> Let's suppose the aim of the article was indeed to learn PBR from first principles, what would it look like?

Well given the title I at least expected the article to explain or derive things like why and how metals and their alloys have the color (wavelenght-dependent complex index of refraction) that they do, why and how say quartz crystals have different colors, birefringence, fluorescence (makes T-shirts appear extra bright) etc.

And there is no mention of the recording process. Are we simulating good old film with its silver crystals of various sizes? Different film stock is known to have very different looks due to their chemistry.

Or a digital camera sensor with its quantum and thermal noise, bayer filter and a rolling shutter causing those funny-looking propeller pictures?

Not knocking the article, but given the title it fell well short of my expectations going in. That is, I was wondering how on earth anyone had managed to do all that.

> I dislike "Physically Based Rendering: From Theory To Implementation", I personally think that the literate programming approach of the book is way too confusing and disorganized.

Interesting. Personally it's by far the best programming related book I've read. I didn't mind the literal programming, and I loved how it dove fairly deep into the math and physics but also into the details of implementing the math.

The latter being important as there are can be so many gotchas when implementing math.

> Let's suppose the aim of the article was indeed to learn PBR from first principles, what would it look like? Quantum electrodynamics?

Something like that, yes. A truly from-first-principles treatment of photon-surface interactions would involve an extremely deep dive into quantum numbers, molecular orbitals, solid state physics and crystal lattices (which are metals), including a discussion about how electron waves superpose to produce various conduction/valence bands with various band gaps, and then discuss how photons interact with these bands.

no, the first principles could be reduced to the domain that you're working in, which in this case would be non-relativistic physical optics. that is, the description of electromagnetic waves using maxwells equations. these could be considered true first principles for this problem domain.

you don't need to go to quantum physics or general relativity for everything, that would mean that a description from first principles is impossible for any field that doesn't (yet) directly connect there like biology, psychology, you name it. which may be technically correct but clearly not in the spirit of the idea.

in general this article has a quite surface level focus and narrow scope. there isn't even a description how the most common physical rendering primitive ever, a ray of light, is related to electromagnetic waves in mathematical terms. the article is not very mathematical in general which is disappointing.

Sure! And I appreciate the response. I hope I didn't come off as too mean, it can be hard to find that balance in text, especially while criticizing. I really do not want to discourage you, and I think you should keep going. Don't let mistakes stop you.

  > Let's suppose the aim of the article was indeed to learn PBR from first principles, what would it look like?

I think you shouldn't go that route, but the most honest answer I can give is that such a beginning doesn't exist in physics knowledge. You could start with something like String Theory, Supergravity, Loop Quantum Gravity, or some other proposition for a TOE. Physicists are still on the search for first principles.

All this is well beyond my expertise btw, despite having worked in optics. If you want to see some of this complexity, but at a higher level, I'd highly recommend picking up Jackson's Elecrtodynamics book. That's that canonical E&M book for graduate level physics, Griffith's is the canonical version for undergraduate (Junior/Senior year). Both are very well written. I also really like Fowles's "Introduction to Modern Optics", and it is probably somewhere in between (I read it after Griffiths).

I am in full agreement with you that having deep knowledge makes a lot of more shallow topics (and even many other deep topics) far easier to grasp. But depth takes time and it is tricky to get people to follow deep dives. I'm not trying to discourage you here, I actually do encourage going deep, but just noting how this is a tricky line and that's why it is often avoided. Don't just jump into the deepend. Either wade people in or the best option is to lead them in so they don't even recognize they're going deep until they're already there.

  > I dislike <PBR Book>, I personally think that the literate programming approach of the book is way too confusing and disorganized

This is very understandable and I think something you should hone in on and likely where you can make something very successful. But an important thing to note about his SIGGRAPH talk is his audience. His talk is aimed at people who are experts in computer graphics, but likely computer scientists and not physicists. So his audience knows a fair amount of rendering to begin with and can already turn much of what's being said into the code already. But if you listen to it again I think you'll pick up on where he mentions they'll ignore a bunch of things[0]. There's no shame in ignoring some things and working your way forward. I actually like what Hoffman said at 22:25 "and we know that's an error. But we'll live with it for now." That's the mark of good scientific and engineering thinking: acknowledge errors and assumptions, triage, but move forward. A common mistake looks similar, dismissing those errors as inconsequential. That's putting them in the trash rather than tabling for later. Everything is flawed, so the most important thing is keeping track of those flaws, least we have to do extra work to rediscover them.

