Noisy Intermediate-Scale Quantum (NISQ) technology will be available in the near future. Quantum computers with 50-100 qubits may be able to perform tasks which surpass the capabilities of today's classical digital computers, but noise in quantum gates will limit the size of quantum circuits that can be executed reliably. NISQ devices will be useful tools for exploring many-body quantum physics, and may have other useful applications, but the 100-qubit quantum computer will not change the world right away --- we should regard it as a significant step toward the more powerful quantum technologies of the future. Quantum technologists should continue to strive for more accurate quantum gates and, eventually, fully fault-tolerant quantum computing.
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We're probably decades away from Shor's algorithm. Right now we're mostly dealing in the realm of "Noisy Intermediate-Scale Quantum" machines (NISQ). The abstract of this paper gives a good summary of where we're at: https://arxiv.org/abs/1801.00862
The "operating system" has little to do with accelerating that (outside of maybe cutting out some development cost + time), though in theory they can provide some algorithms and optimizations that minimize noise and decoherence.
There is no known useful application of current quantum computing (so-called NISQ, for Noisy Intermediate-Scale Quantum). It is an open question whether there is any, see https://arxiv.org/abs/1801.00862.
Hopefully we will see results way before we start breaking RSA. It looks like people are targeting applications in quantum chemistry [1]. Also, Dyakonov's criticisms are toothless, see comments here [2].
[1] https://arxiv.org/abs/1801.00862
[2] https://scirate.com/arxiv/1903.10760
For the skeptical, there are two quantum computing job tracks which can operate independently for the next while:
(1) The engineering and basic physics research necessary to build a real, working quantum computer of high enough quality (low error rate) and size (number of qbits) for real-world use. Scott Aaronson believes we won't have a sufficiently-advanced quantum computer to, for example, run Shor's algorithm against a real-world key size for at least 15 years.
(2) The development of quantum algorithms, error-correction schemes, cryptography, and as-yet-unknown use-cases; the implementation thereof in a large, well-designed software library; finally, the development…
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of education materials to ease onboarding of the existing software engineering workforce to quantum computing. Microsoft has an actual quantum software engineering job listed, at this very moment: https://careers.microsoft.com/us/en/job/503847/Quantum-Softw...
Now, it's completely possible that (1) just won't pan out and we'll never, ever have a quantum computer advanced enough to work on real-world problems, in which case all investment into both (1) and (2) will have been a complete waste. However, given that we have good reason to believe (1) will succeed, why should we put (2) on hold for the next 15 years? Do we really want to finally have a shiny new quantum computer, then not have anything to run on it?
For an overview of the current state of quantum computing and what we can do with current NISQ (noisy intermediate-scale quantum) computers, there's a good survey paper by John Preskill called Quantum Computing in the NISQ era and beyond: https://arxiv.org/abs/1801.00862
I'm a little worried about these companies over-hyping the current state of capability. For sure, this is an exciting time though, and I am certainly optimistic about the long-term prospects. Anyone interested would do well to read [0]
[0] https://arxiv.org/abs/1801.00862
Yes, there are two reasons that python is an ideal tool for quantum computing libraries at the moment.
- In the NISQ era [1], circuits have limited depth and size. It doesn't matter so much which language (or even algorithm!) you use when N<1000.
- Simulating a circuit is expensive, but all the heavy lifting can be delegated to highly optimized C code. The most expensive part of Cirq's simulation is (or soon will be) a call to `numpy.einsum` [2].
1: https://arxiv.org/abs/1801.00862
2: https://github.com/quantumlib/Cirq/blob/24638f234704686c4bb6...
In honor of Alan Turing's hundredth birthday, I unwisely set out some thoughts about one of Turing's obsessions throughout his life, the question of physics and free will.