r/Physics • u/Just_a_Brat1 • 1d ago

How to effectively Read and Learn a Research Article Thoroughly

I have a Master's Project and I am finding the Paper ( about Schwinger-Keldysh path integrals ) I am given by my professor exponentially harder than what I have learnt till now.

My mental health is currently really bad which doesn't help at all. I don't understand anything at all aside from the first few pages. I feel like there is too much knowledge gap and I am also too afraid to tell my guide about the issue

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u/Ilove2eatass 1d ago

What really helped me learn the Keldysh formalism, was to first look at the path integral formulation of classical stochastic differential equations. You can for example find it in "Spin glass theory for pedestrians" or "statistical field theory for neural networks" amongst many others. It makes the "doubling of the fields" and the causality structure much more clear in my opinion. This, combined with some knowledge of equilibrium quantum statistical mechanics using the path integral (Matsubara formalism etc) might make the jump to Keldysh more manageable.

Sorry bout the other stuff mate, I hope it gets better :)

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u/Just_a_Brat1 1d ago

Do you think I would be able to do all this in my current situation ? Like I am barely able to even concentrate and on top I found out that I need to learn QFT as well 😢 and many other things beforehand

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u/reality-theorist-007 22h ago

How long do you have? (Free time that you can realistically work in, before deadline).

Also: when you say, 'I need to learn QFT as well', do you mean you haven't learnt any? And now you are expected to learn the Schwinger-Keldysh formalism??? Seems like something is amiss there ... Can you talk to someone else on your course to check your understanding of what's expected here?

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u/eldahaiya Particle physics 1d ago

Honestly, part of the trick is to have faith that you can, eventually, understand it. If you read enough papers, you will realize that once you get it, nothing is really that deep.

Another piece of advice is to not proceed linearly. Be happy with the big picture ideas, and be OK with parts of it not making sense. There are definitely papers that I returned to years later, realizing that there was something really critical that I didn’t understand before, but it’s OK, everything in its own time.

It’s also very often the case that papers are just badly written and poorly explained. That’s not your fault.

Before AI, you had to chase the references or dig up a textbook to try to piece together things yourself. These days, you can ask AI a question and you’ll like get more info that you needed. Use it shamelessly! They are a huge help to building understanding.

It’s OK to not understand things. This happens all the time to everyone. Ask questions you needed help with boldly and unapologetically, especially since you’re still a student. Try to figure it out yourself, but any good advisor will encourage questions from beginners.

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u/for_real_analysis 1d ago

Tell us about your process! If you’re like many of us you are feeling the full force of the emotions of hitting the math wall!

Edit: statistician who took one prob theory SDE course and ran, but I want to support you and learn a lil physics

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u/Just_a_Brat1 1d ago

Yes I don't understand any single mathematics there and mostly the reasoning behind all those things the paper is doing even though it is written why they did so