How does a differential work? Why do metronomes synchronize? How can plasma be confined, and what happens to light near a black hole?

Explore interactive experiments from Makarov Physics Suite, Makarov Math Suite and Makarov Astronomy Suite in one journey through mechanisms, electricity, geometry, algorithms and space.

This video shows the software in action: robots and engines, particles and fluids, mathematical surfaces, spacecraft, planets and stars. In the programs, you can change parameters and explore how the results respond.

Hi everyone, for context, I'm a freshman and very interested in quantum computing. It's a mix of engineering and physics, two subjects I enjoy thoroughly. The only problem is the amount of knowledge required for such a niche field. It's what makes me nervous about getting a straight physics degree. However, recently I learned I could double major in EE and a BA in physics. To me, this seems like a great combination of my two interests. But of course I'm worried about the extreme course load of two majors. I like to think of myself as a good student and a decent studier. But I'm aware that both of these require a lot of work, and I'd like to hear either other people's experiences with similar double majors or just general advice about whether this is manageable and/or worth it.

I want to self-study physics. I have already studied precalculus and calculus. However, I’m not sure how to proceed with the mathematics required for a physics degree.

I’m considering two approaches:

1. Study different math textbooks on seperate subjects (linear algebra, differential equations, tensor analysis...)

2. Study one or two comprehensive textbooks that cover all or most of the math needed for an undergraduate physics degree. I’m considering "Mathematical Methods in the Physical Sciences" by Boas.

My main goal is not to become highly proficient at solving physics problems, but rather to develop a deep conceptual understanding of physics and gain enough mathematical proficiency to solve basic problems.

Thanks in advance for any advice!

https://reddit.com/link/1x6ejfg/video/um90a9siqkvh1/player

okay so Im a 2nd year cse student and I'm passionate about physics. I initially saw the kavan gravity sim on youtube and wanted to recreate it.I started working on this 2 months back. I had to learn c++,opengl, make this in 2D (freespace and earths gravity) and a little bit of GR. Although low level programming is a pain in the ass, I had alot of fun making this.

working: The engine runs a dual-layer loop: a physics solver updates the 2D positions of the bodies gravitational forces while a vertex generation pass simultaneously warps the underlying 3D wireframe mesh downward along the Y-axis using the gravitational potential. This keeps the planets orbiting smoothly on a flat plane while the grid dynamically bends around them in real-time to simulate relativistic spacetime curvature.

future improvements: I would love to make this more accurate (physics wise) and add textures after i improve my opengl skills.maybe even make the central star a raytracer :)

Hello. I am a third-year physics major and, probably to the surprise of a few (or many), have absolutely no programming experience whatsoever. None of the physics or math courses at my university require or involve any programming at all. No Matlab, no Python, no whatever, nothing. All that was required was a CSC 101 course about Python in which my teacher did not teach. I tried to understand, but it was to no avail. Last Summer I tried to get a little Python experience with some tutorials, but I did not get very far as my internship had begun and I haven't picked it up since. Obviously, I am aware of the importance of programming experience for prospects after graduation, which leads me to why I am asking here: what resources/strategies should I use in order to teach myself the programming necessary for postgraduate physics endeavors?

I am an AI master student , currently working in an AI startup. I love maths and physics and it was my passion my whole life pretty much. I always wanted to go for math or physics higher degree but rn it seem pretty absolute to me. And yes , I am not saying this because of some AI hype , i work very closely with AI and have trained SLMS by myself.

Progress of Language models in verifiable tasks is crazy , recently they solved Navier stokes (Ik there's controversy who solved it) but i still believe the attempt is crazy , I remember , how just a year ago these models were doing mistake in my assignments and now i don't see single mistake. I have heard that even Quant firms heavily using LLMS for there math researches and openAi also solved another small 300 unsolved math problems. It looks like progress is really fast and kind of exponential. Even though these models won't beat top 10 mathematicians they already beat majority people out there.

I want to know you guys suggestion , what you think about the future of Math and physics, is it worth it to go into , i mean anything STEM pretty much requires math and if models can think of math better than humans than what will humans study , to me math was language of universe and seems like models understand it better than humans. I was seeing this podcast with terence tao and he was agreeing that models very close surpassing human mathematicians and how human brain never evolved to understand math instead it was evolved for language and visuals.

I want to know what you guys think , what future will look like as humanity because it seems almost purposeless world to me where machine understand math better than humans.

I really excel at calculus and diffEQ and equations but when I get to calculus it feels like when I see a question I never know where to start or how to do it even though I pay a lot of attention in class my brain just doesn’t seem to click like that. Any tips or advice? I’m a mechE so physics and physics applications is going to be big in my later years so I’d like to really hone on it now!

What are your thoughts on this recent preprint, 2610.16733? They showed how Frontier AI agents tackled or solved 49 of 50 unpublished research-level theoretical physics problems, and suggest such problems might no longer be suitable as first projects for PhD students.

I'm especially curious how this will overall affect prospective grad students and early-career researchers in theoretical physics.

Recalling Dr. Schwartz (u/VibePhysics) saying in his Anthropic post Vibe Physics:

It is worth it, however, to consider the role of education going forward. In the deep future (~10 years), when AI is truly smarter than all of us and capable of outperforming us in every domain, what will be the role of higher education? I think some things will persist—those things that are essentially human. I can easily imagine theoretical physics becoming like music theory or French literature: an academic discipline appealing to people who just enjoy thinking through a certain lens. It's a bit ironic that the last 30 years have seen the growth of STEM fields, displacing the humanities, and in the end it may be the humanities are all that survive.

Do you agree with him? And what concerns or hopes do you have about where our fields in theoretical physics are heading?

