Four or five thoughts on scientific writing

18 August 2016

2565 words

A few days ago I handed in my bachelor’s thesis in physics and I had a few thoughts while writing it. Some of these thoughts only apply to literature that features a lot of mathematical equations, but some apply to all academic writing, or all writing in general.

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“Cite before you write” is difficult

I have the impression that a common mistake for undergrads writing their first scientific paper is that they start writing and only insert citations later. This takes a lot of time because they have to go through the whole text and remember where they read each argument they mention. Additionally, it leads to worse quality citations because many students will get lazy and only insert citations until their supervisors stop complaining.

Like anyone who thinks they’re smart, I figured I wouldn’t make this mistake when I’m writing my bachelor’s thesis. But there I was, multiple pages written, a rough outline of the entire document finished, and I still had approximately zero citations in the text.

This surprised me because, whenever I research a topic online and take notes about it for myself, I never fail to cite sources. I gather links to sources, put them at the bottom of a markdown file, and write my notes around those links.

Why did I do it wrong in the context of my thesis? The problem wasn’t that I didn’t know citing as I write would be a good idea – I’d explicitly planned to do it. My best guess is that there was too much friction in the process. In the markdown example, all I have to do is copy the link to the source, paste it into the document, and put some identifier for the link at the beginning of the line (e.g. [example]: http://example.com "Optional title"). To get a proper citation into BibTeX, I have to find the paper on Google Scholar, click “Cite”, click “BibTeX”, copy the content of the entry, open the bibliography file, paste it in, change the identifier if it looks gross, go back to my document, and enter \cite{identifier}. It’s no surprise that people get lazy if that’s what they have to do for each source.

A solution to this problem is using citation management applications. There is, for example, Zotero, which can store all your papers in a handy library. It even gives you a button for your browser to quickly add new references without digging through cite-menus on Google Scholar. Using such an app, you just add every paper you look at into your library and, from there, export your bibliography file. Then you can copy or drag the citations from your Zotero library without having to think about the details.

I find it surprising that I hadn’t heard much or thought about them until a few weeks before my deadline.

On formal tone

I was surprised to see how much the tone of scientific papers differs from that of textbooks. So far I’d only ever read textbooks, and a lot of why I was excited to write my bachelor’s thesis was that I liked the styles of some textbooks. Authors like David Griffiths or David Halliday¹ write in a way that is both whimsical and easy to understand.

Here are some fun examples:

Before leaving our review of the notion of temperature, we should dispel the popular misconception that high temperature necessarily means a lot of heat. People are usually amazed to learn that the electron temperature inside a fluorescent light bulb is about 20,000°K. “My, it doesn’t feel that hot!”²

I would be delinquent if I failed to mention the archaic nomenclature for atomic states, because all chemists and most physicists use it (and the people who make up the Graduate Record Exam love this kind of thing). For reasons known best to nineteenth century spectroscopists, $l=0$ is called s (“sharp”), $l=1$ is p (for “principal”), $l=2$ is d (“diffuse”), and $l=3$ is f (“fundamental”); after that I guess they ran out of imagination, because now it continues alphabetically (g, h, i, but skip j—just to be utterly perverse, k, l, etc.). The shells themselves are assigned equally arbitrary nicknames, starting (don’t ask me why) with K: The K shell is $n=1$, the L shell is $n=2$, M is $n=3$, and so on (at least they’re in alphabetical order).³

And then I looked at articles and didn’t find a single joke in them! In fact the more papers I read, the more it felt like I was reading an entirely new language. Sentences are much longer than in non-academic writing. Most authors avoid using contractions (e.g. “can’t”, “isn’t”). Nobody puts any emotion into their writing, eliminating all traces of informality from the text. To say something “ran out” as in the second example above would probably already be too informal. It seems uncommon to add analogies to complicated explanations to make them intuitively easier to understand.

In a TED talk, linguist John McWhorter proposes that texting doesn’t harm teenagers’ writing skills because they subconsciously treat it like a form of speech rather than writing. Since writing a text message doesn’t feel like composing an essay, using lol and rofl won’t destroy the child’s ability to spell. I suspect that this compartmentalization of different means of communication is part of why formality is so important in academic writing: “Normal” written language can be imprecise but still easy to understand, if the reader and writer have shared background knowledge. Academic papers usually communicate complicated ideas where precision is important. It’s not hard to imagine that funny metaphors can easily lead to misunderstandings. So, while I don’t see how contractions would cause any problems on their own, the rule “be careful with funny metaphores” is harder to follow than “nothing even remotely informal ever”. If following either rule will lead to a well-argued paper, the latter is more efficient. Similarly, if it’s forbidden to write in terms of analogies, it’ll be easier not to be tempted to think in terms of bad analogies.

