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by j1vms 2344 days ago
The role of this "era" may be in reformulating quantum physics and, separately, general relativity in new ways that make the ideas more accessible to more people, and earlier in their lives. The goal could be to make of modern physics... the new classical physics. That is, we start to let go the crutches we still teach because it is thought that day-to-day life is more readily explained by Newtonian physics. We are now in era where most advances (e.g. smartphones among them) could not exist in their present form without modern physics.

Once more people accept the concepts of modern physics as a way of life (perhaps intuitively?), we will be in fertile territory for any potential new revolution in physics.

3 comments

These theories have a very precise mathematical formulation and very weird unintuitive consequences. If you try to teach them without math, you only keep the weird unintuitive part and it's more unintelligible.

For quantum mechanics you have to know eigenvalues and eigenvectors. This is studies in the first years of the university in a technical career. I'm not sure if it can be teach much earlier.

For Special Relativity you have to know Minkowsky spaces. It's not so difficult, it can be moved to the first years of the university.

For General Relativity you have to know curved spaces. It's not imposible to learn, but you can get a Ph.D. in Math or Physics without studding curved spaces.

Linear algebra (with diagonalization not just using gauss-jordan) could be pushed back to highschool for motivated students, and is in some countries. The coordinate system aspect of special relativity (the origin of time dilation and most of its "weird effects") only requires algebra. General relativity requires the full mechanisms of differential geometry but advances in things like differential forms are pushing this back to the undergraduate level. Overall I would say that it could be done but you would have to leave the unmotivated students behind.
Turtle Geometry gets as far as motion in curved spacetime using code in Logo. Dunno how many high schoolers have ever learned from it, but it's there. (It includes a nice concrete intro to vector algebra earlier, too.)

Re quantum mechanics without many prerequisites, I'm a fan of Feynman's book QED.

We can keep math, but switch to better theories, with plausible explanations.

A kind of Pilot Wave can explain quantum weirdness to layman people with ease.

We can ditch theory relativity and calculate speeds relatively to CMB, which is much easier to understand.

We can ditch Big Bang theory and, instead, accept that light is not immortal, because it ages with time. IMHO, Dipole Repeller and Shapley Attractor are much more attractive and easier to explain than Big Bang.

All three examples you gave have problems or inconsistencies and this is why they are not used. You are being downvoted because you are suggesting teaching formalisms that are known to be insufficient simply because they fulfill your personal criteria of intuitiveness.
We have no perfect theory to explain everything, so it's just tradeoff, exchange of one set of inconsistencies for another set of inconsistencies, but with better intuition. I'm doing it here, in my country.

The problem with current theories is that I understand them when I reading them. It's like piece of complex code or book with complex but boring text, like phonebook. I can follow it, when I read it, but I cannot reproduce it when book is closed.

Can we teach a phonebook to kids? Yep. Is it useful? Nope.

Recently, I did "quantum physics in one picture" experiment. Results are very good: lots of reposts, comments, interest in topic.

But it is not a tradeoff in the cases you picked, rather one set of formalisms has drastically more inconsistencies than the other. E.g. pilot waves: you gain having real numbers (which I personally see little value in) and you gain having a more mechanistic intuitive source of the interference (which is indeed interesting). However describing multiple interacting entangled particles becomes incredibly difficult, describing annihilation and second quantization which is needed for the quantum behavior of fields is not completely done yet, and (what I consider the most substantial problem) you can not work with finite level systems (i.e. anything but a spinless particle in a box is very difficult to describe by pilot wave theory).

In short, pilot waves were a worthwhile avenue of research, but we have seen they are incredibly cumbersome or even insufficient in many quantum mechanics problems.

Yep. Pilot Wave theory is underdeveloped theory, but it helps to develop intuition. Walking droplets are even better for that. IMHO, it's better to use QM to solve QM problems in science, but use walking droplets and Pilot Wave Theory to develop intuition for others. Walking droplets are easy to demonstrate. Double slit experiment can be reproduced in school lab. This way, quantum physics can be taught in school for children of age 12+, so they will be ready to solve much more complex problems when they will be PhD.

Entanglement is hard problem for PWT. Photos of entangled photons[0] are intriguing, because they look similar to behavior of walking droplets in some experiments (see dotwave.org feed). I hope, someone will be able to reproduce entanglement in macro. Currently, my top priority is to reproduce Stern–Gerlach experiment in macro (I suspect that interference between external field and particle wave creates channel, which guides particle into spot, but it better to see it once). Second priority is creation of "photons" in macro. Entanglement will be third. IMHO, all of them require microgravity to reproduce in 3D.

