How is computer science and physics related? Not sure if this is a 'real' question, but what is the relationship between physics and computer science? A lot of physicists are also computer scientists and vice versa. My professor has a PhD in Physics but is a Computer Scienctist. What's the relation? Why is this so common?
 A: I think the main reason why this is so common is that many people who are of the tenured professor age now (50-60) were in graduate school before most colleges offered a Ph.D. in computer science.  So back then, people who were interested in theoretical computer science got their doctorate in Mathematics, and people who were interested in applied computer science got their degrees in a field of the natural sciences.  Since physics offers the most readily answerable questions computationally, particularly with the computational power available in the 1950s and 1960s, many applied computer scientists ended up in physics programs.  When schools began to offer full bachelor's, master's, and doctoral programs in computer science, these people returned to their first love.  (I gathered most of this from talking to a CS professor I had in undergrad who followed exactly the same path you describe.)  I'm pretty sure there are a lot more physics Ph.D.s in computer science professorships than vice versa (even though I'm sure there are exceptions, and I'll get several comments pointing this out).  I realize there is a lot of overlap between the two fields, but if you want to know the real reason what there are so many professors in CS from physics, this is why.
A: From my reasoning and knowledge of one CS professor who has a PhD in astronomy:


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*Above all, the answer depends on your definition of what a "computer scientist" is.


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*What do you mean by "computer scientist"? Someone who does research in a computer science department? Or does perhaps artificial intelligence, algorithm development, or grid computing for a commercial company?

*Or do you mean people who study the same thing a "pure" computer scientist might, but in a different setting (perhaps biology or physics)a 


*The last part is ambiguous: You probably mean "Why is this [physics doctorates doing computer science] so common?", but it could also mean "Why are CS professors with degrees in physics so common?


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*The computer science professor I mentioned above described learning the cost of bugs in a program: They (the astronomy graduate students) would write a complex program, a Fortran simulation of the sun's core, and print it on punched cards. They would then take the shoe-box of cards (all in a specific order!) to the computer desk, which was located in a "bunker" underneath the main building of the university. Perhaps a few days later, they would come back to receive the output of their queued program. If there was anything wrong with the output (perhaps it halted on an error, what a shame), they would have to go through their entire program to figure out what went wrong. Thus, they learned to meticulously debug their program on paper (really the only way, at the time, I suppose, since they could only use the mainframe) and "run" the program in their head.

*However, this professor (technically a lecturer) "only" teaches: first- and second-semester Java, a web development class, a course on building computers (sigh, I think you used to get to keep your build), and an introductory databases class. So, if we are talking about professors (loosely), their background will probably determine what kind of classes they teach.
A: First off, physics tends to provide a very good background for people who move on to study problems in other areas, which is perhaps why there is a lot of cross-over to computer science.
However, there are also a number of areas at the interface of computer science and physics which attract people from both sides:


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*Computer hardware (which is generally based on semiconductor physics).

*Large scale simulations

*Physics of computation (Quantum computing, reversible computing, etc.)

*Theoretical computer science
etc.


Of these, perhaps the last one (TCS) seems the most surprising. However, in recent years, there has been significant success in applying ideas from thermodynamics and statistical mechanics to problems in computational complexity. An example of this would be the simulated annealing algorithm which works extremely well for optimization problems, as well as work done on phase transitions in 3SAT.
A: I have an M.Sc. in CS and an M.Sc. in Physics (astro), from my experience the intersections usually originate in (at least) two areas.
First, in many fields of Physics, experiments and simulation produce large quantity of data, eg. SDSS (dataset is many TBs), Pan-Starrs (will produce TB/day) in astrophysics, large colliders such as LHC in particle physics (producing 1PB/s). When dealing with the storage and processing of such large datasets, physicists get involved with CS and some of us enjoy it.
Second, there's a field called "complex systems", such as spin glasses or stock markets, which can be modeled effectively on computers, hence the computer program becomes the experiment itself. Complex systems is an exciting field for physicists because fairly simple systems (eg. a pendelum) can produce very complex behaviour, they are relatively cheap to research (PCs are cheap, software is free), and they can be found in many fields of physics.
A: A lot of physical modeling can be done in computer programs. Physics is based on creating mathematical pictures of the way the universe works. Physics really builds on the logic that is integral to computer science.
I think this blog post sums it up nicely when it says, "Without algorithms there would be no Physics! Physics is built on the fundamental assumption that we can model the world using algorithms. Computer Science is the most fundamental natural science."
Blog post on Physics and Computer Science
A: A lot of things are common.


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*Physical processes can be thought of as a computation.

*Both fields exploit mathematics in very interesting way that is why it appeals to same people.

