I already know C#, I guess it’s time to learn Q#:

Microsoft today launched a preview version of a new programming language for quantum computing called Q#. The industry giant also launched a quantum simulator that developers can use to test and debug their quantum algorithms.

The language and simulator were announced in September. The then-unnamed language was intended to bring traditional programming concepts—functions, variables, and branches, along with a syntax-highlighted development environment complete with quantum debugger—to quantum computing, a field that has hitherto built algorithms from wiring up logic gates. Microsoft’s hope is that this selection of tools, along with the training material and documentation, will open up quantum computing to more than just physicists.

We are living in the future.

I’m not sure how to interpret the feelings this causes in me. I think it might be fear.

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Interesting.

What’s still an open question is whether useful-sized quantum computers are even possible, and if so, when they might appear. So far the largest I have seen is a few dozen qubits. The smallest useful (to run Shor’s algorithm on data too large for conventional machines) requires maybe 8000 effective qubits. With error correction, the raw number needed is at least 10x that, and possibly a much larger number. A difficult problem is to keep the system coherent; I don’t know how that difficulty scales with qubit count. Presumably it’s at least linear; for all I know it might be exponential.

“2017 D-Wave Systems Inc. announced on 24 January general commercial availability of the D-Wave 2000Q quantum annealer, with 2000 qubits.[178]” .

In ten years we went from 1 qubit test systems to 2000 qubits. At that rate we should be getting to 8000 about a couple months ago.

Yes, but quantum annealing is not quantum computation. It’s an approximation. And while exact answers obtained rapidly via quantum computation may be interesting, yet another way to approximate answers isn’t. For example, there are stories about “hard problems” that can supposedly be solved by quantum annealing, such as the Traveling Salesman problem. But they miss the fact that efficient heuristics — algorithms that come “close enough” — have been known for decades. And annealing delivers that, not the exact optimal answer, for $10M or so.

I spent a while reading the literature about that one. A lot of it is physics papers discussing experiments that try to show the machine is actually doing what it is intended to do.

On the 8000, I wasn’t talking about 8000 physical qubits. Also, I just got into an email exchange about this, where I was told that my numbers are actually much too optimistic. The “usual estimate” is that factoring a 2000 bit number (which is a bit too small to be interesting) would require, with error correction and other overhead, about 500 million qubits.

Ah. Interesting and thanks for the clarification.

I’ve been trying to read up on the subject. It’s seriously hairy. My Quantum Mechanics 101 from 40 years ago is very little help. A kind friend lent me his textbook “A gentle introduction to quantum computers”. I think I can recommend it, though I didn’t understand all that much. It’s by two MIT faculty; my suspicion is that it’s for a Ph.D. level course in the MIT physics department.

Anyway, my impression to date is that the distance between reality and marketing hype is larger here than usual in high tech.

Thanks for the info.

there are two hard problems in computer science. Cache invalidation, naming, and counting.

I see what you did there. 🙂

This is going to give new meaning to the term “Heisenbug”

The future is here, and I’m of two minds about it.

The future is here, but it keeps crashing.

🙂

Of course it crashes … its from Microsoft😬

I’m buying cat futures.

Live ones or dead ones?

Doesn’t know yet. Hasn’t opened the box. Waiting for Christmas.