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"Searching for a solution in a broad space" describes virtually every hard problem in computer science. For example optimization problems are everywhere. In pl
by bnegreve 10y ago
"Searching for a solution in a broad space" describes virtually every hard problem in computer science.
For example optimization problems are everywhere. In planning or in machine learning, just to name a few.
Having efficient ways to solve such problems would very definitely make a difference.
I agree that it's unlikely to happen anytime soon, though.
- lisivka 10y agoThe problem with analog computing was that they tend to oscillate or pickup noise which greatly limits their usefulness for precise calculations. With quantum computing, you will need to use series of runs and average them. For simple cases, it will be e.g. 10 runs, for complex cases you may need thousands or millions of runs. IMHO, it still will be faster (because quantum produces random values at mach faster rate than macrosystems), but (IMHO) efficient quantum algorithms can be reimplemented with electronic circuits, which will consume much less resources than general purpose quantum computer.
- bnegreve 10y ago> efficient quantum algorithms can be reimplemented with electronic circuits, You can emulate a quantum computer with a classical one, but it takes exponential time. If you could emulate them efficiently, quantum computers would just be another Turing machine, with all the limitations we already know. I think this is the whole point of quantum computers, they are different from what we already have.
- lisivka 10y agoI talking about analog computing, not about digital computing. https://en.wikipedia.org/wiki/Analog_computer https://en.wikipedia.org/wiki/Analog_computer