Simulation of the
Universe
By
Neil
J Boucher
Synopsis
The article looks at
what it would take to simulate the universe and what such a universe might look
like. Could we tell if we were
living in such a universe??
The general conclusion
is that it is decidedly possible to simulate the universe, provided the universe
is quantized and finite, but that it would fail the Occam’s razor test in that it would not be the simplest way
to build a universe.
The Computational
Task
Here we consider what
would be necessary to completely simulate the known universe. We find that it is not something that
can be achieved from within the universe.
The are about 10
particles
in the universe and if we allow each to have 10 properties (which will include
location, momentum, spin, charge, mass) then we have to store 10 
pieces of information. However looking at this a bit more
closely it becomes a bit more complex.
If, in the real world, momentum for example can take on any value then it can take on values
that include irrational values. Even to store one such value we would
need infinite storage capacity.
Therefore to be computable the world must be quantized! It also follows
that all information about the
universe and its components must be quantized if we are to even consider
computerizing it. This includes the scale of the universe and so precludes an
infinite universe. The number of bits for storage of information (as distinct
from pieces of information, as one velocity for example might require 40 bits to
store it) will depend on the quantizing scale.
Since a top end PC
might have 500 gigs of memory (5 x 10
bytes)
we fall a long way short and cannot even consider it a candidate. In fact we would need to do something
rather clever to store enough information because we would need, as a minimum,
all the particles in the universe just to store the information if we did it the
way a PC does. This holds true even if we could find some way to optimize the
use of those particles (your PC might use 1000’s of atoms, or 100,000’s of
particles to store 1 bit of information).
So if we were to ask
the question can we precisely model the known universe, from within the known
universe, the answer must be NO. We
can only model much simpler and smaller universes than the one that we
occupy.
This eliminates the
multiple mirror image computational model; that is, we cannot have universes
that contain computers that in turn spawn new universes as models, unless those
models are significantly smaller and less complex than the original universe
that originated the model.
In an article for
Nature, June 2002, Seth Lloyd of MIT in 
bits
and a CPU that would have manipulated 10
bits
of information in the time since the big bang. His estimate is based on the energy
equivalent of the universe, but can be seen to be consistent with the number of
particles contained within.
The
God Problem
In primitive societies
man looked about and saw that all was too complicated to explain and so he
invented a god that “explained it all”. There is however a problem with this
approach. Suppose you find a watch
on a deserted island, and you can’t understand how it came to be, so you
conceive the watch maker. Now the
watch maker is more complex that the watch so you conceive a god. The logical
process of this thinking is that there is a god of gods and so on. Each new god more complex than the one
before. This really leads nowhere.
To say that one of the god’s “always was, and did not need a creator” is
simply avoiding the question and does not explain anything. An explanation must simply the situation
not add complexity to it.
The computational
model of the universe has to face its own god problem. The computer that runs the simulation is
necessarily more complex, contains more information and is “god-like” compared
to the universe itself. You have
not solved anything at all by postulating a computational universe, but have
replaced a difficult problem about the complexity of the universe, with a yet
more complex machine to run it all in.
The
Quantum Mechanical Problem
Many have looked at
quantum mechanics as a “proof” of a computational universe. This approach suffers from the same sort
of problem as the God concept.
Firstly and fore mostly no one has any idea what is going on at the
quantum mechanical level. Quantum
mechanics is not a description of
quantum mechanical reality, but a mathematical construct that mimics the outward
behavior of the quantum world.
To illustrate this
lets assume someone has somehow managed to model the share market. Lets say that the model is accurate to
+/-5% (this in itself would be an
incredible achievement). Now such a
model can easily be seen as nothing more than a model, and it does not tell us
anything about you or me as investors, but simply mathematically predicts the
herd behavior. It is also not
necessarily unique. Other models
based on different premises might give equally good results. A good working stock market model will
most likely be a substitute for real knowledge rather than evidence of complete
understanding.
The masters of quantum
mechanics are aware that their mathematics is a working model and not something
based on a deeper understanding. The fact that the current quantum mechanical
model is inconsistent with Relativity suggests that it is incomplete. Its high
level of agreement with experiment to date shows it to be a very good model, but
there is reason to believe that some day researchers will find discrepancies
between the theory and measurement.
After all, the model is known to be incomplete and this must at some time
show up as a disagreement with measurements if they are precise
enough.
