General background: Quantum computing (theory) is at the intersection of math, physics and
computer science. (Experiment also can involve electrical engineering.) Eventually you
will want to learn aspects of all of these fields, but when starting you can use any for
an entry into the field. Within each field, the subjects you will want to know are:
General quantum computing texts:
Here is a very partial list of resources for learning more about
quantum computing and quantum information.
- Physics: First learn quantum mechanics. At more advanced levels, various
aspects of quantum information overlap with AMO, condensed matter and high energy.
- Math: First linear algebra and probability. Later my preferences would be
to learn some group and representation theory, random matrix theory and functional
analysis, but eventually most fields of math have some overlap with quantum information,
and other researchers may emphasize different areas of math.
- Computer Science: Most theory topics are relevant although are less crucial
at first: i.e. algorithms, cryptography, information theory, error-correcting codes,
optimization, complexity, machine learning. If you haven't had any CS theory exposure,
undergrad algorithms is a good place to start because it will show you CS-theory ways of
thinking, including ideas like asymptotic analysis.
The canonical reference for learning quantum computing is the textbook Quantum
computation and quantum information by Nielsen and Chuang.
Another good book (with more of a "little yellow book" experience) is
Classical and Quantum
Computation by Kitaev, Shen and Vyalyi.
Online resources: There are also great free resources online.
If you want to get a flavor of what research is currently hot, then
one place to look is at the program of the last few QIP workshops. A less curated list
of interesting papers can be found at scirate.com, where looking at the
most scited papers in the last year should bring up some interesting
Some more specialized books/lecture notes are here. These are more modern and in-depth
than the general resources above.
If you have more resources to suggest or any comments on this page,
then please email me at email@example.com.