So simply writing in a way that feels very formal and fancy is a good way to make sure one’s writing stays precise without having to think about it too much.

But (1), on the other hand, “regular language” is a good tool for communication, too. We’ve all been trained to speak and write from very early on, and if you’re forced to write an basically a different language, it can slow down your thoughts and make you less efficient. Contractions aren’t “formal”, but they can make sentences more fluent and easy-to-parse. And analogies can offer valuable support for complicated explanations to steer the reader’s mind in the right direction such that they have an easier time following the text.

But (2), using formal language is not a fool-proof way to make sure all of your thinking is precise. I recently read a paper that contained the sentence, “At the inner boundary there are basically two types of reasonable boundary conditions: …” Saying words like “basically”, or “essentially”, or “reasonable” may sound fancy, but doesn’t actually explain anything.

But (3), using formal language can actually be harmful for clarity. You know how saying “I did X” sounds informal? A lot of the time, authors use “We did X” instead. This strikes me as a weird custom for papers that only have one author, but it’s still reasonably clear what the author means. It gets problematic when they start using the passive voice to sound fancy. Using the passive voice is almost always a bad idea. The reader needs to know who does what. “The stress tensor is given by …” Is that the definition? Does this follow from something? Are we assuming this? Using the passive voice is an easy way to accidentally leave out crucial information that the readers then have to figure out themselves.

Nobody ever quotes anything

I was wondering why there were so few quotations in the papers I read. Searching the internet revealed arguments like the following:

Unlike other styles of writing, scientific writing rarely includes direct quotations. Why?

• Quotations usually detract from the point you want to communicate.
• Quotations do not reflect original thinking.

Inexperienced writers may be tempted to quote, especially when they don’t understand the content. However, the writer who understands her subject can always find a way to paraphrase from a research article without losing the intended meaning – and paraphrasing shows that the writer knows what she is talking about.⁴

I get that you want to make sure the author understands the concepts they’re writing about and didn’t just copy–paste stuff from other papers without having read them first. But even so, it strikes me as wildly inefficient for them to paraphrase the same thoughts over and over in every paper they write on the same topic. You wouldn’t believe how many times I’ve read about the viscosity prescription being the big unsolved problem of accretion disc physics.

If you’re literally repeating what someone else already said, there is not much value in trying to come up with a new way to phrase it, unless you have a great new explanation. If everyone just quoted one really good explanation, they wouldn’t have to waste their time rewriting the same information and could instead spend their time doing more research.

Next, if you paraphrase everything you read in a paper and then just say, “see <Some paper>”, it can be hard for the reader to find the exact spot you’re referencing. Also, the reader has to have a copy of each paper you’re citing on hand, and find the statement you’re paraphrasing to check whether you actually understood the source material correctly. This is not optimal. On the web, this can be easily solved by putting a quotation of the relevant section, plus a reference to the original article, into a footnote. Then the reader can immediately see the sentence/paragraph what you’re referring to without having to seek out the source article. I can imagine the reason that this hasn’t caught on yet is that it doesn’t work well on paper. If you only have a limited amount of space, you don’t want to dilute your own text with foreign material – and, contrary to the web, footnotes must always take up physical space on the page.

But yeah, I’m always happy when I look at how Gwern cites sources using enormous footnotes.

TeXmacs is better than LaTeX (even though it has bugs)

TeXmacs is a WYSIWYG text editor that makes it easy to write sort of LaTeX-looking documents without the hassle of having to look at the source code and output files separately. What sets TeXmacs apart from other word processors is that you still get a lot of the benefits you expect from plain text editors. For example, one thing I like about writing in markdown is that I can see formatting control characters, like * for denoting the start and end of italics. Most WYSIWYG editors only show you the currently selected formatting options in a toolbar somewhere, which leads to the classic “Write an italicized word, write a normal word, delete the normal word, retype the normal word, argh now the new word is italicized too”-problem. In TeXmacs, when the cursor is in a region with formatting applied, it draws a little box around that region, so you can always tell what’s happening. Typesetting formulas in TeXmacs is the most pleasant experience I have ever had in my entire life and I never want to go back to writing LaTeX equations.

