Chat link is linked. Credit to https://x.com/dmitryrybin1/status/2079904005652893709?s=46

I am in high school and self studying mathematics with the goal to get to algebraic geometry/differential equations/topology (basically as advanced as I can get ig). I am doing this mostly for my intellectual satisfaction rather than anything financial going down the line. I feel that I would probably still self study maths even if Aİ was basically at the top of the chain (it seems to be going down that path) what do you think?

Would you? How much does ai worry you?

I’m an undergrad finishing a BSc in Computer Science, aiming for an MSc (thesis-track) specializing in the Formal Verification of Hybrid/Cyber-Physical Systems (CPS). I love rigorous math-heavy problem-solving and software engineering.

I need to choose 2 final math electives from this list:

* Linear Algebra 2

* Calculus 3 (Multivariable)

* Numerical Analysis

* Basic Statistical Theory 1

* Fundamental Concepts of Algebra (Abstract Algebra)

Math I've already completed: Linear Algebra 1, Calculus 2, Discrete Math 1 & 2, Intro to Stats, and Formal Methods.

1. Which 2 modules will best prepare me for the continuous/discrete intersection of CPS verification tools and reachability analysis?
2. I haven't worked with hardware in my undergraduate level. Is this a disadvantage?
3. It seems — in my research — that Formal verification engineering jobs are mostly for hardware instead of software. How true is that?
4. For someone who genuinely enjoys deep mathematical problem-solving combined with technology, is Hybrid/CPS verification a rewarding path, or would I find Computational Learning Theory a better fit for graduate research?

Thanks for any insights.

Assume you have only one month to live, what topic you. want to understand before you die?

algebraic geometry, topology, cohomology, lie group ....etc

The information on the internet may be obsolete. Also is there a tier list for journals about graph theory?

Hi everyone,

I’ve been working as an independent researcher on an alternative regularized framework for the 3D incompressible Navier-Stokes equations, focusing on mitigating high-energy convective blow-ups while structurally enforcing global energy conservation laws.

Instead of using traditional subgrid models or smoothing techniques, I introduced a modified convective operator T_reg(u) based on a strictly anti-symmetrized tensor architecture, embedded with a high-gradient dynamic attenuation factor Gamma(u). By definition, this guarantees that the energy inner product strictly equals zero unconditionally, preserving the structural L2 stability bound.

To back the analytical proof, I wrote a high-precision pseudo-spectral (FFT) Python solver to monitor long-term simulation stability.

Numerical Validation Results:

\- Identity Check: Verified the algebraic condition across 1,000 randomized chaotic configurations down to pure machine precision (< 10\^-13).

\- Ultra-Long Term Simulation: Integrated the time-dependent system over 500,000 steps without a single hint of numerical divergence or NaN error. The kinetic energy decays monotonically and smoothly.

\- Ideal MHD Stress Test: Tested the same operator under absolute zero-viscosity conditions for 10,000 steps. The solver successfully absorbed the hyper-turbulent coupling without numerical collapse.

The full project is hosted on GitHub under a GNU GPL v3.0 license:

GitHub Repository: https://github.com/mateialex18/Readme.navier\\_stokes

I'm sharing this here to get your thoughts and technical feedback. Let me know what you think!

Is it just me coming across this especially on TikTok? İt always goes like "I'm recording this on the date x/y/z and I just solved the Riemann hypothesis haha let's see how things will go from here."😭😭 are these just trolls or something?

All the examples I’m seeing on the internet where LLM’s are solving problems seem to have counter examples. But say that Cantor had access to Claude with the bookish information at that time. Would the LLM at that time come up with the diagonalization argument?

Or an even harder example is Andrew Wiles proof of the Fermat’s Last Theorem?

Hello! I just got to the ICM and found out that literally no one I know is here. the profs, postdocs, PhD students, and fellow undergrads I know who said they’d go earlier in the year all dropped for various reasons in the last couple weeks :( are there any other younger mathematicians who would be down to meet up at some point in the coming days? Always looking to meet new people!

im sorry if this is the wrong place to ask but what minor did you choose if you did a math major?? Im honestly having such a hard time and thinking about just not doing a minor. (Maybe stats or Econ ????)

I'm starting my freshman year at college with a major in mathematics and I cant find anyone with my particular issue. As it says in the title I'm torn between a laptop and tablet as I fully intend to take digital notes as my paper notes are always unorganized and I lose important things often. A issue with a laptop is I would need to get something to take notes on if I got one and a laptop feel like it will be redundant as I am not going to use it at home. I feel like a tablet with a keyboard would just cover all my needs but I would like advice from people who have already gone through this or any recommendations on what to do.