Now we see the
problem. The mathematics of quantum
mechanics is not reality based, but
is a mathematical construct that mimics the reality as seen in the
laboratory. One should not be
surprised therefore that the mathematics looks like a model because that is all
it is.
So the argument that
quantum mechanical behavior looks computational is circuitous. Quantum mechanics
as we know it, is a model of reality and nothing more. It has never claimed to be
otherwise. We cannot directly infer
anything about the real nature of the universe from quantum mechanics.
A
Computer for a Computational Universe
As we have seen the
universe that we occupy cannot be computed from within the universe itself. That is if the universe were
computational, the stuff that the computer itself is made of is not of this
universe and has no need to be related to the universe in any way. To clarify a computer that flies the
space shuttle or one that makes cars will be of the same kind and may even have
the same operating system. The computers may even happen to be identical. However the stuff that the computer is
made of is totally independent of its function and the computer makers need not
know in advance that application that the computer is intended
for.
So a computer that
simulates the known universe need not, and probably would not be made of
electrons, protons and photons etc. These particles should then be regarded
as simulated and their forms
(properties) likewise can be simple mathematical constructs.
It is unlikely that
the computer would be made of the same sort of stuff that it is simulating.
Likewise the constants of the known universe (gravitational constant, the ratio
of the mass of a proton to and electron and such) can be simple mathematical
starting points. Other limitations
like the speed of light need not be applicable in any way to the computer
itself. This gives us the
possibility of allowing that the computer simulation has looked at many possibly
worlds where many possible particle properties have been tried and the
successful models are the ones that are left running.
Consciousness
A lot of people seem
to have a problem with consciousness, and I am not sure why this is. The brain is a massively parallel
computer that has many conflicting processes. For example the fight or flight response
is really a fight and flight
response. The adrenalin prepares us
for both and the brain considers both; not so much sequentially but in
parallel. On this issue and many
others, the left and right hand side of the brain will come to totally
conflicting conclusions.
Therefore a higher
function of the brain has to be to manage all these inputs and decide on a
course of action. It seems straight
forward enough to allow that this management center would start as a fairly
basic bit of brain hardware, but as the brain evolves the demands on the
management system would rapidly increase.
The management center in the human brain would be called on to make many
varied and complex decisions.
Consciousness in this
light is the evolution of the management function from one that simply resolves
conflicting “reports” from other brain centers to one whereby the management
system can reflect on its own performance (that is it begins to manage
itself). The management system is
now not only aware of the other brain functional centers but becomes aware of
itself. This argument is consistent
with the point of view that all brains except the most simple would have evolved
some form of self consciousness and that the level of consciousness would
increase with the brain complexity.
Consciousness in this
view has a purpose. A management
system that does not review its own performance would be doomed to repeat the
mistakes of the past. However one
that does have a review process, can allow the subordinate centers to show a
degree of folly and ignore it.
Suppose the management
center were not self reviewing and was simply an automatic “judge”. It simply weighs the inputs from all the
competing brain sections and makes a decision. In order to avoid repeating mistakes
then since the management is not self reviewing, the subordinate centers need to
get feedback on the result of there advice and to modify their advice for the
next similar event accordingly.
While this may happen in some instances, there is a lot of evidence from
clinical studies that the subordinate parts of the brain do not have good
feedback paths. In split brain
experiments one part of the brain will consistently deny a truth known to the
other part of the brain. Conflict
over something as simple as whether or not the person likes a certain food can
exist between the two halves of the brain.
Another instance of this is a person with brain damage who could
recognize his mother readily when she called in by phone, but would insist that
she was an imposter when she appeared in person.
From the experiments
above (and others) I think we can conclude that the subordinate parts of the
brain are only minimally conscious and are not especially good at communicating
to each other. The management
system is thus the bit that becomes self aware. As a caution here, when speaking of
parts of the brain the meaning should be taken as “functional parts of the
brain”. It is not suggested that
the brain is physically partitioned into a conscious and an unconscious part,
but rather that this partition is functional.
So to be truly
efficient the brain needs to be self-appraising on some level and it appears
that this is the highest level. If
consciousness requires a considerable computing overhead it would make sense to
centrally locate it. The importance
of this is that were the consciousness to be distributed it would not need to be
particularly “strong” because at each place that it occurred it would be
specialized. By centralizing
consciousness we are giving consciousness (which is merely initially at least
the ability for self-performance evaluation) a chance to evolve into something
very powerful indeed.
