This is paper was published in Nature last month [0]. It mainly focuses on machine learning algorithms for near-term universal quantum computers (tens to hundreds of qubits). It also talks about machine learning algorithms for quantum annealers like D-Wave's.
Your GitHub account [0] gives Common Lisp some love. Why did you choose to use this language? Specifically, for the implementation of your Quantum Virtual Machine?
Linear Algebra is very important for Quantum Computing. You have a masters in engineering, so you shouldn't have any problems with the math. I suggest you review the basics of Linear Algebra if you haven't applied that knowledge in a while.
John Preskill's lecture notes are invaluable. They start from the basics of Quantum Computing, to Quantum Theory, all the way to advanced concepts such as Topological Quantum Computation:http://www.theory.caltech.edu/people/preskill/ph229/
These will be enough to get you started, but it is good apply your knowledge by implementing the quantum algorithms that you have learned.There is a huge list of simulators you can use:https://www.quantiki.org/wiki/list-qc-simulators
I know you want references to open courses, but reading papers shouldn't hurt either. I don't know how much experience you have with Quantum Mechanics, but this paper:https://arxiv.org/abs/0708.0261 explains Quantum Computing very well by referring to concepts in Classical Computing. You should read this first if you are not familiar with Quantum Mechanics.
Let me know if you have any questions and good luck!
Good point. NIST has a list of 50 or so algorithms that will provide speedups when implemented on a Quantum Computer:http://math.nist.gov/quantum/zoo/.
I made a compiler for IBM's Quantum Computer:https://github.com/vtomole/aubree. It's my most impressive hackathon project because it's the only one that I still work on post-hackathon.
The way I understand it, non-abelian anyons, which are the anyons that can be used to build a universal quantum computer have not been found yet. Correct?
This is a really great idea! Reminds me of other projects that are working on integrating IPFS with the Operating System: https://github.com/vtomole/IPOS
I wasn't able to find anything about Google's Numerics flow. Would you provide a reference?
> Anybody else active in this field?
Yes. Rigetti Computing has also been working in this area. https://medium.com/rigetti/rigetti-partners-with-cdl-to-driv...