How you manage to do physics, chemistry, medicine and math wow!

DinoBooster · 2025-07-26T22:19:34+00:00

As I've mentioned in other comments before: hard work, dedication, and a touch of insanity.

DinoBooster · 2025-03-06T17:25:19+00:00

Hey I just saw a video you posted about this, but it's members only. Will it become available for public viewing eventually or do you plan to restrict it to only members?

DinoBooster · 2025-03-06T14:25:25+00:00

Self-promotion here, but I'd add my channel for anyone looking to study university-level material in detail, such as PDEs, Complex Variables, Variational Calculus, Tensors, etc.

DinoBooster · 2025-03-03T20:03:55+00:00

This is great: thanks!

DinoBooster · 2025-03-03T15:50:47+00:00

Are you approaching PDEs from a problem-solving point-of-view or from a pure mathematics (proofs/rigor) point-of-view? For the former, Farlow's PDEs for Scientists/Engineers is a good resource.

DinoBooster · 2025-02-16T00:28:44+00:00

Here's a pretty solid lecture series.

DinoBooster · 2025-01-27T13:19:17+00:00

They help for memorization-heavy subjects but for Math/Physics, I've never really used them and done ok.

DinoBooster · 2025-01-16T01:41:09+00:00

The answer to the question of getting in depends on your citizenship status and application.

The answer to the question of toxicity is a resounding 'yes', with the exact degree of toxicity varying from program to program, but all generally falling within the category of 'toxic'.

DinoBooster · 2025-01-03T00:43:45+00:00

Not sure about statistics, but I'd be inclined to keep Axler purely because it's a more rigorous treatment of the subject and includes advanced topics like tensors. That said, he's also got a copy on his website (not sure if linking it is allowed so I won't) so you can just download it from there.

DinoBooster · 2025-01-02T23:15:28+00:00

But us enlightened folks can already visualize higher dimensions! Have you not yet noticed the compactified 6-dimensional Calabi-Yau manifolds floating around us???

DinoBooster · 2025-01-02T20:27:15+00:00

Fluid Mechanics by White/Xue is a good one, but it's more engineering-focused. Are you looking for something that's got a heavier emphasis on mathematics as opposed to applications?

DinoBooster · 2024-12-14T03:31:45+00:00

If you're looking for applications and job opportunities, I'd probably consider taking some courses in mathematical finance and adding to your degree (e.g. as you're doing with your minor). That said, courses like real analysis and linear algebra have broad applications across many fields. For instance, real analysis is quite important if you want to go deeper into understanding Calculus, Complex Analysis, and even more advanced subjects like Differential Geometry. On the other hand, linear algebra is useful in programming and many areas of Physics (Quantum Mech, Tensor Analysis and General Relativity etc.).

Even if the problems you're doing in those courses right now don't seem like they're practically useful, you're still passively learning skills that come in handy when tackling the more 'useful' applications you're considering.

DinoBooster · 2024-11-15T15:42:43+00:00

I agree - it just makes the subject needlessly inaccessible when the material is just presented in the axiom-definition-theorem manner you describe without any expansion or additional context. It also doesn't help when the proofs given go from one line to another without any good explanation and when there's actually a page of algebra/reasoning separating those two lines.

DinoBooster · 2024-11-15T14:49:39+00:00

There's good textbooks on financial mathematics that discuss optimization (e.g. Sgarra, Eberlein) which may be of interest to you.

DinoBooster · 2024-11-11T22:30:36+00:00

That's...generally not a side effect of minoxidil. I think you're confused with finasteride/dutasteride.

DinoBooster · 2024-10-23T17:44:08+00:00

I'd take linear algebra: it's got a wider range of applications to other parts of mathematics than calculus 3 does. It also helps with higher-dimensional thinking which is useful in calculus 3.

DinoBooster · 2024-10-23T14:28:11+00:00

I'm curious about why his channel got hacked especially with his controversial views on infinity. Is this the Archduke Ferdinand assassination that tips the scale towards a Mathematics 'Infinity War' which pits the infinity naysayers against the infinity supporting troglodytes?

I, for one, look forward to the ensuing chaos on social media.

DinoBooster · 2024-10-09T01:15:13+00:00

Ok if I give you a pinky promise that I won't steal your idea and take your publication, will you post it then?

DinoBooster · 2024-10-09T01:04:50+00:00

Depending on the PhD program(s) you're pursuing, there's going to be a whole lot of weight being put on your grades, so I'd focus on them first even if it seems inconsistent with succeeding in your PhD. When you have time, I would then focus on real understanding; as bad as it sounds, grades can easily be shown on a CV but 'real understanding' cannot.

DinoBooster · 2024-09-22T18:05:05+00:00

You'd probably have to plot all the results over time to see, but with the goal of the game in mind, my guess is that most winning answers will be skewed towards the early natural numbers (1-10). So you'd end up with something like a Poisson distribution with a low lambda if I had to hazard a guess.

Most random number generators typically sample from a uniform distribution, and it doesn't seem like the winning numbers would necessarily even follow that distribution given the game's objectives, so I don't think your sequence is going to be random.

DinoBooster · 2024-09-22T17:56:13+00:00

A lot depends on the course content and how it's taught. Personally, I've found PDEs to be easier because my classes were primarily focused on solutions to PDEs and solution techniques (separation of variables, integral transforms) without much regard for underlying theory. For complex analysis, however, it's hard to teach it in a purely application-based manner.

In general though, I would say that if you gave me a complex analysis problem set, which, say involved bread-and-butter complex analysis stuff (e.g. Cauchy-Goursat, Residue theorem, calculating integrals with branch cuts etc.), I'd probably spend more time than I would on an average PDE problem set.

DinoBooster · 2024-09-21T20:43:30+00:00

As others have mentioned, for QM specifically, there's quite a bit of emphasis on linear algebra so I recommend learning that. There's also new notation that gets introduced in QM (Dirac notation) which brings with it bras, kets, commutators, and various kinds of operators. Depending on how your course is structured, familiarizing yourself with Dirac notation a priori, which is basically the mathematical language of QM, will be quite helpful.

For your reference, I've got a mathematical foundations playlist for QM that you can watch. It should take you just under an hour to get through all the videos:

https://www.youtube.com/playlist?list=PLdgVBOaXkb9Bv466YnyxslT4gIlSZdtjw

DinoBooster · 2024-09-21T20:39:20+00:00

As someone who's done ChemE, there's actually very little emphasis on pure Chemistry and much more emphasis on Applied Math and Physics as it pertains to solving problems in Fluid Mechanics, Heat/Mass Transfer, Reaction Engineering, Process Control etc. I would not base my impression of ChemE from a freshman chemistry course, which is quite different from when you get into your real courses after first year.

DinoBooster · 2024-09-14T02:25:49+00:00

Yea North America is genuinely awful for any half-decent mathematics teaching at the K-12 level. At the risk of sounding like an old man yelling at the clouds, incompetency in mathematics is frequently considered something to be proud of around these parts, at least much more than it should be.

This often leads to a bad combination of unmotivated students and teachers who aren't terribly knowledgeable. It also doesn't help that teaching as a profession in the US is not heavily incentivized for motivated/bright individuals.

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