Because the management
center makes its decisions in a different way to the rest of the brain it would
be important when weighing the inputs that it was aware that its own input
(essentially memories of its past
decisions) are of a different kind and need to be treated differently to the
subordinate inputs. Thus from an
early evolutionary stage it would be an advantage to distinguish its own inputs
from the others. It is already
starting to become self aware!
Really therefore
consciousness is not of itself a problem for a computational universe. The computer needs to be massively
parallel with a management system that can itself evolve.
Quantum Computers
Much has been made of
the potentially staggering computing power of a quantum computer. However with today’s limited knowledge
of quantum computers there is no certainty at all that large quantum computers
could ever be built. The problem is
that the quantum nature only reveals itself at very small scales. Once a large number of particles are
assembled the quantum nature fades away to make way for classical behavior. The
result of this is that a 10 particle quantum computer is still a thing of the
future and that its capabilities, even when built, would not match that of a
$3.00 handheld calculator. Current
theory is not capable of predicting upper limits to the size of a quantum
computer, simply because it is not understood what it is that governs the
transition to classical behavior.
We also need to be
careful to distinguish computational power with storage capabilities. Potentially, the quantum computer might
be the ultimate number cruncher, but it does not offer an equivalent boost in
storage capabilities. Additionally what gives the quantum computer its power is
its massive parallel computing power; the downside however is that once we
extract one of the solutions we lose the others.
Quantum computers
could come in handy however for generating true randomness; which is something
that a macro computer is unable to do.
The quantum computer need not be especially powerful to do this and such
a device is within the feasibility of today’s technology.
Non
Computable Things
Many things are not
computable. For example irrational
numbers like pi cannot be represented digitally on a computer. It is
approximately 3.14159 or more closely 3.14159 26535 89793 23846 26433 83279
50288 41971 69399 37511 (the value to 50 decimal places), but no matter how many
digits we calculate it to we will never have it precisely. As the true value of
pi is infinite in length then it would require an infinite storage capacity to
hold it. However in a quantized
world, this is not a problem as there is a “smallest” dimension of space. Therefore the concept of a perfect
circle is a fiction and any real circle will in fact be a polygon with a finite
number of sides. In such a world pi is merely and
abstraction.
So this is not an
argument for or against a computable universe, rather it is one against the
fiction of the mathematical concept of pi.
In a computable universe the value of pi, like all other values would be
truncated to a finite precision.
The
Virtually Non-computable Real World
Mathematicians and
some physicists have convinced themselves and many others that the world is
essentially a mathematically dominated domain. Mathematicians only study problems that
lead to neat mathematical solutions and for them it is a case of not seeing the
woods for the trees. Physicist
proceed to eliminate the clutter (the real world) and concentrate on the essence
(the part of the system that they are studying, isolated from outside
influences). So studying one atom
in isolation might lead to some rather neat mathematics. Two atoms are decidedly
messy and anything more is quite frightful.
A good example of the
consequences of this is the study of ballistics. The path of a ball (lets say a cannon
ball) through a vacuum under the influence of gravity that does not go too high,
has a neat mathematical solution.
It is so neat and beloved by the physicist that even today school
children are taught to calculate the path of a cannon ball fired through a
vacuum. The fact that probably no cannon has ever been fired in a vacuum is not
mentioned. Most texts dismiss the
atmosphere as something that will cause some drag on the cannon ball but for the
purposes of the study can be ignored.
The truth is that allowing for the drag is very messy and the neat
mathematics dissolves when account is taken of this parameter. Without the drag the vertical and
horizontal motions can be regarded as occurring independently and out pops a
simple solution. Allow for the drag
and this independence disappears.
The motions become correlated and no neat solution is possible (the
solution requires a computer to do a lot of approximate calculations over many
small paths). But here’s the punch
line…the error that results from ignoring the drag of the air is about 50% (the
actual value varies according to the drag coefficient of the projectile and its
speed). This huge error is
conveniently ignored! Even the famous conclusion that the angle of launch for
maximum range is 45 degrees turns out to be wrong when the drag it taken into
account (41 degrees or thereabouts is more like it).
