Let me start off with a description of my background. I am an undergraduate student, with some background in real analysis (Rudin, Principles of Mathematical Analysis), measure theory (Royden, Real Analysis: Parts I and III) and a little functional analysis (first five chapters of Rudin's 'Real and Complex Analysis'). I know no geometry, beyond Loring Tu's 'Introduction to Manifolds'. Additionally, just to give you the entire picture, I have an algebra background from Dummit's and Foote's 'Abstract Algebra', until but not including the section on Galois Theory. I also know a little spectral theory from William Arveson's 'A Short Course in Spectral Theory'.

I recently took a course on ordinary differential equations, where we followed a combination of Arnold's 'Ordinary Differential Equations' and George Simmons's 'Differential Equations with Applications and Historical Notes'. I liked the course, and decided to study partial differential equations from Evans's 'Partial Differential Equations'.

I would like a roadmap that answers the following questions:

  1. What related areas of math would I need to know to understand research-level papers in the subject? Here, I understand that there could be many frontiers of the subject, each requiring its own set of prerequisites. I am looking for an answer that explains what exactly the area of research aims at doing and what the prerequisite content to work in that area would be. If certain things are required only in parts as prerequisites, I would very much appreciate it if you could name the theorems or the sections of books I would have to read.

  2. What could I read immediately after reading Evans? I've heard that Michael Taylor's three volume series is good, and plan on taking a look at that, but more well-directed (as in, towards a specific sub-area of research) recommendations would be appreciated.

  3. If you could estimate the time it would take (on an average) to study the material you suggest, especially if it isn't a book that mentions that, I would appreciate it, since it helps to know whether I am rushing through things (in which case, I often remember nothing later) or am going too slowly (in which case, I will try seeking help from some more advanced students or a professor).


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    $\begingroup$ I have the feeling that the questions ask about too much detail. The only answer I know is: find an advisor and ask them. $\endgroup$
    – Dirk
    Commented May 4, 2019 at 9:19
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    $\begingroup$ True. But I think giving a partial answer or answering in less detail is certainly appropriate (and welcome) here $\endgroup$ Commented May 4, 2019 at 12:23
  • $\begingroup$ My advice is to read randomly. It's early in your studies, so you don't need to know what to focus on. Skim through papers on PDEs posted on arxiv. If you find something that intrigues you, try reading the paper. Chances are that you won't get far (but if I'm wrong, that would be great). So you go backwards and figure out where to learn the background to the paper. If you find yourself really getting into something, then focus on that and dig deeper. Otherwise, just randomly graze around. Even that will pay off later. $\endgroup$
    – Deane
    Commented Apr 16, 2021 at 23:49

1 Answer 1


PDE is VERY broad. It will be virtually impossible to answer this question in any generality. I heartily second the recommendation that you read Taylor's three-volume treatise. He really emphasizes the microlocal viewpoint, which is hugely useful in many areas of PDE, and it's a good contrast to Evans. As an aside, Michael Taylor is in my department and that man's knowledge about PDE is truly encyclopedic.

Now, I'll try to address your actual question a bit. If you've REALLY studied Evans, you should be equipped to start dipping your toes into the research literature. Along the way you should also start to get some ideas about what sorts of problems interest you. You could simultaneously begin looking at interesting articles while working your way through new material in Taylor. From there, I would decide what sorts of other "prerequisites" are needed based on the articles you're reading. In my opinion, this is a much more efficient path to studying research-level mathematics than first attempting to gather all of the possible prerequisite knowledge (if the latter is even really possible).

I'll give an example path by way of anecdote. For my MA thesis, I studied a problem related to the Alt-Caffarelli-Friedman functional. I began by working through the relevant portions of Evans (Laplace's equation, Sobolev spaces, second-order elliptic equations and calculus of variations). After that, I jumped right into reading the Alt and Caffarelli paper on the one-phase problem and other relevant research literature (Alt-Caffarelli-Friedman, Littman-Stampacchia-Weinberger, etc). Along the way, I had to take some detours into some particular functional analysis and a healthy dose of geometric measure theory.

To summarize, research in PDE is a huge subject and draws tools from all over mathematics. This will particularly depend on the problem you want to study. Rather than obtaining all of the possible prerequisite knowledge first, it's much better to (1) obtain some basic pde knowledge (Evans + Taylor would do it), (2) begin reading interesting research, (3) identify where your prerequisite knowledge is lacking for the particular problem at hand and then (4) do the necessary prerequisite study (you can often look to the references of the paper you're reading to find good resources for this).

Regarding the timeline: I would say that if you're ready to start studying Evans, then you could be ready to start dipping into research math within a semester or maybe a year (depending upon how quickly you move, how selectively you read, etc).

For the sake of completeness, I want to add a few specific "prerequisites" that have been useful in my corner of the PDE world (assuming the basics as given). Your mileage will vary depending on where you go in PDE.

(1) Harmonic analysis - Littlewood-Paley decomposition, various multilinear estimates and analysis, Fourier analysis, etc. Stein's Harmonic Analysis is great for this material. Additionally, I'd recommend the two-volume Classical and Multilinear Harmonic Analysis by Muscalu and Schlag, as well as Wavelets: Calderón-Zygmund and Multilinear Operators by Coifman and Meyer.

(2) Microlocal analysis - pseudodifferential operators, paradifferential operators and paraproducts, frequency localization, the notion of the wave front set and more. For this material Michael Taylor has some wonderful references: Volumes II and III of his PDE text, Pseudodifferential Operators and Nonlinear PDE, Tools for PDE). Para-differential Calculus and Applications to the Cauchy Problem for Nonlinear Systems by Métivier is a great, standard reference for paradifferential calculus. Hörmander's four volumes are great, of course. Finally, I'd point out: Pseudodifferential Operators and the Nash-Moser Theorem by Alinhac and Gerard, the Coifman-Meyer book I mentioned earlier has some good material on paraproducts and paradifferential operators and Microlocal Analysis for Differential Operators by Grigis and Sjöstrand.

(3) Geometric Measure Theory - theory of rectifiable curves, sets of finite perimeter and so on; the notion of an approximate normal and an approximate tangent space; the notion of blow-up limits; regularity theory of minimal surfaces; and plenty more. Geometric Measure Theory by Federer is a classic reference. Also, Minimal Surfaces and Functions of Bounded Variation by Giusti. Simon's lecture notes are good as is Maggi's Sets of Finite Perimeter and Geometric Variational Problems.

  • $\begingroup$ Know next to nothing about PDE & my in my info is outdated, but Evans pointed out (pre-book) there seems to be a divide in PDEs between linear and N-linear PDEs. The big technology like microlocal analysis (FIO, $\psi$do's) have been more successful with LPDEs. With NLPDEs one keeps modifying proof techniques to attack new problems (eg. PL Lion etc..). So if you like big theories, turn to microlocal analysis; if you prefer specific examples, look at NLPDE in Lion, Evans etc. (3) Evans/Gariepy & F. Morgan have intros to geometric measure theory. Other perspectives-B.Malgrange,SatoKawaiKashiwara $\endgroup$
    – p.co
    Commented Apr 30, 2021 at 18:59
  • $\begingroup$ @p.co There certainly is a HUGE difference between linear and nonlinear pde. However, though microlocal analysis grew out of the study of linear pde, it is highly useful for nonlinear pde. For example, the paraproduct and paradifferential operators have been hugely successful in nonlinear pde. One example, among many, is the study of the local well-posedness of the water waves equations (Alazard-Burq-Zuily, etc). $\endgroup$
    – Gary Moon
    Commented Apr 30, 2021 at 19:19

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