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warplants t1_ist5dor wrote

Reply to comment by upyourego in Rolls-Royce says a combination of quantum compputing and classical computing is likely to be in use for at least a decade before pure quantum takes over. The company is working with Classiq to create hybrid algorithms to speed up simulations for fluid dynamics and new materials. by upyourego

> over time they'll become more useful until they can beat out supercomputers.

Completely wrong. Quantum computers can never, even in principle, be faster than conventional computers for 99.99% of computing tasks. Quantum computers only might have an advantage for a very tiny subset of computing problems.

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upyourego OP t1_ist6t9c wrote

I was over simplifying - but yes I agree their use is limited to certain problems - but for the industries where they are useful the change will be substantial.

Also abstraction layers like those developed by Classiq can increase the number of usable applications

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leaky_wand t1_istciam wrote

Wouldn’t the applications follow the tech though? Maybe the applications are so limited today because engineers recognize brute force methods as inefficient and solve them via classical computing methods instead. If future computing problems are crafted to become structured more like quantum computing problems (evaluating millions of potential possibilities vs. attempting to craft a single solution up front), it seems there are a lot of applications possible.

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warplants t1_istgc1j wrote

Here’s the problem with quantum computing: yes you’re simultaneously evaluating countless potential “possibilities”, but at the end the QC only gives you the answer for one randomly chosen possibility. In that sense it’s far worse than just brute-forcing through every possibility with a classical computer, as at least with the classical computer you know which result corresponds with which possibility.

The sole advantage of the QC is that it can evaluate far more possibilities than can be classically brute-forced. But, again, when it spits out the answer, it erases the work done on all possibilities except the one randomly chosen by your measurement.

This means that at a minimum, you have to run the same problem many times on a QC to get a distribution of possible answers (since each individual answer is basically meaningless). Once you have a distribution, if you’re lucky you might see that certain solutions are more/less common that others, and this in itself may give you some insight to the problem you’re originally trying to solve.

TLDR computing anything with a QC is hugely inefficient compared to classical compute, the only problems you might even consider for a QC are those that simply can’t be classically computed in human timescales.

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