Unfortunately, when I started writing, I discovered bugs that occasionally made TeXmacs freeze up and I had to restart it. It seemed relatively dangerous to make myself dependent on a program that sometimes freezes, but, in retrospect, I should’ve stuck with it. I switched to LaTeX and it felt like placing individual atoms of ink on the paper. This decision probably cost me a lot of time and writing quality, since I had less time for editing.

I tried talking to people at my university about TeXmacs and most of them said, “I’m pretty happy with LaTeX,” or, “I’m pretty fast at typing LaTeX,” but once you see how fast you can really be, you will not want to go back.

My hope is that if many people use TeXmacs, it’ll get more code contributions and become less buggy, because that’s supposedly how open-source works.

Putting each sentence on a single line in your text file is a good idea

Say you use LaTeX for your writing anyway, or you write in markdown. There are two common ways to write plain-text documents:

1. One line per paragraph. Each paragraph is contained in a single “line” of text, followed by an empty line. Most text editors wrap lines dynamically, such that these one-line paragraphs just look like normal paragraphs.

2. Hard wrapped lines. Some people like to use old text editors like Vim. Vim isn’t very good at handling long lines that have to be displayed on multiple lines on the screen. So, instead of putting an entire paragraph into a single line, Vim users configure their text editor to insert line breaks after, e.g., 80 characters. This makes the files nice to look at in old text editors, but it makes editing more complicated: Whenever you change something at the beginning of a paragraph, the line breaks in the rest of the paragraph may no longer be in appropriate places, so you have to reformat the entire paragraph.

After switching to LaTeX, I wanted to try a technique I read about a few years back: Inserting a hard line break after each sentence or sub-clause. This sounds like a strange idea because it makes the right edge of your text look all jaggedy, but it is actually really useful.

LaTeX and markdown ignore single line breaks in the text, so the output you create is going to look the same as when you use methods 1 or 2. But if you place line breaks after periods, or important commas, it suddenly becomes much easier to delete, edit, and re-order individual sentences. Another nice feature is that you can easily see when you’re accidentally starting each sentence with the same words. And your version control system is going to love keeping track of your writing because version control systems natively operate on lines and not sentences. And you can now see how long your sentences are, because they’re visually separated from each other. This can help prevent the common problem where scientists write extremely long sentences.

Note that I’m only recommending putting line breaks in the source documents. Don’t put line breaks in published texts.

∞/3: Epilog · Abstraction

26 June 2016

554 words

[When I gave a draft of part 3 to a friend to read, they commented on the first paragraph, “Math isn’t about giving things funny names; it’s about giving things meaningless names!” I had a thought on this topic but when I wrote part 3, but I couldn’t really make it fit and thought it wasn’t that interesting anyway, but my friend said it was, so here goes. (Parts 1, 2, 3.)]

15-year old Nino had an idea once: “Math is stupid! When solving physics problems, you always have to take the actual physical quantities, then make up weird letters to put them through the equations, and then you have to translate them back to the physical quantities. This makes it harder to see what you’re doing because, when you glance at an equation, you only see the relations between letters and not the relationships between the actual physical quantities. In the hundreds of years that science has been around, someone must’ve come up with a more intuitive way to write equations. After all, computer scientists don’t just call their variables a, b, c, x, y, z either!”

However, the meaningless symbols are actually a good thing. As I said earlier, the scientist’s job is coming up with mathematical constructs that mirror the behavior of certain aspects of reality. They use this mathematical model to look for new unexpected behaviors and run experiments to check whether these behaviors can be observed in reality. Now, since many things in the universe kinda look the same if you squint a little, it makes sense to apply the same models to them. Thus, you can solve the complicated math parts of your model once, while getting new predictions for many different experiments. For example, you only have to solve the equations for the harmonic oscillator once to model everything that sort of vibrates a little.

Or, you write an object’s kinetic energy as $E_k=m v^2/2$, and its rotation energy as $E_r = I \omega^2/2$. In both cases, you have half of some property the object has (the mass $m$ or the moment of inertia $I$), multiplied by the square of what the object is doing (How fast the object is moving $v$, or how fast it’s spinning $\omega$). So when you want to, e.g., form the time derivative of $E_k$ or $E_r$, it still has the same form ($\dot E_k = m v \dot v$ and $\dot E_r = I \omega \dot\omega$) and you can easily see that you don’t have to do the calculation twice. Thinking about formulas in this way can also help with memorization: If you take the rule, “Energy is always¹ half of a property times the square of something that changes,” what do you think the energy stored in a capacitor looks like? If you’re a person who frequently finds themselves in situations where they have to answer such questions, you may remember that the Very Important Property of a capacitor is the capacitance $C$, and a thing that changes is its voltage $V$. This suggests the stored energy would be $E_c = C V^2/2$ which, in fact, is correct.

