a fair bit of redundancy in the form of different ways of coding the same amino acid and so forth, it's actually more like 10/6 of a bit, even without taking into account other sources of redundancy.
But there
is a lot of redundancy in your genome, as far as we can tell, in the form of duplicated genes and stretches of DNA that might or might not do anything. All in all, there is about a gigabyte worth of base pairs in a human genome, but the actual gene-coding information can compress down to a few megabytes. The
thermodynamic entropy of the molecule that encodes those megabytes is much, much, larger. If each base pair represents about a thousand bits worth of thermodynamic entropy under typical conditions, then the whole strand is into the hundreds of gigabytes.
I keep saying "under typical conditions" because thermodynamic entropy, being thermodynamic, depends on temperature. If you have a fever, your body, including your DNA molecules in particular, has higher entropy than if you're sitting in an ice bath. The information theoretic entropy, on the other hand, doesn't change.
But all this is dwarfed by another factor. You have billions of cells in your body (and trillions of bacterial cells that don't have your DNA, but never mind that). From a thermodynamic standpoint, each of those cells -- its DNA, its RNA, its proteins, lipids, water and so forth -- contributes to the overall entropy of your body. A billion identical strands of DNA at a given temperature have the same information content as a single strand but a billion times the thermodynamic entropy.
If you want to compare bits to bits, the Shannon entropy of your DNA is inconsequential compared to the thermodynamic entropy of your body. Even the change in the thermodynamic entropy of your body as you breathe is enormously bigger than the Shannon entropy of your DNA.
I mention all this because from time to time you'll see statements about genetics and the second law of thermodynamics. The second law, which is very well established, states that the entropy of a closed system cannot decrease over time. One implication of it is that heat doesn't flow from cold to hot, which is a key assumption in Carnot's proof.
Sometimes the second law is taken to mean that genomes can't get "more complex" over time, since that would violate the second law. The usual response to this is that living cells aren't closed systems and therefore the second law doesn't apply. That's perfectly valid. However, I think a better answer is that this confuses two forms of entropy -- thermodynamic entropy and Shannon entropy -- which are just plain different. In other words, thermodynamic entropy and the second law don't work that way.
From an information point of view, the entropy of a genome is just how many bits it encodes once you compress out any redundancy. Longer genomes typically have more entropy. From a thermodynamic point of view, at a given temperature, more of the same substance has higher entropy than less as well, but we're measuring different quantities.
A live elephant has much, much higher entropy than a live mouse, and likewise for a live human versus a live mouse. As it happens, a mouse genome is roughly the same size as a human genome, even though there's a huge difference in thermodynamic entropy between a live human and a live mouse. The mouse genome is slightly smaller than ours, but not a lot. There's no reason it couldn't be larger, and certainly no thermodynamic reason. Neither the mouse nor human genome is particularly large. Several organisms have genomes dozens of times larger, at least in terms of raw base pairs.
From a thermodynamic point of view, it hardly matters what exact content a DNA molecule has. There are some minor differences in thermodynamic behavior among the particular base pairs, and in some contexts it makes a slight difference what order they're arranged in, but overall the gene-copying machinery works the same whether the DNA is encoding a human digestive protein or nothing at all. Differences in gene content are dwarfed by the thermodynamic entropy change of turning one strand of DNA and a supply of loose nucleotides into two strands, that in turn is dwarfed by everything else going on in the cell, and that in turn is dwarfed by the jump from one cell to billions.
For what it's worth, content makes even less thermodynamic difference in other forms of storage. A RAM chip full of random numbers has essentially the same thermodynamic entropy, at a given temperature, as one containing all zeroes or all ones, even though those have drastically different Shannon entropies. The thermodynamic entropy changes involved in
writing a single bit to memory are going to equate to a lot more than one bit.
Again, this is all assuming it's valid to compare the two forms of entropy at all, based on their both being measures of uncertainty about what exact state a system is in, and again, the two are not actually comparable, even though they're similar in form. Comparing the two is like trying to compare a football score to a basketball score on the basis that they're both counting the number of times the teams involved have scored goals.
There's a lot more to talk about here, for example the relation between symmetry and disorder (more disorder means
more symmetry, which was not what I thought until I sat down to think about it), and the relationship between entropy and time (for example, as
experimental physicist Richard Muller points out,
local entropy decreases all the time without time appearing to flow backward), but for now I think I've hit the main points:
- The second law of thermodynamics is just that -- a law of thermodynamics
- Thermodynamic entropy as currently defined and information-theoretic (Shannon) entropy are two distinct concepts, even though they're very similar in form and derivation.
- The two are defined in different contexts and behave entirely differently, despite what we might think from them having the same name.
- Back at the first point, the second law of thermodynamics says almost nothing about Shannon entropy, even though you can, if you like, use the same terminology in counting quantum states.
- All this has even less to do with genetics.
* Strictly speaking, you need to take the Sun into account. The Sun is gaining entropy over time, at a much, much higher rate than our little pond and its surroundings, and it's only an insignificantly tiny part of the universe. But even if you had a closed system, of a pond and surroundings that were sometimes warm and sometimes cold, for whatever reason, the result would be the same: The entropy of a closed system increases over time.
