# The Essence of Lagrange Multipliers

In which we attempt to better understand the classic multivariable calculus optimization problem.

June 10, 2024

In which we attempt to better understand the classic multivariable calculus optimization problem.

March 12, 2024

Here’s a dubious idea I had while playing with using delta functions to perform surface integrals. Also includes a bunch of cool tricks with delta functions, plus some exterior algebra tricks that I’m about 70% sure about. Please do not expect anything approaching rigor.

February 28, 2024

Normally I haunt comment sections and leave replies on discussions about Geometric Algebra: “Wait, wait, although GA is clearly onto something it’s not as good as those people say, there’s something wrong with it; what you probably want is the wedge product on its own!” Which is not especially productive and probably a bit unhinged. So, today I’m going to actually make those points in one central place that I can link to instead.

To be clear, I’m not opposed to GA per se. What I (and, I think, a lot of other people) have a problem with is that the subject is pretty clearly flawed… and that the culture around it does not seem to realize this or be interested in addressing those flaws.

In particular, **Hestenes’ Geometric Product is not an intuitive operation that we should be basing all of geometry on**. And GA’s tendency to do so and then say “yes, this is *the* way that geometry should be done” (with a sort of religious zeal) is problematic and offputting. It’s also just ineffective: treating certain models as if they are somehow canonical and obvious and perfect is wrong, mathematically and socially, and it puts people off right from the start. There probably is a place for the geometric/Clifford product in a grand theory of geometry, but it’s not “front-and-center” like GA treats it today, and as a result the theory is a lot less compelling than it could be.

October 24, 2023

There’s an identity in electromagnetism which has been bugging me since college.

Gauss’s law says that the divergence of the electric field is equivalent to the charge distribution: \(\del \cdot \b{E} = \rho\). But in order to use this for a point charge—which is the most basic example in the subject!—we already don’t have the mathematical objects we need to calculate the divergence on the left or to represent the charge distribution on the right.

After all, the field of a point charge has to be \(\b{E} = q \hat{\b{r}}/4 \pi r^2\), and since its charge should be concentrated at a point it has to be a delta function: \(\del \cdot (q \hat{\b{r}}/4 \pi r^2) = q \delta(\b{x})\). In your multivariable-calculus-based E&M class you might mention this briefly, at best. Yet it is… kinda weird? And important? It feels like it should make a basic fact that lives inside of a larger intuitive framework of divergences and delta functions and everything else.

October 14, 2023

Here’s some stuff about delta functions I keep needing to remember, including:

- the best way to define them
- how \(\delta(x)/x = - \delta'(x)\)
- possible interpretations of \(x \delta(x)\)
- some discussion of the \(\delta(g(x))\) rule
- how \(\delta(x)\) works in curvilinear coordinates.

September 25, 2023

For a generic linear equation like \(ax = b\) the solutions, if there are any, seem to always be of the form

\[x = a_{\parallel}^{-1} (b) + a_{\perp}^{-1} (0)\]regardless of whether \(a\) is “invertible”. Here \(a_{\parallel}^{-1}\) is a sort of “parallel inverse”, in some cases called the “pseudoinverse”, which is the invertible part of \(a\). \(a_{\perp}^{-1}\) is the “orthogonal inverse”, called either the nullspace or kernel of \(a\) depending what field you’re in, but either way it’s the objects for which \(ax = 0\). Clearly \(ax = a (a_{\parallel}^{-1} (b) + a_{\perp}^{-1} (0)) = a a_{\parallel}^{-1} (b)\), and that’s the solution if one exists.

This pattern shows up over and over in different fields, but I’ve never seen it really discussed as a general phenomenon. But really, it makes sense: why shouldn’t *any* operator be invertible, as long as you are willing to have the inverse (a) live in some larger space of objects and (b) possibly become multi-valued?

Here are some examples. Afterwards I’ll describe how this phenomenon gestures towards a general way of dividing by zero.

May 1, 2023

What "science" means at tech companies.

April 25, 2023

Look, a list of simple things that you and your colleagues should know to avoid, but which you will still do by accident from time-to-time and eventually spend months of your life, in total, tracking down.

Don’t worry, these are all a bit more interesting than React 101 stuff like “don’t write conditional hooks”.

October 12, 2022

Many more words about React.js. Previously: The Zen of React.

