A new quantum algorithm speeds up a huge class of problems


Original version From This story Appeared in Quanta Magazine.

For computer scientists, solving problems is a bit like mountaineering. They must first choose to solve a problem – to identify a peak to climb – and then they must formulate a strategy to solve it. Classical and quantum researchers use different strategies to compete with healthy competition between the two. Quantum researchers report a quick way to solve a problem – often by scaling peak that no one thinks – classic teams compete to see if they can find a better way.

The race almost always ends as a virtual tie: when researchers think they have invented a quantum algorithm that works faster or better than anything else, classic researchers usually face it. Last week, a quantum speed, published in the journal Science, was met with urgent doubts from two separate groups that show how similar calculations could be made in classic devices.

But in an article published last year on the Scientific site of Arxiv.org, researchers explained that it seems to be a quantum speed that is both convincing and useful. The researchers described a new quantum algorithm that works faster than all the classics known to find good solutions for a wide -class optimization problems (looking for the best possible solution among many options).

So far, no classic algorithm has not eliminated the new algorithm known as the decoded quantum interference (DQI). “This is a success in quantum algorithms,” said Gil Kalai, a mathematician at the University of Richman and a prominent skeptical computation. Quantum algorithms reports excite the researchers, partly because they can clarify new ideas about difficult problems, and to some extent because for all buzz around the quantum machines, it is unclear which problems will actually benefit from them. A quantum algorithm that works better than all known classics in optimization work is a main step forward in inhibiting the potential of quantum computers.

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“I’m interested in it,” Ronald de Greg, the theoretical scientist at CWI, the National Institute of Mathematics and Computer Science in the Netherlands, who was not involved in the new algorithm, said. But at the same time, he warned that the researchers still could eventually find a classical algorithm, which would be done. And due to the lack of quantum hardware, it is still going to be able to experiment with the new algorithm.

According to Avyn Tang, a computer scientist at the University of California, Berkeley, this algorithm may inspire a classic new work, which was prominent as a teenager by creating classic algorithms that match a quantum. New claims “is interesting enough that I tell people to classic algorithms,” Hi, you have to look at this article and work on this problem. “

The best way forward?

When classic and quantum algorithms compete, they often do so on the battlefield, focusing on finding the best options to solve a wonderful problem. Researchers typically focus on problems in which the number of possible solutions explode as the problem grows. What is the best way for a delivery truck to visit 10 cities in three days? How to pack the packages on the back? The classic methods of solving these problems, often involving possible solutions in clever methods, are rapidly unbearable.

The specific optimization problem that DQI is dealing with is almost: You are given a set of points on a sheet of paper. You have to provide a math performance that passes through these points. In particular, your performance should be a polynomial-a component of the variables raised to complete agents and minted by coefficients. But it can’t be too complicated, meaning that powers cannot be too much. It gives you a curved line that rotates up and down by moving on the screen. Your job is to find the Wiggly line that touches the most points.

Changes in this problem have been shown in different forms throughout the computer science, especially in error coding and encryption – – Fields focused on secure and accurate data encryption when transferring it. DQI researchers basically recognized that drawing a better line was similar to changing a noisy encrypted message close to its exact meaning.

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