So, who is your audience?

This is just my opinion, so you have to be the real judge; but I think you should leverage your non-expertise. One of the hard things when teaching is that once you understand something you quickly forget how difficult it was to learn those things. We quickly go from "what the fuck does any of this mean" to "well that's trivial" lol. You referenced Feynman in your blog post and most important thing I learned from him is one of the best tools for learning is teaching (I've given way too many lectures to my poor cat lol). It forces you to answer a lot more questions, ones you normally would table and eventually forget about. But at your stage it means you have an advantage, that the topics you are struggling with and have overcome are much more fresh. When learning things we often learn from multiple sources (you yourself shared overlapping material), and that's because multiple perspectives give us lots of benefits. But at this point, don't try to be a physicist. If you want to work towards that direction, great! If you don't, that's okay too. But let your voice speak from where you are now.

Reading your blog post and poking through others, there's a "you" that's clear in there. Lean into it, because it is good. I like your attention to detail. Like in your Ray Marching post how you just color code everything. Not everyone is going to like that, but I appreciate it and find it very intuitive. I'm a huge fan of color coding equations myself and make heavy use of LaTeX's annotate-equations package when I make slides.

But I think looking at this post in isolation the biggest part to me is that it is unclear where you're going. This is a problem I suffer from a lot in early drafts. An advisor once gave me some great advice that works really well for any formal communication. First, tell "them" what you're going to tell them, then tell them, then tell them what you told them. It's dumb, but it helps. This is your intro, it is your hook. I think there's places for these ideas but early on they almost feel disconnected. This is really hard to get right and way too easy to overthink. I think I can help with a question: "What is your thesis?"/"What is your main goal?" Is it "learn how our human eyes capture light and how our brains interpret it as visual information"? Or is it "Physically based rendering from first principles". Or even "learn how to create physically realistic renderings of various materials." These are not exactly the same thing. When I'm struggling with this problem it is because I have too much to say. So my process is to create a "vomit draft" where I just get all the things out and it's going to be a mess and not in the right order. But once out of my head they are easier to put together and in the right order. After your vomit draft check your alignment. What is most important and what can be saved? What's the most bare bones version of what you need to communicate? Build out of that.

I do really think there's a good blog post in here and I can see a lot of elements that suggest a good series may come. So I do really encourage you to keep going. Look at what people are saying they like and what they dislike. But also make sure to not take them too literally. Sometimes when we complain about one thing we don't know our issue is something else. What I'm saying is don't write someone else's perfect post, write your post, but find best how to communicate what you want. I know I've said a lot, and I haven't exactly answered all your questions, but I hope this helps.

[0] There's a side note here that I think is actually more important than it appears. But the thing is that there's a weird relationship between computation and accuracy. I like to explain this looking at a Taylor Series as an example. Our first order approximation is usually easy to calculate and can usually get us a pretty good approximation (not always true btw). Usually much more than 50% accurate. Second order is much more computationally intensive and it'll significantly increase your accuracy but not as much as before. The thing is accuracy converges much like a log-like curve (or S-curve) while computation increases exponentially. So you need to make these trade-offs between computational feasibility and accuracy. The most important part is keeping track of your error. Now, the universe itself is simple and the computational requirements for it are lower than it takes us to simulate but there's a much deeper conversation about this that revolves around emergence. (The "way too short" version is there's islands of computational reducibility) But the main point here is this is why you should typically avoid going too low quickly, because you end up introducing too much complexity all at once and the simplicity of it all is masked by this complexity.

LOL to be honest I'm more scared of the people that it doesn't happen to. At first I feared them because I thought they knew so much more and it meant I was so far behind. But later I feared them because I recognized we were at not too dissimilar levels and the main difference was recognizing how far left we have to go.