[0]: https://phys.org/news/2019-07-scientists-unveil-first-ever-i...

One problem is that physicists are not interested in lowering the bar to understanding advanced theories. Some say it's all fairly simple once you spend a decade learning some very advanced math. The art of teaching is in making the material more accessible, and at that I dont think much progress has been made.
>physicists are not interested in lowering the bar to understanding advanced theories

That is not true, geometric algebra is an example of a recent pedagogic improvement that is getting a lot of attention. The problem is that physics will never be easy enough for someone who is not prepared to think deeply, because it is one of the few areas where truly new ideas can be found. Virtually every area of learning involves repackaging concepts we have all known from childhood (people's motivations, stories, colors, that kind of thing) in specific ways. Major exceptions are physical tasks like learning to sew or play an insturment, and "esoteric" subjects like math and physics. In all of those cases you cannot learn by casually reading because the neurons in your brain are simply not prepared for it.

> is getting a lot of attention

Not really. People look at it, marvel, and move on.

Worse, they're snidely dismissive.

I've been interested in GA for years now because it helps me visualise and understand otherwise inscrutable mathematics.

Nobody, literally nobody mired in the traditional mathematics of theoretical physics can explain why the Universe is best represented using matrices of complex numbers with constraints on them.

"Shut up and calculate" or some variant is the common response to such probing questions.

More often, it's some variant of "Well, I can understand it, you need to study more.". This is usually stated just politely enough not to be outright insulting. But if you keep asking probing questions, it turns out that they don't really understand either, the "study" didn't help them either. They only got better at pushing the symbols around on paper They're dismissive of such questions because they're too proud to admit their own ignorance.

Geometric Algebra (GA) was my "lightbulb" moment where I finally understood where Dirac matrices, Pauli matrices, and the like come from and why they have the structure that they do.

My logical conclusion was that GA is the far more elegant, clear, understandable mathematical structure that brings a wide range of Physical phenomena under a unified formulation. So clearly, it should be used for pedagogy.

Nobody agrees with that. The attitude is "well, that's nice, but it's mathematically equivalent so there's no benefit." which is just the stupidest thing I've ever heard.

Imagine if you saw a function called "add_num(a,b)" that computed the sum of two integers using the full bit-by-bit adder digital logic circuit simulated in software using boolean logic. Absolutely bonkers, insane code, right? Clearly this ought to be scrubbed from the codebase and replaced with a simple "+" operator, because we're not maniacs. Physicists would argue "no", it's equivalent, it's "working", so shut up, leave it and just move on.

Drives me batty.

If you haven't used it already, Versor[0] is nice to play with. GA is simple enough that even normal-ish teenagers can understand it and produce useful results (my sons are using it in a game they're building). Math isn't even close to my strong suit, but Dual numbers and GA make sense to me, and have made it a lot easier for me to do (seemingly, to me anyway) advanced stuff. :-)

[0] http://versor.mat.ucsb.edu/

I 100% agree with you in all respects — I don't come from a physics background but I hear you loud and clear. I think the 'why' is deep and psycho-historical in nature:

- we're exiting the "industrial" mindset where everyone is the same making the same products, to a wider topology of knowledge and skills (more and wider horizontals, more and bigger verticals, 'average' profiles become 'scattered'). This clearly drives a need to "learn a little bit of a lot of things" even at expert level.

- The walls and denial you expose here is to me but a symptom of the disease that current academia will either have to heal or die of. Seeing how Khan (and thousands of Udemy's after them, indies) changed the landscape, my money is on a major paradigm shift incoming for academia (it's already done, they just don't seem to know it yet as institutions, most of them). Lots and lots of great teachers around the world almost freely sharing incredible hands-on knowledge and insight.

- Some applied domains with dramatic tension of the demand side (lots of positions to fill) don't have the luxury of elitism and massively adopt "pragmatic" approaches especially in learning. Software dev, programming and tech in general is much like that — the "one liner" installs and 1-page "getting started", all the intelligence solely put into making things intelligible and usable is, frankly, quite humbling and inspiring in that field. A very good side of the SV/Cali culture. So, examples of how to proceed next really do exist.

Now when I think back of topics that I hurt my head against for months or years, that a simple 20-minute video could 'unlock'... Why, why do we not make it a staple of "teaching" to at least consider 2-3 angles to make sure everyone's got a fair chance at getting at least 1?