3/3: Mathematical notation

13 June 2016

Modified: 12 October 2016

1876 words

[Part 3 is about communicating mathematical ideas. Part 1, Part 2. I took care to contain the tedious math bits in single paragraphs, so the point is still clear if you choose to only read the fun parts.¹]

summary. There is no such thing as “wrong” notation. All that counts is that you get the math right and communicate your ideas clearly.

Last time I explained how it’s not accurate to say that an electron “is” a wave function, because an electron is a thing in the universe and a wave function is a mathematical object, and mathematical objects don’t live in the real universe. When people talk about wave functions, they often use the letter $\psi$. Obviously, even though it looks all nice and wavy, the $\psi$ itself isn’t the wave function either – it’s just its name. The concept of names is one we know and love from the real world: When I point at a chair and say, “This is Bob,” it’ll be clear what I mean when I explain that Bob has three legs. While it’s a terrible idea to call a chair Bob, giving things and their relationships with each other funny names is basically what mathematics is all about.

Just like we grew up believing that dictionaries had authority over the reality of words, school taught us that $+$ means you add two numbers, $-$ means you subtract them, $\times$ means you times them, and so on. But these symbols weren’t handed down from the heavens to the first humans to walk the Earth. There was a time when they didn’t exist, and then someone made them up. Now, $+, -, /, \times$ are pretty basic and sometimes you may even have a use for them in every day life, so these symbols are generally assumed to refer to their corresponding arithmetic operation. There are a handful of other symbols that are pretty unambiguous in their meaning, like $\sqrt{\cdot}$ or $=$, but beyond this lies madness.

madness 1: when wrong is right and right is complicated

The slope of a function graph is called the function’s derivative. (If you’re familiar with, like, math, this may be known to you.) When your function is a straight line, you get the slope by dividing the difference between two function values by the difference of their arguments. When we write the differences as $\Delta f$ and $\Delta x$, the derivative can be written as $f' = \Delta f / \Delta x$. Here, both $\Delta f$ and $\Delta x$ are real numbers. When you have an arbitrary curve instead of a straight line, you can approximate the slope by choosing $\Delta f$ and $\Delta x$ very small. The smaller you make them, the more accurate the result will be. Want infinite accuracy? Make them infinitely small. To make it clear that you’re working with infinitely small numbers (“infinitesimals”), you call them $\mathrm d f$ and $\mathrm d x$, which gives you $f'=\mathrm d f/\mathrm d x$. Yay!

But … what are $\mathrm d f$ and $\mathrm d x$? Both are infinitely small, right? So if you try to calculate $\mathrm d f$, you get $0$. And if you try to calculate $\mathrm d x$, you get $0$, too. If you took any other value for them, they’d no longer be infinitely small, and thus you’d get an inaccurate result. Thus, if $\mathrm d f/\mathrm d x$ were a normal fraction like $\Delta f/\Delta x$, it would be equal to $0/0$, and we all know never to divide by zero. Hence, since $\mathrm d f/\mathrm d x$ does have a value, it must be something else entirely. Remember part 2, where I wrote,

If Newtonian mechanics is wrong, why do we still use it so damn much?

In that post, I explained that Newtonian mechanics often gives us the best prediction we can make, and using a “more correct” model would not give us a better result. Maybe this situation is similar: what do we get if we pretend $\mathrm d f$ and $\mathrm d x$ are numbers, and that we just don’t know their values?

example 1. Say you’re told to solve the equation $f(x) \cdot f'(x) = x^2$. This may look daunting at first, but when you write the derivative as $\mathrm d f/\mathrm d x$ instead of $f'$, you get

$f(x) \cdot \frac{\mathrm d f}{\mathrm d x} = x^2\,.$

and multiplying each side by $dx$ gives you $f(x)\,df=x^2\,dx$. This looks like integrals without the integral signs, so let’s put some on both sides:

$\int f(x)\,df = \int x^2\,dx\,.$

Now we have $f^2 /2 = x^3 / 3$, so $f(x)=\sqrt{2/3} x^{3/2}$, and from this you can calculate the derivative $f'(x) = \sqrt{2/3} (3/2) \sqrt x$. Popping this back into our initial equation, we get $\sqrt{2/3}\cdot \sqrt{2/3}\cdot (3/2) \cdot x^{3/2 + 1/2} = x^2$. The roots of $(2/3)$ combine to a full $(2/3)$, which then cancels with $(3/2)$, and you’re left with $x^2=x^2$, which tells you that your solution is correct. /example 1.

