(IBM.QuantumBlog) From November 9 to 30, 2020, more than 3,300 people from 85 countries applied for the 2,000 seats of the IBM Quantum Challenge to find out what does programming for the not-so-distant quantum future look like?
During the three-week challenge, participants learned how to implement complex quantum data structures using qRAM and design a quantum game solver using Grover’s algorithm. The combination of qRAM and Grover’s algorithm has many practical applications in solving real-life problems on our future quantum systems in areas of quantum machine learning and complex decision making problems.
Participants were presented with a new set of exercises each Monday during the challenge, which became progressively more difficult each week. Of the 2,000 participants, 1,091 were able to solve at least one of the first week’s exercises, 576 were able to solve at least one of the second week’s exercises, and 227 were able to successfully solve all of the exercises, including the final, most-challenging exercise!
who was not only one of the 227 who completed all of the exercises, but also achieved the lowest quantum cost in solving the final exercise is University of Tokyo undergraduate student, Hironari Nagayoshi. He achieved the lowest quantum cost by applying a strategy based on exploiting the unique traits of the problem’s constraints. You can find his solution, here. (link directly to Hironari’s solution notebook) which includes commentary on his approach and strategy. Very impressive. Congratulations Hironari!
We were amazed by the ingenuity and creativity of the scorers who came up with brilliant solutions to the final exercise. As one of our participants described in his tweet, one of the best things from the IBM Quantum Challenge is the special opportunity to see how beautifully others think. Click here for solutions from top scorers.

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