I don't fear the man who knows more than me, I admire them and only have something to gain by admitting my ignorance to them. But I do fear the man who believes he knows more while in reality he doesn't. Nothing productive comes from them as they don't even recognize the journey we are both on.

  > How much more “first principles” could this article be!?

I think you've answered your own question and demonstrated my point. See my third sentence. The notion of "more 'first principles'" is like asking who's before the first person in line. If there's more people in front, then they aren't the first person in line and if there aren't, well you're right, how can you be more first? But I think we both know this isn't the start of the line...

As to your actual question(?) of "how more fundamental can it be"? Well, the answer is a lot. They barely scratched E&M theory. I specifically mentioned that even a undergraduate in physics would be exposed to much more fundamental aspects. Likely even before their junior year.

But if you're asking "how much more fundamental should* it be" well most of my comment is arguing that it should not be. I argued that it generally isn't a good idea to start from first principles, and I'll even argue that it probably isn't a good idea to start there even if they are in quotes.

Agreed - OP's criticism is way over the top.

This blog post is very much "first principles" for the layperson. It's not the level of "first principles" that a trained physicist would expect (where there would be rigorous derivations involving dielectric functions and the like), but it's great for a layperson who wants to understand why the world looks the way it does.

Idk, empirical observations? A theory is certainly not a principle.

The roughness reflection slider thingy is trivial to generate with any LLM, however you should try generating the BRDF illustration with:

- 3d primitives (arrows, hemisphere)

- billboarded text rendering

- mouse interaction/canvas rendering that works for multiple scenes

It might be possible to vibe code but you’ll hit a wall of complexity really quick

I think >90% of the time I hear the phrase "first principles" mentioned I'm safe in expecting something that is very high level to follow. I'm glad nerds have (kinda) been pushed into celebrity status but I also think there's a lot of cargo culting that has followed. Unsurprising I guess, since one is much easier than the other. I just wish there was more pushback, especially in tech (not because the only abuser of this, but we're definitely the ones with the most weight)

  > you can get far more mileage out of the naive models than people want to admit.

All models are wrong, but some models are useful, right? I'm a big fan of this phrase so much because I think it helps us remember that it's okay to be wrong.

I feel like the biggest problem of first principles is that this is almost never where you start. Rather it is something you work towards. Where it then becomes an iterative process expanding/extrapolating out, then coming back in and refining. Low level knowledge is so beneficial, but also very difficult to obtain. It's even more difficult to see how much room is below you without ever having gone down.

Yeah he abuses a lot of phrases... He does provide a master class on psuedointellectualism though. Drops enough vernacular that layman think he's smart and even enough that experts might think they're in good company if they don't pay too close attention. But I think the biggest clue that it's fake is how dismissive he is of nuance and detail. It's such a classic defense from psuedointellectuals because they know if they venture into depth then the gig is up. Meanwhile, look at any two nerds arguing. It's always nuanced and over minute things that they'll always insist are very important (because often it is, but only at that level).

Lol apparently reasoning by analogy is first principles to him -- see human drivers using only vision therefore no lidar somehow being "first principles".

Can confirm, latest Firefox on S24 doesn't render the interactive elements. Chrome does, however, and it's a beautiful article.

Seems fine on Firefox on Mac

How long did it take you to write that code / this article?

I'm a big fan of zero-dependency code (or at the very least with any dependency vendored/hosted locally), it means this page will still work and look as it does today in 25 years time.

I don't know if TS runs natively in browsers yet, but v8 / NodeJS does support it (just strips off Typescript specific tokens).

Love it! For typescript, esbuild has been my favorite tool for turning typescript into browser-readable js, and then I check type errors separately using the ide plugin.

Interesting link, thank you!

It looks like a good model for lower incident angles but begins to diverse at higher angles. There's also one huge caveat - it relates the GGX model to real world ground glass. Obviously it's important to compare like to like. However, very few materials in the real world are ground glass.

Looking around my surroundings, I see painted drywall, wood, paper, plastics, and textiles. It would seemingly be a mistake to assume each of these materials behaved optically like ground glass. I hope that similar measurements are carried out on other materials.