I've seen on other similar posts that a program called LaTeX will require I have a laptop but is this something I need use during lectures or something I can just use my desktop for. Also for reference I live close enough to my school that I will be going home everyday so that's not the issue.

Before I came to this debate I was looking at laptops and found the Acer - Swift Go 16 AI on sale for for 699$ usd. However if anyone has any better recommendations if you think I need a laptop feel free to send them but I would like to say around the 700$ but don't mind going above it if seriously needed. Also I would like to use windows as I'm not a fan of Mac OS. And for tablets I would also just prefer to avoid apple products as I'm not a fan of them but wouldn't mind if its the only good option.

Additionally for classes I'm taking I will have calc 3 in fall and diff eq in the spring if this effects what I should use lmk.

TLDR: just read the title.

recently i studied autostereograms and tried to make them on my own out of curiosity. the outcome was not practically useful at all as there're millions of free resources online that could make autostereograms of high quality. it's the journey that mattered. i learned a lot from it and i'd like to share

at first i was overwhelmed by the amount of variables i had to deal with. the eye separation, the view distance, the background distance, the width of the base pattern, the closest point relative to the farthest point, etc. i got lost. after some struggles i realized it's all about ratio / similar triangles

then everything became simple. we don't have to actually set how far the observer was from the screen, etc. as shown in attached image 1, we let the entire thing to be 1 unit wide and 1 unit high and deal everything inside as ratio

as a math guy i particularly love those variables that lie between 0 and 1. we imagine the observer and the background (the plane containing the farthest point) never move. the screen moves. when the screen touches the background p=0. it's the possible minimum of p. when the screen touches the observer p=1. it's the possible maximum of p. the smaller the value of p, the weaker the 3d effect is

we do the same to the closest point. closest point can be interpreted as the highest point of the 3d scene. we imagine the screen and the background never move. the closest point moves. when the closest point touches the background q=0. it's the possible minimum of q. when the closest point touches the screen q=1. it's the possible maximum of q. the smaller the value of q, the weaker the 3d effect is

let's call p the background factor and q the foreground factor and here's my program. you can run it on browsers. click ▶️ to run. click ⏹️ to exit. when running the program

• press [q] to decrease foreground factor
• press [w] to toggle foreground subject (a disc / a sphere)
• press [e] to increase foreground factor
• press [a] to decrease background factor
• press [s] to change background (4 included)
• press [d] to increase background factor
• press [x] to toggle caption (off / on)

all backgrounds are function generated. if you have any interesting ideas of making background just let me know...:)

Hello all,
I’m currently in the process of enrolling in classes for my first semester in college. I graduated from high school in 2024 and haven’t had much math experience since. Even while in school, I avoided the complex math classes because it was easy to rationalize that I wouldn’t need them for anything I was interested in- plus it was frustrating that missing a day or two meant a complete disconnect from whatever the next section was.

All of that to say, I’m not too well versed in math, and have made no attempt to sustain most of the information I had.

My current situation:
- I moved to Seattle last year and have obtained residency
- I am working 30-40 hours a week and am making enough to sustain myself, but it’s difficult to save up.
- I’ve enrolled for the fall quarter at Seattle central college
- I don’t know what I want to pursue in school, so I want to have general classes that leave wiggle room to make that choice later
- my partner is a math major

Now the question is- should I take MATH 146? Looking at everything I just laid out, the obvious answer to me feels like no. Taking 146 requires me to concurrently take math 46, which I wasn’t planning on because I didn’t want to overfill and exhaust my schedule since I’m also taking english 101. All three of those classes line up to make my in-person schedule MoWe 8:05-11:35 (eng,46,146)

Again, this is my first college experience. I couldn’t find much information on the subject which is why I’m here. My work is able to accommodate my school schedule and express that they want me to succeed; even with accommodations my hours will still take a slight toll.

If you’ve made it this far, I really appreciate it. Please ask any questions that could help. Thanks :)

Firstly this is not some form of self endorsement, i don't know the guy in real life or anything, came across him a while ago and he has good content. What do you think about him?