In other words, we used a “mathematically” “wrong” approach to correctly solve a problem. In many situations, this is even a good idea. As long as you can prove that what you’re doing works, using symbols that look less mathematically rigorous but lead you to the solution more intuitively can save a lot of time and even help prevent mistakes.

The cool thing about this is: Many people have already realized this, which is exactly the reason we have $f'(x)=\mathrm d f/\mathrm d x$ and $\mathrm{curl}\,\vec v = \nabla\times\vec v$ and so on, which means you can often be pretty wishy-washy about your notation and still end up making fewer mistakes.

madness 2: when math isn’t all clear and unambiguous

Mathematics is known for being clear and unambiguous. And yes, we can definitively² prove that a theorem is either true or false, in contrast to the sciences where we only have falsifiable hypotheses and probabilities. But the language of math is just as bad as the language of language. Languages take shortcuts, sacrificing semantic clarity for the sake of data transmission rates. This is okay because most of the time everyone knows what you’re talking about.³ They tell you that mathematics doesn’t work that way, but I’m going to make the case that it does.

You know how you do your particle physics homework, and you use the symbol $m_e$, and the only thing that symbol has ever stood for was the mass of an electron, and your teacher tries to make this elaborate argument about the importance of declaring your variables but somehow they completely miss that you never told anyone what $\pi$ means or what $e$ means or what $\log$ means, and so on? But then the cutoff point between what you need to define and what’s “obvious” isn’t really clear, and it becomes this huge frustrating mess? That’s the kind of thing I’m talking about. Or you say, “Let $p$ be the momentum operator,” and your professor complains that $p$ can’t be an operator because operators always need to have a hat, like $\hat p$, and you say, no, you defined $p$ to be the operator and shut up you’re being ridiculous, but the professor insists and you end up having to draw a little hat on every single instance of the letter $p$ in your equations even though leaving it out would give you 100% the correct result and cause zero confusion.

example 3. You have a function $f(x,t)$ you want to integrate over $x$.⁴ You’ll write something like $\int_a^b f(x,t)\,dx=[F(x,t)]_a^b$, right? And here it’s totally not clear if the brackets are to be evaluated with $x$ as $a$ and $b$ or $t$ as $a$ and $b$. You know, from looking to the left of the equals-sign, but it isn’t clear just by looking at the right half of the equation. Likewise, some authors write volume integrals as $\int_V f(\vec r_1, \vec r_2)\,d\tau$, where it’s unclear whether they’re integrating over $\vec r_1$ or $\vec r_2$. They fix this problem by putting explanations in the text and following conventions throughout the book so it’s clear from context what they mean. /example 3.

example 4. Or, instead of integrals, let’s talk about derivatives. When you have a bunch of equations with many partial derivatives, it can be frustrating to write $\partial V_x/\partial x, \partial V_y/\partial x, \partial V_x/\partial y$, and so on, over and over. This is because you’re told that the components of a vector field $\vec V$ must always be written as $(V_x,V_y,V_z)$. But since all these letters are only names, you can simply rename the components. For example, you could call the vector field $\vec V = (X,Y,Z)$. This already saves you the work of writing a subscript every time you reference one of the components of $\vec V$. But as an added bonus, you can now use the subscripts for other purposes, like partial derivatives. Thus, you can define $\partial V_x/\partial x$ as $X_x$, $\partial V_y/\partial x$ as $Y_x$, and so on. This is much shorter and way more fun! I tried that once and my TA was hopelessly confused because they didn’t understand that indices on vectors don’t have to mean selecting the corresponding component, even though I explicitly defined what everything means at the top of the page. /example 4.

Context matters when writing down equations. Everything doesn’t have to be clear in isolation, as long as you explain what’s happening. Obviously this doesn’t mean that you can just write literally anything because then it wouldn’t be clear anymore what you mean. But what you can do is invent new notation and use that if it makes sense. Note, however, that making up your own things isn’t always a good idea: there already exists a large set of shared expectations about what many symbols do and, often, it makes sense to go with established conventions. Like if you’re using other people’s equations, you shouldn’t just exchange all the letters for no good reason, even if you feel like $\xi$ is a much nicer letter than $\lambda$.

