QHack—the quantum machine learning hackathon
Part hackathon, part fan expo, part scientific conference, QHack offered a new kind of experience in the quantum space. Like all the best events, it had a teaser trailer, a vintage poster, its own theme music (imagine Daft Punk remixed the Knight Rider intro music), and a top-notch swag game.
Participants from more than 85 countries tested their skills against one another to claim the top spots on the leaderboard. At stake was more than bragging rights: top teams could unlock a share of $100k in credits for quantum computing platforms, early access to unreleased services, and internships at a world-famous scientific lab.
Organized by Xanadu and sponsored by major players in the quantum space like AWS, Sandbox@Alphabet, CERN Quantum Technology Initiative, IBM Quantum, Rigetti, and Google, QHack 2021 is Xanadu’s second QHack event (after QHack 2019), this time taking place entirely online.
QHack at a glance
- 35 hours of live streams with over 13,500 views
- 2650+ registered participants
- 400+ active teams
- Participants from 85+ countries
- 100+ swag packs shipped all over the world
QHack live streams
The event kicked off with three jam-packed days of quantum machine learning talks featuring an amazing line-up of guest speakers from across the quantum industry (see bottom of this post for links to the talks). As the synthwave theme should make immediately clear, QHack isn’t your usual academic event.
Our guest speakers treated us to their latest scientific and technical insights, then sat down with our hosts for more in-depth personal interviews. We heard stories about their journeys through academia and industry, meeting scientific celebrities, Dungeons & Dragons, how to use social media, mountain biking adventures, and karaoke catastrophes. Viewers were also treated to a quantum musical composition and a PennyLane-themed standup comedy act. With its first-ever stream, QHack ranked 2nd for total viewers in the Science and Technology Category on Twitch.
Fun fact: immediately after watching the QHack live streams, the French electronic music group Daft Punk famously called it quits, knowing it was time to pass on the torch to a new generation of creators. [*citation needed*]
QML Challenges
Running in parallel to the QHack live streams were the QML Challenges. Participating teams raced to solve 12 different quantum machine learning programming challenges across four categories: circuits, optimization, gradients, and variational quantum eigensolvers (VQE). Teams that placed in the top 80 would unlock credits that they could use for accessing quantum hardware and simulators on Amazon Braket. In a surprise bonus announcement, the top 50 teams were also granted first-ever alpha access to Sandbox’s quantum simulator Floq.
The competition was intense! There were 400 active teams tackling the challenges, and by the end of QHack, 57 teams had completed every single problem, achieving a perfect score.
QHack Open Hackathon
Finally, the event was capped off with a week-long hackathon. Having levelled up their skills on the QML Challenges, teams put themselves to a new test. To succeed in this open-ended hackathon, teams had to combine a great idea with swift execution and a polished pitch. At the mid-week point, the teams with the most promising projects could also unlock an extra Power Up: $4000 in AWS credits to execute their hackathon ideas directly on quantum hardware. The top team at the end of the event could claim prestigious summer internships at CERN.
The Open Hackathon had a lot of interesting, thought-provoking, entertaining, and even off-the-wall project submissions (38 in total). Teams hacked a Quantum Chess Engine, tackled high-energy physics problems with QML, explored variational language models, and composed “Qountry” songs. They traversed barren plateaus, generated data with Quantum GANs, extended current QML models with new features, and composed quantum musical scores. You can check out all of the submissions at the QHack 2021 GitHub repo. Thanks to all teams for participating!
And the winners are…
With so many hackathon projects, it was a challenge to choose a final winner. But three teams rose above the rest to claim a spot on the podium:
Third place:
Many body system, Quantum Optimal Subarchitecture Search (QOSE)
Aroosa Ijaz, University of Waterloo & Vector Institute
Jelena Mackeprang, University of Stuttgart
Kathleen E. Hamilton, Oak Ridge National Laboratory
Roeland Wiersema, University of Waterloo & Vector Institute
Yash Chitgopekar, University of California, Santa Barbara
Second place:
Entangled_Nets, Event Classification with Layer-wise Learning for Data Re-uploading Classifier in High Energy Physics
Eraraya Ricardo Muten, Quantum Technology Laboratory, Bandung Institute of Technology
Togan Tlimakhov Yusuf, Department of Electrical and Electronic Engineering, Ankara University
Andrei Voicu Tomuț, Faculty of Physics, Babeş-Bolyai University Cluj-Napoca Romania
First place:
Notorious FUB, Trainable Quantum Embedding Kernels with PennyLane
Peter-Jan Derks, Eisert Group at Freie Universität Berlin
Paul K. Faehrmann, Eisert Group at Freie Universität Berlin
Elies Gil-Fuster, Eisert Group at Freie Universität Berlin
Thomas S. Hubregtsen, Eisert Group at Freie Universität Berlin
Johannes Jakob Meyer, Eisert Group at Freie Universität Berlin, QMATH at University of Copenhagen
David Wierichs, Gross Group at University of Cologne
Congratulations to the top teams!
Thanks again to both our sponsors and our participants for making QHack 2021 such a success and helping it become a signature event in the quantum space. See you at the next QHack!
QHack 2021 talks:
Maria Schuld (Xanadu): Quantum Differentiable Programming
Nathan Killoran (Xanadu): Training quantum computers: An introduction to PennyLane
Christa Zoufal (IBM Quantum): Quantum Gradients
Josh Izaac (Xanadu): Quantum Differentiable Programming with PennyLane
Patrick Coles (Los Alamos National Lab): How to design a Variational Quantum Algorithm
Alejandro Perdomo-Ortiz (Zapata Computing): Enhancing Machine Learning and Optimization with Quantum Generative Models
Ben Bartlett (Stanford University): How to Train Your Photons: Adventures in Optical Machine Learning
Cedric Lin (AWS): Getting started with quantum computing on Amazon Braket
Amira Abbas (IBM Quantum and University of KwaZulu-Natal): The Expressibility of Quantum Machine Learning Models
Leonardo Banchi (University of Florence): Training and Testing: A Quantum Information Perspective
Will Zeng (Goldman Sachs and Unitary Fund): Faster Quantum Derivative Pricing with Variational Compilation
Sukin (Hannah) Sim (Harvard University): How to Optimize Parameter-Heavy Quantum Circuits
Marco Cerezo (Los Alamos National Lab): Trainability and Barren Plateaus in Quantum Neural Networks
Jules Tilly (Rahko and University College London): Quantum Machine Learning and AI Prospects in Drug Discovery
Guillaume Verdon (Sandbox@Alphabet): Research & Tooling for Quantum-Probabilistic Generative Modelling & Beyond
Jakob Kottmann (University of Toronto): Orbitals, Fermions and Gradients: Getting started with Tequila
Sofia Vallecorsa (CERN): Quantum Machine Learning in High Energy Physics: Examples from CERN
Vishal Sharma (Entropica Labs and Ludwig Maximilian University of Munich): Quantum Circuit Born Machine with Qubit Recycle
Alba Cervera-Lierta (University of Toronto): Please, Feed the Quantum Troll
Balint Koczor (University of Oxford): Exponential Error Suppression and Quantum Analytic Descent
Eduardo Miranda (Plymouth University): The Dawn of Quantum Computer Music: A Natural Progression
Eric Kessler (AWS): Learning Quantum Machines: PennyLane and Amazon Braket
Murphy Niu (Google): Machine Learning at Google Quantum
Roger Luo (University of Waterloo and PIQuIL): Yao Framework — Quantum Computing in Julia Language
Juan Miguel Arrazola (Xanadu): PennyLane: The Untold True Story (Comedy Show)
