bkcooper

Addendum: having now had the chance to start on Silksong, strongly recommend Hollow Knight first. That's not because of story, but because Silksong seems like it's geared to be noticeably more difficult than Hollow Knight was, both in platforming and in combat. (One of the things that I think Hollow Knight did really well was the spread of available difficulties. Beating the game isn't too hard; getting the true ending involves a few more specific difficult tests; and the DLC added boss gauntlets that let you go pretty crazy with how hard you want to make it.)

I mostly agree, and would say you should just play it blind. If you care about getting 100% (112% after the DLC) there are probably a couple of things where looking them up would be useful. It is also a very big world, so trying to do cleanup once you have all exploration tools can be quite involved

It is very much worth playing but you could probably skip it. As others have alluded to, the storytelling is very influenced by Fromsoft (Souls games, basically) and is pretty oblique. But, even without following it exactly, the gameplay itself is still great, and the music and art do an excellent job setting up a melancholy vibe. The different zones have a lot of personality.

I would assume that's mostly a function of this being for a general audience. Yes, you absolutely can talk about quasiparticles using techniques adapted from QFT. I don't know if Landau originally conceived of it that way, but there were definitely a bunch of Soviet physicists shortly after him who did.

In the article, "quiet" and "comfort" are bolded in that section, indicating that they are referring to Bose QuietComfort headphones

The recommendations in this thread so far do suggest a lot of nice books - CS:APP and SICP - but given your description of previous struggles with more academic stuff, along with the request for "practical examples or projects", I'm not sure they are right for you. By all means take a look, but don't be discouraged if they don't fit what you're after. An algorithm book with a somewhat different tone that you might check out is Skiena's Algorithm Design Manual. I've been reading Ousterhout's A Philosophy of Software Design recently and that might also be something that would interest you.

However, I might suggest that books and theoretical knowledge are not the main things you need right away. I moved into software engineering after a long time in science. I had done plenty of coding, and had a pretty decent amount of theoretical knowledge, but there was still quite a bit of practical adjustment. I really like Rzor's suggestion of https://missing.csail.mit.edu to start with.

Beyond that, I think maybe I would find some specific codebases that you'd like to understand better, and start with reading more of those. I feel like that's often better than books for picking up idiomatic usage and patterns in given domains. As you hit specific barriers, I think it will be much easier to pick up the intrinsic motivation to dip back into theoretical knowledge at that point.

Hadean Lands is also very cool

Yeah, I would not point somebody unfamiliar with Stern-Gerlach trying to learn "the basic idea of quantum mechanics" at Sakurai. Feynman lectures vol. 3 maybe

Well, the characters are stuck on a primitive planet in the Slow Zone so if you go in expecting Space Opera then you’ll be disappointed.

Except half of Fire Upon the Deep was characters on the same planet but it was actually cool. The first two books are definitely among my favorite sci-fi of all time, the third one was a dud.

My main gripe is that these three books all share the same trope that underpins one of the major subplots: glib, charming politician type is scheming, eeeeevil. In the first two books, there's enough novelty (how the Tines and Spiders work, programming as archaeology, localizer mania) to make up for that. But I don't really think the third book adds much in the same way, and it is also very clearly building to a confrontation that will happen in a future book. So the staleness is much more noticeable

I spent quite a bit of time at the end of high school into early college playing on a Forgotten Realms themed MUD. It accomplished two valuable things: it durably increased my typing speed by 20-30 wpm, and it also inoculated me against the MMOs which would have been way more destructive for me.

You might be interested in Kip Thorne (of Gravitation fame) and Roger Blandford's book Modern Classical Physics, which is designed to cover the elements of non-quantum physics that are generally ignored in the first year PhD curriculum. Part headers: statistical physics; optics; elasticity; fluid dynamics; plasma physics; general relativity

I largely agree with your comments in this thread -- I'd been thinking about trying to express the same thing myself. I'd been guessing the motivation would be ML, where I feel that most people substantially overestimate how much they'd need.

Signals processing, though, is one of the places where I actually think a decent understanding of some of the higher-level concepts in linear algebra is really helpful. Linearity itself comes to mind, and maybe it just reflects my physicist's education, but it's hard for me to imagine having a working understanding of Fourier transforms without getting the idea of changing bases. I feel like you're about halfway through a first linear algebra course before you'd get there.

EDIT: that said, a good signals processing book probably covers a lot of this in sufficient depth if you can figure it out. The other catch-all comment I'd make is that linear algebra from a math class can look somewhat different from practical linear algebra on a computer. (That it's often a bad idea to directly invert a matrix for many computing applications is non-obvious from math class.) A book like Trefethen and Bau is great on that latter subject but is not a good starting point for OP.

When the conductor is grounded, the charge on the conductor is no longer constant. It can change until the total enclosed charge in any sphere surrounding the conductor is zero.

Nocedal and Wright is good. +1 also to the suggestions for Boyd and Vandenberghe. I really like Boyd's writing in general; he has coauthored some good review articles on proximal algorithms and ADMM.

A couple of other suggestions:

Nesterov's Introductory Lectures on Convex Optimization. This one is pretty tough sledding, but I found the perspectives in the first chapter particularly to be enlightening. It seems like there's a newer Springer book which is probably an expansion on this.

Bertsekas's Nonlinear Programming. Bertsekas has written a lot of books, and there's a fair amount of overlapping going on. This one seemed to be the one that has the most nuts and bolts about the basics of optimization.

EDIT: If you want more understanding of convexity beyond what's presented in these books, Rockafellar's Convex Analysis is helpful.

Concrete Mathematics

Spivak

Jaynes

All good books, all pitched at a level that is very ill suited for what is being asked for.

To the GP, "math for English majors" is a common enough course schema that I think looking at a few syllabi might score you something.