In conclusion: Be free, be spontaneous, be brave – give your equations meaning instead of useless hats and subscripts. Sometimes, you really don’t have to repeat yourself.

2/3: Models

30 January 2016

Modified: 13 June 2016

1671 words

[Part 2 is the best part. Part 1, part 3.]

In science, we try to understand the world by building models and theories that describe it. You see an apple falling on your head, think, “oh, maybe that’s how the planets move, too”, and you write down rules that allow for the motion of planets and don’t allow for some phenomena you do not see, like things falling upward. You call the collection of those rules your model, or theory. When you have your model, you perform more experiments to test it, and every time your model’s prediction roughly matches your observations, you get more confident that your model is correct.

What does it mean for a model to be correct? This is where the trouble starts. In school we learn that classical mechanics is a pretty good approximation of reality, but quantum mechanics and relativity is the correct theory of how the universe works.¹ This framing has always bothered me: If Newtonian mechanics is wrong, why do we still use it so damn much?

Say you throw your keys out the window, and you want to calculate the path they will take to the ground as exactly as possible. So you get out your pencil and notebook and you start scribbling. Should you do your calculations relativistically? It would be more work, but you want to be really exact, so you add a bunch of γ’s everywhere and do your calculations relativistically. Then you notice that you’ve been assuming a flat earth the whole time. Oh no! All right – the earth’s a sphere, right? Let’s use that and we get an ellipse instead of a parabola for the flight path of our keychain. So – is the result more accurate than the classical, flat-earth one? Certainly not a lot more, but maybe a little? Nope. Not one bit. Why? Because the difference the air resistance makes, and the uncertainty of the direction you’re throwing in is much bigger than the difference a relativistic calculation could make.

This still doesn’t mean that objects in our everyday lives have a different nature than single electrons or supermassive black holes. It just means that, if you put enough electrons and protons and stuff together, and you don’t make them too dense or too fast, you can predict what they’re going to do by using the model of classical mechanics.

Many physics students, when they’re starting out, seem to feel like they’ve been promised something. That they’ll be led behind the curtains of reality and shown how the world really works. They seem to accept Newtonian mechanics – it works, after all. Medium sized objects, apparently, are Newtonian in nature. But it doesn’t take long for the disappointments to start. “Ideal gases don’t exist in nature, but it’s a simple model that works relatively well for lots of stuff,” they tell us. We’re not happy, but we’ll take the approximation, for now. We’re relieved when they teach us the “real gas” models, like Van der Waals gases. Then it gets worse again: “Ideal fluids are a pretty absurd approximation. There are no ideal fluids in the real world, and for most fluids, you don’t even get very good results using this model. But it’s simple, and it teaches the principles that you need to understand to work with better fluid models later.” We’re not taught the more complicated fluid models in that semester, and it leaves us with a quasy feeling. Why are we being taught a rough approximation instead of the correct model?

After a few semesters, the students get herded into a lab, to perform their first experiments themselves. Their belief is already shaken by countless lectures only teaching rough approximations instead of the real thing. But this is worse. Here, they finally see how the sausage is made. “All of physics is just estimations and approximations!” they exclaim. “Nothing here is exact!” It slowly sinks in that this is not just a rough approximation of what physicists do. Physics really is just approximations. Dutifully, the students draw error bars in their hand-crafted plots of noisy data, and wheep.

What’s important is that this isn’t a bad thing, and especially not a preventable thing. The approximations aren’t the result of laziness. The small inaccuracies in every scientific theory are the result of countless hours of patient, skillful labor. It’s awesome that we can make very accurate predictions about the behavior of gases just using pV=NT, instead of calculating the exact position and momentum of every elementary particle in our system. Because, by the way, that “system” is the entire universe. It’s super cool that we can just pretend planets are single points in space, with a mass and no size, only feeling the gravity of the sun and not each other’s, and still predict their orbits with great accuracy. Planets aren’t spheres, their orbits aren’t circles, Kepler’s Laws of Planetary Motion aren’t woven in the fabric of the universe, and yet, pretending all this is true will get us to Mars.

