Meet our Quantum Hackathon Winners

9 April 2018

by Ryan Karle

This past weekend we hosted our first-ever quantum computing hackathon, drawing attendees from right here in Berkeley and as far away as Osaka, Tokyo, Basel, Toronto, Melbourne, London, and more. Participants ran the gamut, from researchers at national laboratories, to professors, to hobby quantum programmers, to high school students.

19 teams presented their work to our panel of judges: Zavain Dar, investor at Lux Capital; Daniel Mulet, program director at the Creative Destruction Lab in Toronto; John Morton, professor of nanophotonics at University College of London; Guen Prawiroatmodjo, software engineer and physicist at Rigetti; and Eleanor Rieffel, senior research scientist and lead at NASA’s Quantum AI Lab (QuAIL). Projects included everything from games powered by the quantum computer to implementations of quantum information theory papers, like Kosuke Mitarai’s work on Quantum Circuit Learning. In the end, three teams took home a prize (a UV photolithography mask used to make our quantum chips):

  • Best expert project: Hannah Sim and Jhonathan Romero (from Zapata Computing & Harvard), Eric Brown (from Creative Destruction Lab & University of Waterloo), and Evan Anderson (from University of Colorado-Boulder): A quantum autoencoder for effective compression of quantum data. The team built on top of Jhonathan’s work at Harvard (see the paper here).
  • Best newcomer project: Jordan Sullivan, Timo Joas, James Chen, Daniel Lengyel, Vladimir Kremenetski, and Dhruv Devulapalli (from UC Berkeley): Number recognition using a quantum computer.
  • Most creative project: James Wootton (University of Basel), Jonathan DuBois (Lawrence Livermore National Laboratory), and M. Sohaib Alam (Valor Water Analytics & UT-Austin): A collection of mini games for quantum computers. The team drew inspiration from some of James’ past work to create three awesome games that used our quantum computer.

We’ll be sure to have more of these in the future. Join the community for updates!

Originally published at rigetticomputing.github.io on April 9, 2018.