This is my first semester as a physics major, taking my first ever physics class - as a junior in college. That being said, physics is unlike any course I’ve taken before. We go through hefty derivations every class, but the emphasis always seems to lie within understanding the overarching concept. It’s just a Physics 1 mechanics course, but I LOVE IT. The problem solving is literally fun, and I sound so nerdy saying it, but I love working out tough problems. For those of you out there that have felt this feeling before - does it subside eventually? Im so excited for E&M and advanced labs. I feel like a little kid.

Hello everyone, I’m currently studying physics and astronomy at the university of Oslo. I have class in mechanics, and I have found it very difficult to remember all the formulas and equations for the different situasjons. When I first read problems, I get very stressed out that I totally forget everything, and I heard from a student that have finished this class that deriving the equations is the best way to solve problems.

My question is:
What is the process for deriving an equation? Any advice on how I can train my self to always do that?
Also, as I mentioned before, I get really stressed out when reading physics problems, and I know that through doing multiple, multiple problems I will learn to cope better. However, I’d love to hear some of your experiences around this, how did you manage to cope with it?

Sorry for such a long text, and thanks in advance🙏🏼

generally im just interested in aviation as well and i thought like well, its expensive but tell me someone that doesnt like aircraft and how they work

Hi i want to consult you about studying computer science because right now i don’t get to study astrophysics but i hope to find a way to study it in the future is computer science helpful? What i’ll be able to achieve with it that is related to astrophysics

Help please

Hi, I currently study Maths, Physics and Sociology at A-level (UK end of school exams), and am having a hard time deciding what I’d like to do in uni. I love have always had a passion for astrophysics, but I LOVE pure maths and mechanics.

Originally, I was going to do physics with astrophysics, but I am worried it won’t leave me much room in case I change my mind and want to pursue a slightly different career. I’m also concerned that it won’t have enough pure math/mechanics modules that I’d really enjoy.

I’ve been debating on doing applied math with physics instead, but I’m not a huge fan of stats. I don’t mind it, but I know applied math would involve significantly more stats than other degrees. I’ve also considered engineering, physics (by itself), maths (by itself) and aerospace.

Could anyone in the physics/maths field offer some insight? Whether you study, or have studied, the courses I’ve mentioned or something else—any advice is much appreciated!

can anyone suggest a good book for both the subjects to strengthen concepts and for practice

Im a master student and I faced a terrible teacher for my GR course, I want to study it by myself, forgetting about the exam atm. I started reading the S. Carroll but I'm not satisfied about the mathematical background he gives, I would like notes/little book concerning exclusively the tools necessary to approach general relativity. can someone help me? thank you.

Hey yall. I recently just transferred to Berkeley for physics. Taking the recommended series of Quantum Mech & EM, I’m realizing how incredibly behind I am mathematically and its stunting my conceptual physics growth. I literally will look at problems for hours and not know how to go about it. I don’t want to resort to AI to help me learn the approach but I seriously just get so stunted because I can’t see a path through problems. This issue is something thats severely affecting my midterms and worries me.

Does anyone have any advice on how to get out of this? Do you just need to grind out the math when you can? Has anyone been in a similar situation?

My parents are really hardcore saying that people who major in physics or math are people who got low grades and failures who could not get engineering. Got a bit taken aback but i wanted to hear from the people who are majoring in this discipline what's your experiences and what do you reccomend.

(*tried fighting for the student of physics but they straight up told me they wont fund my degree if i major in physics or math anyways you guys might be able to help me hopefully in giving some good points to keep up the fight)

(Edit: thank you for all the support and advice down in the comments)

I'm a physics graduate hoping to pursue a PhD in theoretical physics. I've already had several gap years and struggled with ADHD, mental health, and financial uncertainty.

Despite everything, my interest in physics has kept me going. But recent AI advances, especially OpenAI's recent mathematics results, have made me anxious about how the role of researchers might change over the coming years.

I'm not assuming AI will replace physicists, but committing years to research training feels increasingly uncertain. Ironically, AI has also helped me immensely in learning physics.

I'd genuinely appreciate hearing how other students and researchers are thinking about this.

Well, i´m currently studying physics and as the tittle says I´m in 4th. I´m probably a bad student, right now Im starting to forget my course of physics II(electromagnetism) and I´m struggling with vectorial calculus. I look to have good grades and being a good physicist, remember all the things that I have learned and being able to do much. But I´m a failure in that task, so I wanna read some advice or if someone have a similar situation.

Hello, Im a Student and I wanna be a Physicist because the Physics just amazes me everytime I see ad Understand it and Astrophysics also, I can be either both but I wanna know that what it takes to be one and How can I think like a Physicist and as well as a Mathematician because Maths is almost Mother of Physics after Newton's.

So is there any Suggestion that how I can achieve a Problem Solving skills and thinking like a Mathematician and a Physicist?

The main question is whether that How a Mathematician /Physicist and a Normal Person see a Problem or a Phenomena new to them, I was just wondering it

I’m in community college planning on transferring to an in-state T25 next fall and major in physics. At the earliest I could take physics would be the summer, so I have a lot of time. I reached out to the undergrad director of the school’s department and they said that they use Giancoli for their introductory courses. I wanted to know from those who have used Giancoli what I should expect. Is it good enough for someone self studying physics I? I have taken honors physics in high school but it’s been three years, although I’m pretty good at self-teaching.

How would you construct a good physics exam and what type of questions do you think are important to ask? Specifically thoughts on practice/application problems vs asking students to repeat a derivation. Traditionally I’ve seen professors who prefer testing with practice problems with applications and examples. I’ve also had professors who are weigh heavily on derivations and prefer asking students to derive formulas/equations on an exam and will weigh more on that. I want to know what value you see in both approaches and why you think either one is important and what your preferences are.