As you may know: in 2018ish, the React team added “hooks” to the library. From the beginning hooks have been presented as a new, better thing which would gradually take the place of class components. This was very strange and controversial at the time, and it still is, judging by the comment sections complaining about it every other week.

Common frustrations about hooks: they’re confusing, they’re clunky, they’re unnecessary, they’re difficult to use correctly. All of these are true. But I think hooks are great and that they’re the future of programming. This article, hopefully one of a series, attempts to get you to agree with that statement. It’s about what hooks are and why they are how they are.

In particular I think it really helps to see a hook written out as a simple programming exercise, in order to understand exactly how they solve the problem that they are trying to solve. When you do this, and understand what that problem is, you can see that, while hooks aren’t even a great solution to that problem, they are at least better than classes, and therefore they are a step in the right direction.

September 17, 2022

I am hoping to write a series of posts about React.js: why it’s great, why hooks are great but also confusing, and then maybe what all is wrong with it and what can be done. These are largely perspectives I came to hold while working as a frontend developer at Dropbox for the last few years (I quit earlier this year, though, for… reasons.)

July 3, 2022

For posterity: here’s a little Python script I wrote that takes an image file and pads it with white space (or whatever color) to make it have a certain aspect ratio.

October 31, 2021

Seriously it’s very bad right now. Right?

October 15, 2020

More exterior algebra notes. This is a reference for (almost) all of the many operations that I am aware of in the subject. I will make a point of giving explicit algorithms and an explicit example of each, in the lowest dimension that can still be usefully illustrative.

August 10, 2020

Rapid-fire non-rigorous intuitions for calculus on complex numbers. Not an introduction, but if you find/found the subject hopelessly confusing, this should help.

July 24, 2020

QM is harder to understand that it needs to be because people are reluctant to write down explicit examples of all of the objects that you talk about. They’ll write a whole textbook about operators and observables and their eigenvalues when they act on the wave function, but they won’t just *write down an example of a wave function that has those properties*.

This is my attempt at fixing that. I’m trying to learn QFT and it helps to have the prerequisites compressed into the simplest possible representation. It also helps me to write everything down in a compressed form so I can reference it more easily.

This will make no sense if you don’t already have a good understanding of quantum mechanics. Also it might be kinda wrong-ish, but I bet it will help.

Conventions: \(c = 1\), \(g_{\mu \nu} = \text{diag}(+, -, -, -)\). I like to write \(S_{\b{x}}\) for \(\nabla S\).

December 22, 2019

The so-called Born Rule of quantum mechanics says that if a system is in a state \(\alpha \| 0 \> + \beta \| 1 \>\), upon ‘measurement’ (in which we entangle with one or the other outcome), we measure the eigenvalue associated with the state \(\| 0 \>\) with probability

\[P[0] = \| \alpha \|^2\]The Born Rule is normally included as an additional postulate in QM, which is somewhat unsatisfying. Or at least, it is apparently difficult to justify, given that I’ve read a bunch of attempts, each of which talks about how there haven’t been any other satisfactory attempts.

Anyway here’s an argument I came up with which seems somewhat compelling. It argues that the Born Rule can emerge from interference if you assume that every *measurement* of a probability that you’re exposed to (which I guess is a Many-Worlds-ish idea) is assigned a random, uncorrelated phase.

September 15, 2019

Most of our descriptions of how our brains work are fundamentally *vague*. We speak of our brains performing verbs like “think”, “realize”, “forget”, or “hope” but we aren’t talking about what’s going on mechanically to result in those qualities.

Sure, these can all be assigned truth values, in the sense that if everyone generally agrees that someone ‘realized’ something, we might define their brain to have performed the objective act of ‘realization’. But this gives no *technical* understanding of what the process of realization is – beyond, perhaps, some hand-wavey story about connections being bridged between neurons.

So, sometime in the last few years the English-speaking Internet became aware of the condition called aphantasia. Aphantasia is when a person is unable to picture images in their thoughts – they don’t have a “mind’s eye” at all.

This is interesting because, in contrast to the above, aphantasia is a concrete description of how the brain works. Some people see an image in their head when they draw or recall something; others don’t. Their brains work in materially different ways. I would have no idea how to figure out if two people “realize” something via different mechanisms, but I can be sure that two people’s brains operate differently, if one sees pictures and the others don’t.

March 2, 2019

More on simplexes in oriented projective geometry (OPG), since they are connected to everything else. See the previous post for details on OPG.