Since all models are wrong the scientist cannot obtain a “correct” one by excessive elaboration. On the contrary following William of Occam he should seek an economical description of natural phenomena. Just as the ability to devise simple but evocative models is the signature of the great scientist so overelaboration and overparameterization is often the mark of mediocrity. — George E. P. Box

The goal here is not “understanding”. The goal is making good predictions. I see my fellow students understanding that ideal gases don’t exist in nature, but I don’t see them make the jump to “Van der Waals Gases don’t exist any more than ideal ones do”. I don’t see them understanding that “quantum wave functions” are a mathematical function instead of a thing, out there in the universe. The problem is that physics ventures so deep into the hidden parts of reality, that it’s no longer intuitively clear that there is a distinction between the map and the territory. They tell you about the paradox of the double slit experiment and you conclude, “electrons aren’t just particles”. They show you Schrödinger’s equation and solve it to get the wave function. “That explains it!” you think, and you conclude that electrons are wave functions.

But the universe does not run on math. The reason the universe looks so much like it’s made of math when you apply science to it is because math is really really versatile. But this doesn’t mean our Laws of Physics are more than summaries of our observations. It’s not the universe that is good at being modeled by math – it’s the math that is good at modeling anything, be it our universe or universes with different rules.

I’ve heard someone say, after reading a mechanics textbook, that they finally understand why perpetual motion is impossible. It’s because something something holonomic constraints can’t do any work because something dot product. This can’t possibly be true because that’s not the order in which things happened. First the perpetual motion machine didn’t work, then the theory was written and it was written in such a way that perpetual motion machines don’t work, and that’s why something something holonomic constraints forbids them. If the textbook had explained, in detail, why perpetual motion machines do work, that wouldn’t have made it true.

We once had a homework exercise where we were supposed to say why a particle behaved in a certain way. The obviously “correct” answer – the teacher’s password – was “because of Heisenberg’s Uncertainty Principle”. But the Uncertainty Principle just follows from Schrödinger’s equation, and we’re using that to solve all our quantum mechanics problems. So by that logic, basically everything happens because of the Heisenberg Uncertainty Principle. That can’t be right.

For example, when a pen falls off a desk, that seems to be proof that gravity exists, because gravity made it fall. But what is “gravity”? In 1500, “gravity” was the pen’s desire to go to the center of the earth; in 1700 “gravity” was a force that acted at a distance according to mathematical laws; in the 1900s “gravity” was an effect of curved space-time; and today physicists theorize that “gravity” may be a force carried by subatomic particles called “gravitons”. Gendlin views “gravity” as a concept and points out that concepts can’t make anything fall. Instead of saying that gravity causes things to fall, it would be more accurate to say that things falling cause [the different concepts of] gravity. Interaction with the world is prior to concepts about the world. (source)

It’s not the laws we have written down that tell reality what to do. It’s reality that tells us what laws to write. Writing down the law will not make reality obey it. But reality doing something unexpected will make us write a new law.

The point I’m trying to make here is, when you have electrodynamics homework to do, and taking a few shortcuts by pretending stuff doesn’t interact as much as the theory says will allow you to finish in 6 pages instead of 47, maybe you should do that. Because there is no “correct” model. You’ll never know what matter is “really” made of. All you can ask for is a good prediction.

Victory!

25 January 2016

1396 words

People tell me I should go to a CFAR workshop and they may well be right, so it’s time to figure out how to prevent what is inevitably going to happen there from happening.

each of the workshop’s sessions invariably finished with participants chanting, ‘‘3-2-1 Victory!’’ — a ritual I assumed would quickly turn halfhearted. Instead, as the weekend progressed, it was performed with increasing enthusiasm. By the time CoZE rolled around, late on the second day, the group was nearly vibrating. When Smith gave the cue, everyone cheered wildly, some ecstatically thrusting both fists in the air. (source)

Group enthusiasm is not for me. I’ve been to the LessWrong Community Weekend, and I’ve been to EA Global, and each time, everyone was excited and there was always the stupid cheer at the end. I do like that this is a thing – enthusiasm is good! Group cheers increase the feeling of togetherness and community. I don’t want to suggest dropping this custom. Yet, every time I’m part of this custom, I cringe and I can’t cheer or shout or wave my fists around and, instead, I start feeling anxious, sad, and not part of the group. And if I’m not really careful, I always end up in a sadness/depression spiral. I want to change that.