A related example is
the many body problem. It is
relatively easy to model mathematically two bodies that are isolated from the
real world that orbit around one another.
Make it three (for example as in the earth, moon sun) and the task
becomes most formidable. Go to four
or more and it is virtually impossible. And yet most solar systems are more
complex than a four body situation
particularly if the asteroids are included.
Another seeming simple
problem is the solution to a detector circuit as seen in figure 1 below. In fact
this circuit could have come out of a high school physics book.
The circuit consists
of a signal source, a diode and a load with a filtering capacitor. If enough simplifying assumptions are
made it is relatively easy to extract mathematical solutions for this
circuit. However if we look into
the situation a bit further we find the situation is definitely too complex for
high school consideration.
Lets accept that the
diode equation is I=Io.e
Where e= the charge of
an electron
V= the voltage across the diode
K=Boltzmann’s constant
T= the absolute temperature.
Io= the reverse leakage current of the diode (a
constant)
I= the current through the diode.
which of itself is a
simplification of the diode behavior so we are already filtering some of the
clutter already. We can simplify this even more by noting the e/kT=40 (approximmately) so we can
model the diode as
I=Io.e
…eq 1
Lets ignore the
capacitor for now (more clutter that makes the problem harder) and just consider
the load resistance.
The voltage loop
around the circuit would give us
Vs=V+I.R …eq
2
where R is the load
resistance
Vs is the generator voltage (instantaneous value).
So here we have a
fairly simply pair of equations that define the circuit mathematically. However
the simplicity is deceptive. We can
conclude that
Vs=V+ Io.e.R but to solve this for V is
anything but easy.
These are but a few
examples of the enormous difficulty of actually using mathematics to model the
real world. Most real world
problems are too complex to yield to mathematics. This is not to say that all is
lost. We can use approximate
numerical methods to model all of the above examples to a very high degree of
accuracy. However the solutions are
not neat mathematical ones but involve iterative methods that start with a guess
and then home in on the solution.
Numerical methods are widely used and consume much computer time but they
are evidence of how poorly the real world conforms to
mathematics.
In summary, if you
simplify the problems by removing the real world clutter, you should not be
surprised that you get neat mathematical solutions, because that was why you
removed the clutter in the first place.
Chaos
Chaos theory tells us
that the outcome of any chaotic event is highly dependent on the initial
state. If the initial state itself
is uncertain (as it must be in quantum mechanics) then the outcome is
unpredictable and any initial uncertainty will multiply over time. If computers
were to mimic nature they would need to quantize everything. Quantizing errors
are additive and in a chaotic system even small errors can lead to very
different outcomes for the same original state.
However such
graininess exists in the real world. A world system that brings the weather into
being can be resolved down to molecular parts and at this level the patterns
would differ from those of a continuum.
So the real world becomes digital in that sense. A computer with
sufficient resolution would not be distinguishable from the real thing.
Conclusion
If the universe is a
simulation of if it is simulable then the following is
true.
- There is no place in such a universe for
irrational numbers like
and e and any equation containing these
numbers will be an approximation. - In a computed or computable universe the
equations of physics will be digital.
That is the only permitted solution will be integer multiples of the
small units (of space, .time, mass etc).
- The universe and everything in it will be
finite. This would apply also to
quantum states
- A simulated universe made of the same stuff
as the universe would be inefficient and we should expect that such a computer
would be made of other “stuff”, which we can call computrons. Computrons
would not be subject to the laws of the known universe.
As an afterthought on decoherence, the computability requirement would leave its
mark on this too. Because
computable quantum states would need to be finite in number, then so too would
entangled ones. Assuming that the
total permitted number of states (the finite number) is a constant, entangled
quantum states would become more and more restrictive. The most improbable states would become
increasingly improbable (there are more of these states so that if the total is
fixed the more improbable states would be the big losers). So a collection of quantum objects would
not suddenly decohere as is the current expectation,
but they would slowly become less and less quantum-like as the number of
entangled objects increased.
Decoherence by interaction with a non quantum object would
simply be the result of an entanglement of a quantum object with one that has
massively restricted options (the non-quantum object) When the entanglement
occurs the quantum object becomes part of the “non-quantum” object and the
restriction that the total number of
probabilities be a constant would rob the quantum object of its quantum
nature.
Thus a computable
world would be detectable. The
finite-ness of it would give it away.