Paul P. Mealing

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Saturday, 7 December 2024

Mathematics links epistemology to ontology, but it’s not that simple

A recurring theme on this blog is the relationship between mathematics and reality. It started with the Pythagoreans (in Western philosophy) and was famously elaborated upon by Plato. I also think it’s the key element of Kant’s a priori category in his marriage of analytical philosophy and empiricism, though it’s rarely articulated that way.
 
I not-so-recently wrote a post about the tendency to reify mathematical objects into physical objects, and some may validly claim that I am guilty of that. In particular, I found a passage by Freeman Dyson who warns specifically about doing that with Schrodinger’s wave function (Ψ, the Greek letter, psi, pronounced sy). The point is that psi is one of the most fundamental concepts in QM (quantum mechanics), and is famous for the fact that it has never been observed, and specifically can’t be, even in principle. This is related to the equally famous ‘measurement problem’, whereby a quantum event becomes observable, and I would say, becomes ‘classical’, as in classical physics. My argument is that this is because Ψ only exists in the future of whoever (or whatever) is going to observe it (or interact with it). By expressing it specifically in those terms (of an observer), it doesn’t contradict relativity theory, quantum entanglement notwithstanding (another topic).
 
Some argue, like Carlo Rovelli (who knows a lot more about this topic than me), that Schrodinger’s equation and the concept of a wave function has led QM astray, arguing that if we’d just stuck with Heisenberg’s matrices, there wouldn’t have been a problem. Schrodinger himself demonstrated that his wave function approach and Heisenberg’s matrix approach are mathematically equivalent. And this is why we have so many ‘interpretations’ of QM, because they can’t be mathematically delineated. It’s the same with Feynman’s QED and Schwinger’s QFT, which Dyson showed were mathematically equivalent, along with Tomanaga’s approach, which got them all a Nobel prize, except Dyson.
 
As I pointed out on another post, physics is really just mathematical models of reality, and some are more accurate and valid than others. In fact, some have turned out to be completely wrong and misleading, like Ptolemy’s Earth-centric model of the solar system. So Rovelli could be right about the wave function. Speaking of reifying mathematical entities into physical reality, I had an online discussion with Qld Uni physicist, Mark John Fernee, who takes it a lot further than I do, claiming that 3 dimensional space (or 4 dimensional spacetime) is a mathematical abstraction. Yet, I think there really are 3 dimensions of space, because the number of dimensions affects the physics in ways that would be catastrophic in another hypothetical universe (refer John Barrow’s The Constants of Nature). So it’s more than an abstraction. This was a key point of difference I had with Fernee (you can read about it here).
 
All of this is really a preamble, because I think the most demonstrable and arguably most consequential example of the link between mathematics and reality is chaos theory, and it doesn’t involve reification. Having said that, this again led to a point of disagreement between myself and Fermee, but I’ll put that to one side for the moment, so as not to confuse you.
 
A lot of people don’t know that chaos theory started out as purely mathematical, largely due to one man, Henri Poincare. The thing about physical chaotic phenomena is that they are theoretically deterministic yet unpredictable simply because the initial conditions of a specific event can’t be ‘physically’ determined. Now some physicists will tell you that this is a physical limitation of our ability to ‘measure’ the initial conditions, and infer that if we could, it would be ‘problem solved’. Only it wouldn’t, because all chaotic phenomena have a ‘horizon’ beyond which it’s impossible to make accurate predictions, which is why weather predictions can’t go reliably beyond 10 days while being very accurate over a few. Sabine Hossenfelder explains this very well.
 
But here’s the thing: it’s built into the mathematics of chaos. It’s impossible to calculate the initial conditions because you need to do the calculation to infinite decimal places. Paul Davies gives an excellent description and demonstration in his book, The Cosmic Blueprint. (this was my point-of-contention with Fernee, talking about coin-tosses).
 
As I discussed on another post, infinity is a mathematical concept that appears to have little or no relevance to reality. Perhaps the Universe is infinite in space – it isn’t in time – but if it is, we might never know. Infinity avoids empirical confirmation almost by definition. But I think chaos theory is the exception that proves the rule. The reason we can’t determine the exact initial conditions of a chaotic event, is not just physical but mathematical. As Fernee and others have pointed out, you can manipulate a coin-toss to make it totally predictable, but that just means you’ve turned a chaotic event into a non-chaotic event (after all it’s a human-made phenomenon). But most chaotic events are natural, like the orbits of the planets and biological evolution. The creation of the Earth’s moon was almost certainly a chaotic event, without which complex life would almost certainly never have evolved, so they can be profoundly consequential as well as completely unpredictable.
 

4 comments:

מבול said...

Math sometimes does not connect with reality. True. I was encouraged to take another look at my own blog. The link is in the comment stream of your February post on Simultaneity. The blog is half as long as it was in Feb, and I now have a very specific mathematical thing, the Distributive Law of high school algebra. It doesn’t always work, and that can create problems.

Paul P. Mealing said...

I have to confess I found your blog post difficult to follow. I'm not sure why you need to convert from miles to kilometres, though it's not a big deal.

Regarding the distributive law, it always works from my experience. It's one of the most common mathematical 'devices' in our toolkit. I admit I don't really understand what you've done with the 'double sheep bend' or why it would be a problem. My guess is that you still trace out the length of the rope no matter how many bends it has in it.

You're using the distributive law simply to convert yards to feet - very straightforward. The number of bends in the rope is irrelevant. If you add the length of each bend and multiply by the conversion factor (in this case, 3) the distributive law will work.

מבול said...

Thanks for your feedback. I got rid of the double sheep bend ( it is a knot ). I got rid of the whole foot-yard rope model and stuck with miles-kilometers. The Distributive Law does not work for the Lorentz Transforms. In textbooks or on the web have you ever seen the following?

gamma • ( x′ + vt′ ) = gamma • x′ + gamma • vt′

gamma • ( x – vt ) = gamma • x – gamma • vt

Paul P. Mealing said...

There’s not a problem with the distribution law, it’s simply the way you’re trying to apply it. The γ (gamma) function in the Lorenz transform function is γ = 1/√(1 – v2/c2).

Note that the brackets are behind a square root (√) so, if you want to use the distribution rule, you need to square the factor before you multiply the numbers inside the brackets, then add and take the square root of everything in the brackets. Likewise, if you factorise the v2/c2 outside the brackets you do it in 2 steps.

Step 1: 1/√ v2/c2 (c2/ v2 – 1) Take the factor outside the brackets

Step 2: 1/ v/c √(c2/ v2 – 1) Take the factor outside the square root

Note that when you move the factor outside or inside the square root, you have to either take the square root or square it respectively.