I am a first year graduate student in a computational math program. Based on my background (I just finished a one-semester graduate real analysis course), instead of reading a specific textbook, my supervisor suggested me starting reading papers. And if I find unclear concepts, I can refer to some books in library, learn the specific knowledge and come back to the paper.

In general I agree with this method since I think this is the most effective way to learn a new technique, that is, applying the new knowledge directly to my research. But I am not sure what I should do if it's a pure math concept, instead of a numerical scheme. For example, say the existence of weak solution of a particular PDE. After reading the relavant chapter or chapters of a classic book which I borrowed from the library, should I try to do the exercise after those chapters before moving back to the paper? Based on the suggestions here, I should try to solve as many as exercises in that book to make sure I understand the theorems and techniques, and this is what I usually do in my undergraduate study.

But I have several concerns about this approach. Firstly, it may be time-consuming and may delay the research process. Secondly, unlike reading an undergraduate textbook, I started the reference book in the middle, while the exercises may require some previous chapters' techiniques, which I may not know and may not be directly related with my current research.

So may you share your experience about how to deal with this senario? Do you come back to the paper immediately (say after knowing the statement of a theorem) or do you spend some time solving exercises? If the exercises involving previous chapters' concepts, do you usually read previous chapters as well or do you just skip those exercises? I know it's good to learn more things, but given the time constrains and tons of things I need to learn, sometime it may not be practical.

4 Answers 4


I wanted to put in a word that mathematics really is hard and takes time to learn.

In particular, in my experience -- which is, I must say, almost exclusively with pure mathematics, but in many programs in the US the distinction between pure and applied only emerges later on -- relatively few first year math PhD students are reading papers independently. Unless I very much misremember, I did not start reading "serious" math papers until my second year. For what it is worth, I was a student at Harvard, and I entered with a BAMS from the University of Chicago. I was not poorly prepared compared to my American peers. Also for what it is worth, "one-semester graduate real analysis" is what I took as a third year undergraduate. And then I followed it with another semester. And by the way I was a student of number theory. As I recall I spent the first semester of my first year studying for my quals, passed them at the beginning of the second semester, and spent the second semester learning about elliptic curves, local fields and schemes from textbooks of Silverman, Serre and Hartshorne. The idea of plunging into papers without having learned this material: well, it might have added some drama, but almost certainly it would have added to my total time to degree.

I have very mixed feelings when I hear people on this site say things to early career graduate students like: "don't get too bogged down in any one thing"; "you can read textbooks forever; time to start reading papers"; "only spend as much time to learn something as is needed to apply it to your own work"; and so forth. It is not that such sentiments are not applicable in mathematics: I have said all of these lines myself. It is rather that in mathematics this kind of advice gets given out much later in the day: some of it is great advice for mid- and late-career grad students, and some of it sounds more appropriate for postdocs. On the other hand I have seen a lot of students -- including talented ones -- get snagged because they prioritize "their research" over basic learning. I did my PhD thesis on moduli spaces of abelian surfaces with quaternionic multiplication. I didn't know what any of those words meant as a first year PhD student.

Now I write all this knowing that the OP is in applied math, which depending on what that means could either be identical to the pure math experience, wildly different, or anywhere in between. But he is asking about pure math knowledge and seems to have the intuition that it will not come so quickly or easily. I think the most honest, helpful answer is: it does not come so quickly or easily to pure math students at top places. So if you're expecting it to come quickly and easily to you, then you're setting yourself up for disappointment. A certain amount of patient, textbook-driven linear learning will pay immeasurable dividends down the road. How much? Good question: that's what advisors are for.

Well, after all this I may as well take a crack at the precise question asked. Should you solve exercises in textbooks you read in order to gain background on your research? Sometimes. I think that whenever you're reading a math book and get to some exercises you should at least look over them and get a sense of how close you are to being able to solve them. This is an important clue to how much of the material has sunk in. On the other hand, how much time should you spend solving any one "problem set" when you're reading the text in "research mode"? Not very much unless you see how solving that particular problem is relevant to your work (in which case: lots of time, potentially). If you don't know whether the exercises are relevant to what you're doing, you either haven't read closely enough or are reading too linearly: you don't have to read textbooks in order or one at a time. Grab several off the shelf at once. Play them off against each other. Often what you actually need is something that most texts will hint at, drive somewhere near, leave to you as an exercise....but the right textbook will do it wonderfully. Or maybe no one text will say exactly what you want, but together they will. Being able to "triangulate from multiple sources" is, I would say, an intermediate research skill: I know many PhD students who don't seem to have mastered it (e.g. for complete lack of trying!), but it is one well worth developing if you're trying to dive head-first into the literature.

Good luck.