February 23, 2019

In the previous post in this series, I looked at how some operations related to exterior algebra (wedge / ‘join’, ‘meet’, interior product, Hodge Star, geometric product) roughly correspond to set operations (union, intersection, subtraction, complement, symmetric difference), but the analogy wasn’t very good. Exterior algebra isn’t *exactly* linearized set algebra. So what is it?

Well, I found another subject that’s a much closer fit: oriented projective geometry (henceforth ‘OPG’).

February 13, 2019

*Vector spaces are assumed to be finite-dimensional and over \(\bb{R}\). The grade of a multivector \(\alpha\) will be written \(\| \alpha \|\), while its magnitude will be written \(\Vert \alpha \Vert\). Bold letters like \(\b{u}\) will refer to (grade-1) vectors, while Greek letters like \(\alpha\) refer to arbitrary multivectors with grade \(\| \alpha \|\).*

You may have noticed that the behavior of the wedge product on pure multivectors is to append them as lists: \(\b{wx} \^ \b{yz} = \b{wxyz}\), where some signs come in if you’d rather have the terms in a different order. This could also be interpreted as taking their union as sets. Either way, \(\^\) seems to act like a union or concatenation operation combined with a bonus antisymmetrization step which has the effect of making duplicate terms like \(\b{x \^ x}\) vanish.

January 27, 2019

*Vector spaces are assumed to be finite-dimensional and over \(\bb{R}\). The grade of a multivector \(\alpha\) will be written \(\| \alpha \|\), while its magnitude will be written \(\Vert \alpha \Vert\). Bold letters like \(\b{u}\) will refer to (grade-1) vectors, while Greek letters like \(\alpha\) refer to arbitrary multivectors with grade \(\| \alpha \|\).*

More notes on exterior algebra. This time, the interior product \(\alpha \cdot \beta\), with a lot more concrete intuition than you’ll see anywhere else, but still not enough.

I am not the only person who has had trouble figuring out what the interior product is for. This is what I have so far…

January 26, 2019

December 28, 2018

Here is a survey of understandings on each of the main types of Taylor series:

- single-variable
- multivariable \(\bb{R}^n \ra \bb{R}\)
- multivariable \(\bb{R}^n \ra \bb{R}^m\)
- complex \(\bb{C} \ra \bb{C}\)

I thought it would be useful to have everything I know about these written down in one place.

Particularly, I don’t want to have to remember the difference between all the different flavors of Taylor series, so I find it helpful to just cast them all into the same form, which is possible because they’re all the same thing (seriously why aren’t they taught this way?).

These notes are for crystallizing everything when you already have a partial understanding of what’s going on. I’m going to ignore discussions of convergence so that more ground can be covered and because I don’t really care about it for the purposes of intuition.

November 1, 2018

You may have seen that Youtube video by Numberphile that circulated the social media world a few years ago. It showed an ‘astounding’ mathematical result:

\[1+2+3+4+5+\ldots = -\frac{1}{12}\](quote: “the answer to this sum is, remarkably, minus a twelfth”)

Then they tell you that this result is used in many areas of physics, and show you a page of a string theory textbook (*oooo*) that states it as a theorem.

The video caused a bit of an uproar at the time, since it was many people’s first introduction to the (rather outrageous) idea and they had all sorts of (very reasonable) objections.

I’m interested in talking about this because: I think it’s important to think about how to deal with experts telling you something that seems insane, and this is a nice microcosm for that problem.

Because, well, the world of mathematics seems to have been irresponsible here. It’s fine to get excited about strange mathematical results. But it’s not fine to present something that requires a lot of asterixes and disclaimers as simply “true”. The equation is *true* only in the sense that if you subtly change the meanings of lots of symbols, it can be shown to become true. But that’s not the same thing as quotidian, useful, everyday truth. And now that this is ‘out’, as it were, we have to figure out how to cope with it. Is it true? False? Something else? Let’s discuss.

October 9, 2018

*(Not intended for any particular audience. Mostly I just wanted to write down these derivations in a presentable way because I haven’t seen them from this direction before.)*

*(Vector spaces are assumed to be finite-dimensional and over \(\bb{R}\))*

Exterior algebra is obviously useful any time you’re anywhere near a cross product or determinant. I want to show how it also comes with an inner product which can make certain formulas in the world of vectors and matrices vastly easier to prove.

