December 16, 2020 | Written by: Yuri Kobayashi
Categorized: Quantum Computing
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What does programming for the not-so-distant quantum future look like?
From November 9 to 30, more than 3,300 people from 85 countries applied for the 2,000 seats of the IBM Quantum Challenge to find out.
As our cloud-accessible quantum systems continue to advance in scale and capability with better processors of larger number of qubits, understanding how to implement complex data structures become crucial to us in order to harness the potential of our future quantum systems.
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!
Read an example solution, written by the author of the final exercise, IBM Quantum’s Atsushi Matsuo, here
Meet the top 10 scorers of the Quantum Challenge
Our winner, 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. Please check out the beautiful solutions from our top scorers here.
Top ten scorers of the IBM Quantum Challenge Fall 2020
Scores were determined by measuring the circuit implementation cost to solve the final exercise. Cost is defined as: Cost = S + 10C, where S is the number of single-qubit gates and C is the number of CNOT (CX) gates. Any given quantum circuit can be decomposed into single-qubit gates and two-qubit gates. With the current Noisy Intermediate-Scale Quantum (NISQ) devices, CNOT error rates are generally ten times higher than a single qubit gate. Therefore, we weigh CNOT gates ten times more than a single-qubit gate for evaluating the circuit implementation cost.
From beginner to expert in three weeks
Perhaps the most rewarding experience organizing an event like the IBM Quantum Challenge is to see how much people can learn something new and grow in such a short time. Many people started out as beginners coming into this challenge, yet emerged achieving great levels of experience and skill from tackling the problem sets and learning from their peers.
Our survey results indicate that on the scale of 1-10, most people started out as beginners in quantum computing and Qiskit – identifying themselves between 1 and 3. But after the challenge, identified their level as a 5 or 6.
Quantum starts here