  • Thank you for your great sharing! I guess at this moment, I should spend some time learning from textbooks.
    – John
    Feb 25, 2015 at 7:03

You are definitely looking at the wrong factor here. The question for you should not be "Should I solve the examples?", but rather "Do I understand the technique well enough to confidently apply it to my own research?".

If the answer to the second question is yes, you don't need to waste your time on doing more examples. If the answer is no, you need to study the technique more before applying it, and doing the examples may or may not be a good way to do it. However, in the second case, doing the examples cannot be "too time-consuming", as you will need to spend more time on learning the technique anyway. At the end of the day, it isn't about "solving as many examples as possible", but about understanding the material well enough. As a young researcher, you should be advanced enough to tell when this is the case.

That being said, the way how you phrased the question makes me wonder to what extend you actually understand the technique. Specifically:

I started the reference book in the middle, while the exercises may require some previous chapters' techiniques, which I may not know and may not be directly related with my current research.

Of course one needs to know the concrete example to be sure, but if you are unable to do the examples because you have not read the previous text book sections, it seems to me that your understanding of the overall area is not all that great yet.

  • Thank you for pointing out my mistake. I will keep your advice in mind. As a first year graduate student, there are a lot of things I have to get used to. It seems the pace in graduate school is much faster compared with undergraduate study, especially for computational math program. There are some senior students who don't understand real/functional analysis well but start to write papers by implementing numerical simulations, which makes me wonder what I should do (while indeed, our thesis topics are different).
    – John
    Feb 24, 2015 at 7:44
  • Btw, what I want to learn from the reference book is functional analysis but that book's exercises involve a lot of convex analysis, which is introduced in previous chapters.
    – John
    Feb 24, 2015 at 7:45
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    @JohnZHANG I often just try to work out simple examples I come up with myself, but perhaps you should try looking at other books for more useful exercises/examples.
    – Kimball
    Feb 24, 2015 at 10:28
  • The only way of knowing if you indeed understand a math concept is to do the exercises. It's REALLY hard to judge your own ability in pure math without doing the dirty work.
    – aussetg
    Jul 9, 2015 at 8:11

It depends in your learning process. My philosophy is in general:

*To be able to say that you understand something, you need to be able to code it.*

This leads me to code lots of things in order to fully understand them. While it seems time consuming, once I have code it I realised that I do understand a lot of the high end research in the field and It saves me a lot of time that would be spent into trying to understand each specific paper using the technique I coded (or variations).

However, you can not code everything. There are THOUSANDS of methods in each field. My recommendation: Solve the textbook problems that will be relevant to your work, the ones that you are going to use/modify.

  • 2
    This approach might seem more time consuming but I prefer it to doing examples because it has an objective stopping point and it forces me to clarify my understanding. I know I understand a technique when I can make the program do it. Afterwards if I need a refresher I have the program as notes, written in exactly the way that made sense when it was last clear to me. If I'm doing examples until I feel good about it there's always the risk that I'm rushing, being lazy, over estimating the problem, etc. If you can't program spreadsheets make a good substitute.
    – gunfulker
    Feb 24, 2015 at 18:42
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    @gunfulker Yes indeed. Once you have coded the discrete Fourier transform (for example) you really know that you understand the problem and will probably never get stuck in a problem that may arise from it. Feb 25, 2015 at 9:05
  • 1
    Coding something is very different from proving mathematical problems, e.g matrix multiplication is easy to code, but give no insight about properties of linear application composition. Feb 4 at 10:32

instead of reading a specific textbook, my supervisor suggested me starting reading papers. And if I find unclear concepts, I can refer to some books in library, learn the specific knowledge and come back to the paper.

This is how you learn to read papers. When you first start, there will be several gaps as your undergraduate classes couldn't prepare you for every grad-level sub-field there is. You can fill in the gaps with reference books, your advisor, or other knowledgable students.

Don't worry about missing something out of one of the reference books. Either you'll notice it when a paper makes a claim you don't understand (will be common at first), or your advisor will realize you do not understand it.

Focus on understanding the papers you read. There is no way anyone would have time to read multiple text books and keep up in grad school. It feels overwhelming at first, but stay focused, and it will get MUCH easier.

  • 1
    Thanks for your advice. May I know whether your advice is also applicable to applied math program? I always have a feeling that math students (especially pure math students) should learn enough fundamental theories before reading papers. But I gradually realize that my knowledge can never be "enough" and as an applied math student, time doesn't allow me doing that. So usually how to determine whether a student is ready to read papers? Is being able to pass qualifying exam is the criterion?
    – John
    Feb 24, 2015 at 16:37
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    My area is CS, but I would bet its cross-discipline. There is no way you can be prepared to read papers by a general curriculum. Part of the grad-school (and quals) process is learning how to "drink from the fire hose" so to speak. Feb 24, 2015 at 16:47

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