Quantum computing boils down to unitary matrix operations over complex space. It's very straightforward. But the way those pieces behave in more complicated systems and the emergent properties they give rise to can be studied... Scientifically.
Some of it will be encompassed by computer science in that algorithms will still have the same metrics, but there may be other metrics for which to study quantum algorithms.
Those probability distributions are typically represented as complex vectors and quantum gates as unitary matrix operations on those vectors.
Here's a quantum computer simulator [1] I wrote years ago that allows you to construct quantum circuits using the most common quantum gates found in literature. This is all done by the application of complex matrices. On the right there is the probability distribution that taking a measurement would result in.
Edit: It's worth noting that we can study quantum computing without a quantum computer, just as we can study computing without a classical computer.
Edit 2: Here's Grover's Algorithm in my simulator where you can see that the probability of measuring the correct "hidden" oracle value is 96% after only three applications of the diffusion operator: https://qcsimulator.github.io/?example=Grover%27s%20Algorith...
That isn't thinking about it very deeply. Boolean algebra was useful in either case. When people who are working in Quantum Computing are overwhelmingly motivated by the speed increases only possible with real quantum computers, if one never materializes, not that many people are going to be excited about algorithims for pretend quantum computers that run no faster than classical machines.
Furthermore, the bifurcation of computer science and electrical engineering hasn't been all that successful as an academic practice. UC Berkeley recently decided to leave the ABET accreditation process for EECS because they felt they can innovate on a better synthesis of the fields for the fields and students.
They're related, but computer science has nothing to do with how electrons interact in different materials. Not that it isn't useful for people to know how the lower level components actually work. For that matter, people building the lower level components will also be more useful knowing how they're used in the abstract level.
And similarly, studying QC in the theoretical form can also lead to discovery and understanding of quantum properties. Even if we have no fully-featured quantum computers.
Computers are a procedure, not an object. You can build a computer using people, paper, pencils, and a list of procedures to follow when particular instructions are given.
Computer science and the construction of computers are virtually the same thing. Making a computer was never a challenge; making a faster computer always is.
Some of it will be encompassed by computer science in that algorithms will still have the same metrics, but there may be other metrics for which to study quantum algorithms.