- On the topic of hubris and laziness, this is where physics went astray, imho. Too much hubris and not enough laziness. That was back in the 1980s and it took 40 years to realize, probably 10-20 more to "fix", if ever before we build a new system (see above).

That being said,

> Geometric Algebra (GA) was my "lightbulb" moment where I finally understood where Dirac matrices, Pauli matrices, and the like come from and why they have the structure that they do.

YES, please! Geometric algebra seems like the thing that could blow my mind too. I am very visual, to a fault maybe.

Would you have a 'favorite' resource to share? (book, course, youtube, whatever?)

GA is just "strongly typed" vector algebra. It recognises and embraces the inalienable fact that areas and volumes are fundamentally different to vectors and scalars.

The reason Physics "went wrong" is that in 3D space (only!) the mathematics of areas and vectors is coincidentally isomorphic, so it's possible to cheat and use only vectors and scalars and then everything "works". Similarly, volumes and scalars are easily confused as well, and appear to work fine.

GA has no such restrictions and the same formulas work in all dimensions, including high-dimensional or with degenerate metrics. Problems from classical geometry such as finding tangent lines to circles can be trivially extended to finding tangent hyperplanes to hyperspheres, even for very complex problems.

The formalities of GA force you to include things like the square of the unit pseudoscalar in some physics formulas that were accidentally dropped in the traditional form because in 3D this is just "1" and hence easily overlooked. This makes some formulas weirdly difficult to extend to become relativistic, when in fact the problem was just the "weak typing" of vector algebra.

Vector calculus also inherently requires a basis, which is an easy way to get bogged down in the weeds and get confused by issues with the algebra itself instead of the truly "hard" aspects of the problem.

Generally, the "lightbulb" moment for me was that Geometric Algebra has various subsets that are also closed algebras in their own right. For example, the "even" subset of a 3D GA is isomorphic to Quaternions, and the even subset of a 2D GA is basically the same thing as a Complex number. The various "named matrices" are just other subsets of 3D or 4D GAs. Physicists tend to avoid the full general case and simplify their algebras down to the special subset cases, using the historical names and greek symbols. We have to keep the symbols, you see, because otherwise you wouldn't be able to read 2000-year-old ancient greek texts, or... something.

University Physics is actually a study of the History of Physical Philosophy. The computer science equivalent would be learning about abacuses for the entire first semester, then progressing to mechanical calculators in the second semester, vacuum tubes in the second year, and so forth, only to briefly touch on transistors by the end of the third year. Postgraduate research students would be finally told about modern silicon chips and software development, but by this point they're so used to wiring up breadboards manually that it's too late to teach them how to do anything properly.

Starting with something elegant like pure functional programming in the first year is how I studied Computer Science, but I only found out about Geometric Algebra existing after I graduated Physics. It's nuts.

For background reading:

David Hestenes is one of the few physicists trying to reformulate physics in terms of GA: http://geocalc.clas.asu.edu/html/Overview.html

There's lots of papers around: http://geocalc.clas.asu.edu/html/GAinQM.html

Wikipedia is an okay starting point, but not amazing: https://en.wikipedia.org/wiki/Geometric_algebra

Enkimute's "Ganja.js" online demos are amazing, unfortunately the source was written by one of those crazy maths people who think that terseness helps readability: https://enkimute.github.io/ganja.js/examples/coffeeshop.html...

Real industrial use is few and far between, but at least a few folk have discovered that GA is ideal for robotics. Unfortunately, not everyone got the message, and most robotics software libraries are firmly vector/matrix based and have all the usual issues like numerical instability and gimbal-lock. Fun stuff.

I'm trying to explain quantum physics using single photo[0] (in Ukrainian, but you will get it). It has good adoption among regular people. It based on real physical experiment, just labels are added. BUT scientist are insane when they see it. They argue that quantum physics cannot be explained using picture, because the only true way to explain quantum physics is using mathematics.

[0]: https://scontent.fiev21-2.fna.fbcdn.net/v/t1.0-9/79956387_10...

Also, let’s agree on a consistent interpretation of quantum theory.

As long as we keep teaching the reckless hand-waving that is the Kopenhagen interpretation, we will keep confusing clear-thinking students.

The historical attitude has been, "it doesn't matter, shut up and calculate". There's been quite a bit of push recently to try and nail down exactly what QM means rather than just what it calculates (See: Sean Carroll, etc)