October 8, 2018

*(This is not really an intro to the subject. I don’t have an audience in mind for this. I’ve written my notes out in an expository style because it helps me retain what I study.)*

*(Vector spaces are assumed to be finite-dimensional and over \(\bb{R}\) with the standard inner product unless otherwise noted.)*

Exterior algebra (also known as ‘multilinear algebra’, which is arguably the better name) is an obscure and technical subject. It’s used in certain fields of mathematics, primarily abstract algebra and differential geometry, and it comes up a lot in physics, often in disguise. I think it ought to be *far* more widely studied, because it turns out to take a lot of the mysteriousness out of the otherwise technical and tedious subject of linear algebra. But most of the places it turns up it is very obfuscated. So my aim is to study exterior algebra and do some ‘refactoring’: to make it more explicit, so it seems like a subject worth studying in its own right.

In general I’m drawn to whatever makes computation and intuition simple, and this is it. In college I learned about determinants and matrix inverses and never really understood how they work; they were impressive constructions that I memorized and then mostly forgot. Exterior Algebra turns out to make them into simple intuitive procedures that you could rederive whenever you wanted.

August 6, 2018

Here’s a summary of the concept of oriented area and the “shoelace formula”, and some equations I found while playing around with it which are not novel. I wanted to write this article because I think the concept deserves to be better popularized, and it is useful to me to have my own reference on the subject.

Several resources I have found on the subject, including Wikipedia, all cite a 1959 text entitled *Computation of Areas of Oriented Figures* by A.M. Lopshits, which was originally printed in Russian and translated to English by Massalski and Mills, but is apaprently not available online. I did find a copy via university library, so I thought I would summarize its contents in the process in order to make them available to a casual Internet reader.

I also took this chance to practice making beautiful math diagrams. Which went okay, but god is it ever not worth the effort.

June 15, 2018

A friend is writing her master’s thesis in a subfield where data is typically summarized using *geometric* statistics: geometric means (GMs) and geometric standard deviations (GSDs), and sometimes even geometric standard errors (GSEs), whatever those are. Oh and occasionally also ‘geometric confidence intervals’ and ‘geometric interquartile ranges’.

…Most of which are (a) not something anyone really has intuition for and (b) surprisingly hard to find references for online, compared to regular ‘arithmetic’ statistics.

I was trying to help her understand these, but it took a lot of work to find easily-readable references online, so I wanted to write down what I figured out.

(later edit: I wish I had saved the sources though.)

April 19, 2018

A rant.

My bike was stolen out of the backyard last night, so I’m feeling a little more aggravated by everything than usual.

This has had the effect of reminding me of a recurring sensation in my life as a software developer: that dealing with technology can be a *fundamentally miserable experience*, and that the skill of being ‘good’ at software is often mostly the same skill as *being able to take a lot of crap from faceless, abusive machines in ways that you feel powerless to do anything about.*

So while I’m all for the “let’s teach everybody to code!” movement, I do sometimes wish we’d stop writing yet another Learn Machine Learning With Python Tutorial, or whatever, and just make maybe take some time to work on making everything the world around us better in little incremental ways, by making what we’ve already got *suck* less, for ourselves and for all the newcomers and for just everyone, so we can have less stress and more peace in our lives.

Basically some days I can’t honestly tell anyone they should get into this, when on a good day you get to slowly hack your way through bullshit and on a bad day you might just succumb and give up.

March 30, 2018

Some thoughts on Taylor series.

We can often write a differentiable function \(f(x)\) as a Taylor series around a point \(x\), approximating it in terms of its derivatives at that point:

\[f(x+a) = \sum_{0}^{\infty} \frac{a^{n} f^{(n)}(x) }{n!}\]And, under certain conditions, this series will converge exactly to the values of the function at nearby points.

February 23, 2018

*(Only interesting if you already know some things about information theory, probably)*

*(Disclaimer: Notes. Don’t trust me, I’m not, like, a mathematician.)*

I have been reviewing concepts from Information Theory this week, and I’ve realized that I never quite really understood what (Shannon) Entropy was all about.

Specifically: I have finally understood how entropy is *not* a property of probability distributions per se, but a property of streams of information. When we talk about ‘the entropy of a probability distribution’, we’re implicitly talking about the stream of information produced by sampling from that distribution. Some of the equations make a lot more sense when you keep this in mind.

January 2, 2018

In 2018 I am going to write, because I don’t remember anything unless I write it out for myself.

Update: cool, I actually did some writing in 2018.