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posted by spiraldancing on Tuesday February 11 2020, @03:35PM   Printer-friendly
from the Tyranny-of-Moore dept.

A team of researchers affiliated with several institutions in China created a photonic computer that was able to solve the subset sum problem. In their paper published in the journal Science Advances, the group describes their computer and how well it performed.

[...] In this new effort, the researchers propose the idea of a photonic computer by creating one that can solve the subset sum problem.

The subset sum problem [...] is easy for a conventional computer when the list is small—but when it grows large, it becomes unworkable.

To solve the problem using a photonic computer, the researchers mapped it into a 3-D waveguide network etched onto glass using a femtosecond laser. Photons were then allowed to dissipate into the network in search of a solution in parallel. This allowed the researchers to try different combinations at the same time rather than grinding through them all, as is done with a conventional computer. Not only did the approach work, it was able to do so faster than a supercomputer—and it demonstrated that photonic computers are capable of solving such problems and are scalable, as well.

More information: Xiao-Yun Xu et al. A scalable photonic computer solving the subset sum problem, Science Advances (2020). DOI: 10.1126/sciadv.aay5853


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  • (Score: 2) by FatPhil on Tuesday February 11 2020, @04:27PM (1 child)

    by FatPhil (863) <{pc-soylent} {at} {asdf.fi}> on Tuesday February 11 2020, @04:27PM (#956882) Homepage
    The Big-Oh for this technique is exponential in the size of the input, in space.
    You've traded exponential time or space (the choice is yours) for guaranteed exponential space.
    That's not a win.
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  • (Score: 2) by bzipitidoo on Tuesday February 11 2020, @08:15PM

    by bzipitidoo (4388) on Tuesday February 11 2020, @08:15PM (#956949) Journal

    Seems the headline should have been "Massively parallel computation achieved with photonics", then in the article, they note that it was used to solve large instances of the Subset Sum problem, which is NP-complete. Why, yes, NP-complete problems are easy if one has unlimited parallelism available.

    Wonder how far this scales? Enough to factor huge numbers of the 5000 bit variety?