I'm planning my undergrad degree and would love to hear from people who studied Applied Mathematics and Statistics. I love using math to understand complex systems and am most interested in things like space, weather, oceans, history, culture, and languages. Since I obviously can't major in all of those, I'm considering majoring in Applied Mathematics and minoring in Statistics because it seems like a flexible foundation that could be applied to many different fields. Unfortunately whenever I search for career paths, I mostly find people who went into computer science/tech, finance, or medicine which is fine but I'm not interested in those fields at all. Has anyone here used an Applied Math/Stats background in scientific research or other interdisciplinary fields like the ones I'm interested in. If so, what's your profession? If you're in science, what field are you in? I'd like to know more about using applied math/stats in areas like atmospheric science, oceanography, astronomy, environmental science, archaeology, linguistics, history, geography, or the digital humanities. I'm trying to understand how broad the field really is and what kinds of careers people have actually built with this background. I'd love to hear about any less common paths that you've taken.

I'm a PhD student working in probability and analysis, and right now the problem I'm working on could be considered a moderate extension of some existing theory. But it seems like AI is leading to the rapid devaluation of such work and pure "problem solving" as a skill in general (see for example https://davidbessis.substack.com/p/the-fall-of-the-theorem-economy ). If i were to summarize with an analogy - the stock of combinatorialists feels like it is falling while that of people working on geometric Langlands feels like it is rising.

The common sentiment pretty much everywhere seems to be that mathematicians will now be AI guiders and checkers (although the status quo is changing quite literally every day), and those with a wide vision of the entire mathematical "forest" will survive and those who "solve problems for the sake of solving problems" will not or at least will be deprioritized. Honestly, when I think about it, the problem I am working on is small enough in scope that it could probably just be plugged into ChatGPT Pro and solved after some thinking by the model, with no input of my own except a decent prompt. And I have a subscription to GPT Pro, but I still struggle to do that because it just feels so pointless. But at the same time, I feel pointless and obsolete, because - well I am, because my core skillset is problem solving.

Everywhere I look, I see posts stating something to the effect of "solving problems is not the point of mathematics, improving understanding is". And I kind of get it, it's a little evidenced by the counterexample to the Jacobian conjecture, which I saw, and basically said - ok cool, now what? But on the other end, as someone who enjoys struggling with a problem (without thinking about any broader implications), that aspect of math disappearing is deflating. As Paul Halmos famously said:

"Don't just read it; fight it! Ask your own questions, look for your own examples, discover your own proofs. Is the hypothesis necessary? Is the converse true? What happens in the classical special case? What about the degenerate cases? Where does the proof use the hypothesis?"

Sorry, this turned into a rant, but I assume many others are struggling with this transition and I wanted to just get a consensus and some opinions of what people are doing or think is the right thing to do, other than just quit and start feeding questions to AI and become AI guiders. Because if that's what math is going to become, I'd rather not do it and just pursue another field. Literally today, I found a paper on the Arxiv which literally set up a system to autonomously dig through arxiv papers for open problems and then feed them to some kind of LLM to see if it can prove it. Sure, this kind of activity is seeking truth and trying to advance the frontiers of mathematical knowledge - but is this really the point of math? Is this really what it's all about and what it's all going to be?

Here's an example of a non-specialist proving a result which is true just by plopping it into an LLM - it is literally "vibe math":

https://x.com/vikvang1/status/2079370200286433340

The example below is by people who are experts in the field, but basically created an autonomous system to trawl papers for open problems and then feed them into LLMs so that they can find solutions. Big caveat here: I have a lot of respect for the authors - they discuss the impacts of AI in terms of dislocation of early career researchers, and the general societal impacts and how humans are still important. I laud them for that. But still, it's ultimately an automated system to find problems and solve them, almost for the sake of solving them.

https://arxiv.org/html/2607.17388v1

What is the point of working on specialized/non-famous problems and understanding a field deeply if this is what's happening now?

Hey all. I am studying calculus 2 this summer and my professor has put forward a new criteria for getting an A and a quite unrealistic one at that. He said if using chatgpt or any assistance , we are able to create a new convergence test that has never been presented before (works even if it is applicable for even just a few types of series and fails for others) , we can get a good grade. Is it kinda possible that we do this? Has anybody got an idea. HELPPPP

p.s dont mind my english, its my 2nd language.

Hello!

I am going to graduate in December with a degree in Applied Mathematics. I have had a variety of interests through my classes (cryptography, options, optimization, amongst a few others), but I am unsure as to do what I want to actually do once I graduate. I have started to consider graduate school, but I was wondering if I should rule that out since I’m already unsure on what to specialize in. Any advice/discussion is welcome, just trying to hear others thoughts and experiences.

For those that celebrate.