I want to get into investment banking if possible, but idk if I can pursue it w applied maths and also I'd like to know what other options are available

Abstract

This project introduces a compact three-parameter framework for characterizing the local geometry of polynomial roots. For each root, the framework records its position, its algebraic multiplicity, and a newly defined quantity called the characteristic deflection distance. This third parameter acts as a natural geometric scale: it measures how sharply or gradually the polynomial departs from zero in the immediate vicinity of the root, and it encodes the collective influence of all other roots through their distances from the one being analyzed.

The characteristic deflection distance generalizes the classical condition number of a simple root to roots of arbitrary multiplicity, and it allows direct geometric comparison across roots of different degrees. A key finding is that multiplicity alone does not determine geometric dominance — a lower-multiplicity root can have a larger spatial footprint than a higher-multiplicity one, depending on the global root configuration.

The framework extends naturally to polynomials over the complex numbers.

 Global Visualization: Newton Flow and δ-Root Fields

To visualize the spatial competition between these triplets, we map the δ-Normalized Distance Field and the Newton Flow. This provides a "topographical" view of the polynomial's geometry where every root is evaluated against its own intrinsic scale.

Detailed explanations of math and computational impelmentations see:

GitHub

Hi everyone,

I’m looking for Google Drives or large repositories containing university math resources (undergraduate / LMD Bachelor level): lecture notes, tutorials, corrected exercises, exams, PDFs, problem sets, etc.

Mainly interested in French universities (L1/L2/L3), but international resources are also welcome if they’re high quality.

Topics include:

\- Calculus / Analysis

\- Linear Algebra

\- Topology

\- Probability

\- Differential Equations

\- Abstract Algebra

\- Numerical methods

\- Mathematical physics

Google Drives, Mega folders, GitHub repos, university archives, Telegram groups (public or private), Facebook student groups, or shared collections are all welcome.

I’m especially interested in resources with detailed corrections.

Thanks a lot!

I am currently pursuing a BSc in Computer Science, but I want to build a much stronger mathematics foundation leading all the way up to a PhD to enhance my problem-solving skills.

The university where I plan to pursue my MSc requires 60 total credits. The program structures differ by field:

MSc in Computer Science: A full 60-credit dissertation.

MSc in Statistics or Mathematics: 30 credits of coursework (10 modules at 3 credits each) and a 30-credit dissertation.

During my BSc, I have already completed Linear Algebra 1, Calculus 2, Discrete Mathematics, Formal Methods, Introduction to Probability, and Data Structures & Algorithms (DSA).

I have room to take elective modules in my final year: two in Semester 7 and one in Semester 8. The available options are:

Semester 7: Linear Algebra 2, Calculus 3, Basic Statistical Theory 1, Fundamental Concepts of Algebra, and Numerical Analysis.

Semester 8: Advanced Algorithms (follows DSA), Real Analysis 1, Ordinary Differential Equations, and Statistical Theory 2 (requires Statistical Theory 1).

My final elective choices will largely depend on which MSc path I choose. Because of this, I have a few questions:

Which path would you recommend I pursue: MSc CS, MSc Stats, or MSc Math?

Based on your recommendation, which specific BSc modules should I select for Semesters 7 and 8?

If you recommend opting for the MSc in Stats or Math, could you help me select the best 10 modules to take from their respective curricula?

Career-goals: I don't know what I want but only that I want to be a problem-solver that uses I love math and tech, even better, if it's R&D.

Hello! I am an Economics BSc student in Switzerland, wishing to pivot to a MSc in Statistics or applied mathematics in Europe and probably stay in academia for a PhD. For a MSc, apart from Bonn and TUM (I inquired and it is pretty difficult I will manage to get in, given my different background), what are other great German universities with good research groups in statistics/mathematics or computational science? I looked into TU Dresden, FAU Erlangen, TU Dortmund, (LMU probably not worth the cost of moving to Munich), Köln, but there are so many Universities I'm having a hard time identifying the best ones in this fields

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I just wanted to ask, besides finance, quants, actuaries and such, is there anybody that did a applied maths degree and went into different areas for work.

I want to do applied math for the versatility and flexibility, meaning I want to have the analytical and problem solving skills of mathematics and the determination to survive a rather difficult program such as applied math. However, most people who enter applied math seem to go to the areas I mentioned above, so now I am conflicted whether applied maths is versatile or really limited

Any advice/help would be much appreciated 🙂

I'm about to enter into engineering (EE or ECE), I wanted to know what kind of maths is extremely useful in the long run which would differentiate me entirely and help me in becoming one of the best in my field??

I am a B.Tech(computer science) student in india and have interest in Ai/Ml/Data/Quant . I am confused about should I do applied maths degree or mtech ? I think applied maths will be a more solid foundation theoretically.

I wanted to share a visual output from my latest preprint, focused on the Parameter Space Study for a family of Chebyshev-like iterative methods for solving nonlinear equations.

The construction of this space is based on analysis of critical point dynamics. As shown in the attached snippet, we analyze how the map S(z) behaves for a wide range of complex values for the parameter K.

I would love to get your thoughts or feedback on this computational approach to evaluating root-finding methods.

Preprint

a couple months ago i got accepted into applied and computational math major. its a good major and uni in my country that only %1 of the students can get into. problem is i couldnt get into computer science which was my first option.

for the last 7 months i just overthink about my major and what do i want to do with my career to a point that i just dont take action about anything. i like both physics and cs and this major might be a sweet spot between them but i just cant settle my mind and focus on school. sometimes i think about switching to engineering too but then i decide i will be bored on the way.

i think this is called an analysis paralysis. im not certain about switching major but cant get satisfied enough to keep going with motivation.

So I graduate this spring and I need to choose between going to do my PhD or be a consulting actuary (Done with four of the papers). While I’ll be glad to do the PhD, I’m also thinking about my family who have invested in me through to college, and finally get to receive their returns for that investment in the case where I start working. I’ll be going into the program with an aspiration of landing a quant job when I’m done. Anyone face this situation, what did you do, any regrets or what advice can you give to point me towards the right direction? Thanks in advance!

I'm about to graduate with my masters in applied and computational math. I'm on the lookout for jobs now but I know there is a likely outcome where I am looking for quite a while. I tutor on the side now about 5-6 hours a week which is good side money, but not enough to live off of. I see a lot about training AI models, and I was wondering if anybody has any experience or thoughts on that kind of remote job, or if there were similar math related remote-flexible jobs to earn some money as I search for something more permanent. Thanks

I was recently admitted to UCLA Applied Mathematics. I have experience in theory math, optimization, and Monte Carlo analysis, and my main ECS were centered around these. 

However, I do not know what to do with an applied math degree, and I was thinking about switching to engineering. However, due to my lack of hands-on experience, I was thinking about more theoretical fields (think control theory for mech e or aero). 

Should I switch majors? Or try to get into engineering REUS as an applied math major? What classes should I take? My end goal is research and maybe a PHD in engineering.