I was wondering why exactly it is that I get anxious and sad when the people around me are extremely happy. This seems contradictory. When people around me are sad, I get sad; when people around me are happy – but within reason – I get happy. It’s only when we get into the extremely happy territory that my happiness drops. So it looks like this:

when it should look like this:

Let’s isolate the problem:

• I can be around small groups of extremely excited, happy, loud people and enjoy myself. I’ll laugh and feel part of the group, but I won’t participate in being loud and visibly enthusiastic.
• At the Community Weekend, where were situations where I was feeling sad and anxious, and this feeling was made worse when we were gathered as a big group, and people calmly explained how happy they were about the event. I did not feel part of the group.
• At the end of the first meeting of my productivity-/accountability-group, it was decided that we would do a group cheer at the end. It was a group of roughly five people and I had felt very integrated into the group up until that point. When it was time for the group cheer, I felt like an outsider and got anxious and experienced a sadness spiral for the rest of the night.
• I was once at a concert I liked. At concerts, everyone shouts along with the band (this was a metal concert). I tried – and I couldn’t. I knew nobody would really hear me, or pay much attention to me. It was really loud. But still, I was completely unable to shout, and it wasn’t a physiological problem – the issue was in my head.
• Relatedly: I would never even dream of screaming on a roller coaster. Not just because I couldn’t, but because it never even occurred to me to do that. I was always confused why people screamed – were they afraid? Didn’t they know roller coasters are safe? I’m not a person who screams.
• In my life, there have been approximately three times where I got so angry that I actually did shout at someone.
• Sometimes I get stressed out (mostly because of homework) and want to scream in frustration. Even if I’m the only person in the building, I can’t, and when I try, I feel trapped, because I can’t find a release for my emotions.
• I’ve tried acting in the past, and I experienced the same mental block whenever I tried to play a role that wasn’t me.

The interpretation of this that currently feels most right to me has two parts. One, being loud, excited, enthusiastic, isn’t me, therefore, trying to pretend that I am these things feels inauthentic and wrong. Two, not being able to participate in group behavior when (a) it is expected, and (b) I want to, makes me feel excluded. So the feeling is, group cheers is not something Nino does; group cheers are something members of this group do; therefore, I do not belong to this group.

I remember different situations where I deliberately played a specific role in order to nudge my identity in a certain direction. For example, before I started my TA job, I was Not A Person Whose Job Involves Leading A Group Of People. Deciding to change that was uncomfortable and anxiety-inducing. A person who could do a job like that was not who I was, but it was who I wanted to be. So I forced myself into the role and, knowing that I would be easier not to do this alone, I had someone sit beside me as I sent out the email asking for the job. Once I’d done that, I’d become a person who can, at least, ask for such a job. Once I’d experienced doing a thing a person like that would do, actually showing up to sign the contract and then going to the classes was much easier because I could just let subconscious consistency effects play out. “Well, I did ask for this job. If I’m the kind of person who asks for a job like this, that must be because I think I can do it, and that must be because I probably actually can do this.”

I didn’t used to be the kind of person who enjoys dancing badly at parties. I’m still not 100% comfortable doing it, but ever since I put myself in a situation where I was forced to participate and was in a good mindset to accept that I was actually doing it instead of “I’m forcing myself to do something that is not Something I Do,” dancing has become much easier for me – so much that it can even be enjoyable.

So: I alieve that I’m not a person who can shout, or cheer, or be loud and excited about things. Therefore, getting into situations where this behavior is expected of me, will make me anxious. Knowing that, the solution seems relatively simple. I need to practice shouting, and cheering, and being loud and excited about things. I need to do this as long as it takes to become less painful and aversive. For this to be successful, I need to be in an environment that feels safe to me. My best guess for what that environment would look like is: a group of 2, 3, at most 4 people, including me, in a place where no strangers can easily hear loud noises. Being inside a regular apartment with neighbors above and below would make this considerably harder. Doing this on my own won’t work because I can’t make all the noise myself. Turning on loud music or sounds from the internet won’t work because the sounds need to be human made. As I mentioned, concerts won’t work because I don’t feel safe enough around the other audience members. Open spaces, outside, far away from any buildings would work well because you could start out by standing far apart and shouting things at the other person. Since, in that case, shouting would be necessary to transfer information, it wouldn’t feel as aversive. From there, you could slowly move closer together while keeping the volume high.

Once I’m more comfortable with shouting, we could move on to loudly displaying enthusiasm by saying, “Yay!” and “Woo!” and “Yes!” and “Victory!” really loudly, and waving your fists around and whatever people do.

I predict that, if I do this a few times, group enthusiasm will be significantly more bearable for me in the future, which would make lots of social interactions easier; and that would be extremely useful for my life in general.

I also predict that I’ll feel really really silly doing all of this. (Even more silly than I felt writing it.)

(Comment or email me if you want to be my shouting partner. This could be lots of fun.)