This is false. A single particle can still be described by the maximum entropy probability distribution given its average energy . . .

I'm not sure that construction makes sense. For a single particle not interacting with anything, imposing the maxent constraint on average energy just sets the energy of the particle and there's no room left for a distribution. As soon as its interacting with another system you're good, but then the temperature that you arrive it is a characteristic of the bath, not the particle itself.

Matching memory games are something my daughter got into shortly before turning 4. We acquired a copy of Trouble from somebody and she likes that too.

The bullet points this article (and the one by Chad Orzel it links to) mentions are the common most used things day-to-day by basically anybody doing physics. However, I think stopping at that level of mathematical background would make reading a lot of the existing literature hard. Woit mentions complex analysis, but at least that usually comes up in mathematical methods classes, at least at the level needed to understand the arguments where it is used. Some math that I often found myself wanting more of includes differential geometry (I find physics introductions to tensor manipulation to be very heavy on mechanics and terrible on intuition for what you're actually doing) and functional analysis.

Both articles leave out numerical analysis or scientific computing, which I think is a huge gap. I certainly felt like my education left the impression that these things were way more straightforward than they actually are.

There's been a big push to shorten the game, constantly trimming out levels. I think some aspects of that turned out pretty well (I was skeptical of the D to D + Depths transition but ultimately I came around on it) but I actually liked the slightly longer game. The stretches of the game where I can get in a flow state and smash are usually among the more enjoyable.

My impression is that the devs who have been most influential for the last two to three years find that element of the game boring and instead want to put you in more "interesting" situations (e.g. forcing a rune before entering Vaults, increasingly strong new monsters in Depths.) I find that a lot of those things don't meaningfully decrease my chances of winning or force creative new strategies. Instead, they encourage me to do more tedious things like isolating single monsters, stair dancing, etc.

In fairness, I think my opinion on this was probably in the minority among heavy players at the time.

...the developers have "eliminate tedium" as a specific design goal.

I think lots of good has come from that. At some point, though, it started to feel like a lot of what the dev team considered tedium I considered fun, and vice versa. (I could of course download the old versions and play locally, but playing online was a lot of the fun.)

I need to see if I can get a spellcaster through the full game

"Pure" spellcasting can be done, but it's unpleasant to play (just from a UI perspective) and usually a suboptimal use of XP (DCSS usually rewards moderate investment in several areas rather than extreme specialization in one.) If you're not imposing that on yourself, then book backgrounds are overrepresented among the better starts in the game.

I was hoping that this would be a collection of ideas that failed.

How does electric current through a (non-super-) conductor convert energy to heat?

You have a coupling to other, non-electron/hole degrees of freedom in the system. The stronger that coupling is, the easier it is to transfer energy between the systems and the worse your conductor tends to be.

We're far too obsessed about "relationships" with other walking-dead sacks of meat instead of what really matters, our legacy and the future.

Who is this legacy and future for? "Other walking-dead sacks of meat"? Our glorious transhuman descendants?

I haven't finished it yet, but what I've read of Wasserman's All of Statistics I've liked. The chapters are a bit terse, so I'd plan on doing a bunch of the exercises. The good news is that there are lots of exercises and most of them feel well chosen.

Chapter 7 will eventually fill at least four volumes . . . assuming that I'm able to remain healthy.

Apparently TAOCP has a lot in common with the Wheel of Time.

I have a ton of respect for these huge, decades-long, life-defining projects and the people who undertake them (Robert Caro's LBJ biography is another example.) So the end of this project always receding further into the distance makes me wistful, even if the quality of what gets put out is still excellent.

If you got enough liquid in there, yes, but I think it's really unlikely you'd get that far. Until you've cooled things down, the liquid you put in is going to boil off, which has a corresponding volume expansion of almost three orders of magnitude. Without good ventilation (which you're not going to get if you're not cutting into the box because of the contact switches) this is going to lead to an explosive pressure buildup in the box, which seems like a really bad idea under the circumstances. There are lots of other possible ways for it to go wrong, e.g. the wires could break under thermal stress, which might lead to bad things; the boiloff could disturb the pendulum in the tilt sensor; etc.

The current trend of trying to figure out trustless solutions for everything actually worries me.

If you're worried about breakdown in the face of loss of trust, then these sorts of solutions seem like very important things to be looking at. Do we have any good ideas about how to create trust at the institutional level?

I agree with your concerns. I think they are representative of a broader theme - the acceleration of technical change seems like it will eventually (if it hasn't already) bring us to a point where the rate of cultural change is too slow to catch up to properly adapt to what is now possible.

The Wikipedia article on fractional calculus mentions that fractional derivatives are not local in the same way that integer derivatives are. Is that right? That seems profoundly weird in the context of differential equations.

I believe Overleaf offers this service. I haven't dealt with it myself, but I have friends who like it a lot.

Good comment. My addendum to follow is not directed to you, but to non-scientific readership.

Yea, it's boring for professor on the thesis committee to read, but this sort of stuff is very valuable for students and postdocs, who often struggle to reproduce poorly-documented results from other labs.

There's both absolute and relative poor documentation. The brevity of most scientific publishing (coupled with the lack of any sort of external incentive for clarity, as you point out) means that even papers that are good, by the standard of scientific papers, can be a real bear to turn into working examples. I personally feel that a lot of what makes various labs good is knowledge of the things that aren't going into the papers. A dissertation, with (potentially) a lot more room to go into details, can serve both as a source of this information for external readers, as well as a convenient internal reference for people in the lab who need to dig up some details of their prehistory.

edit: to clarify, my perspective on this is coming from physics. In other fields, there's more of an emphasis on explicit protocols and "methods sections" that presumably help with this sort of thing.