QC Hack 2022

QCHack highlights and the release of qBraid SDK

At this year’s QCHack, participants attended a week filled with amazing talks, 1:1 sessions with academic and industry mentors, and a 24 hour hackathon hosted by Stanford, Yale and Berkeley. The hackathon gathered much interest as 200+ hackers for the final hackathon to tackle challenges provided by Amazon, qBraid, IBM, Microsoft, and Qutech. For participants who wanted to compete in the qBraid challenges, they had the exclusive opportunity to use Amazon Braket and qBraid SDK integration to smoothly transpile any of their circuits written in Qiskit, Pennylane and other languages to Amazon Braket then run on simulators and real quantum computers.

About the SDK

The qBraid SDK, which is available on qBraid Lab, is the world’s first quantum computing circuit transpiler with over 40 possible frontend circuit permutations, which can also submit tasks to every major QC provider including Amazon Braket, IBMQ, Pyquil, and Cirq. Without the SDK, users would have to rewrite their code in each of the languages aforementioned, and run on the available backends.

Hackathon winners

Each team had the choice of three challenges: developing an OpenQASM Parser, creating a Grover’s Search algorithm for hamiltonian cycles, and using qBraid SDK to create Quantum Teleportation circuits on various backend. What really stood out was the participants eagerness to use the qBraid SDK, world’s first quantum computing language transpiler which smoothly converts quantum circuits between 5 languages (Amazon Braket, Qiskit, Pennylane, Pyquil, Cirq) and submits quantum jobs with little to no provider based setup. With each of the winning solutions, we were impressed by the extensions that were implemented upon the basic challenge where the qBraid SDK and Amazon Braket were utilized in creative manners. All of the solutions are runnable on qBraid without any installation of packages. With each challenge the winners shined in their creativity and usage of the qBraid platform to augment their quantum computing experience.


Team leader: Sorana Aurelia (Github Repo)

One shining example is the QuantumCrew’s usage of qBraid SDK in the Grover’s Challenge where they detected hamiltonian cycles in a graph. With the SDK, the team was able to supercharge their ability to submit Qiskit circuits on Amazon Braket backends and convert circuits between the two languages! Such a feat in 24 hours is truly down to the team’s effort and the ease of use of the qBraid SDK.

Quantum Teleportation:

Team: QuantumFeed

Team leader: Tony Ha (Github Repo)

Equally, the quantum teleportation challenge winners performed quantum teleportation using Amazon Braket and the Rigetti M-1 device as well as on IBM devices. While prior methods would require coding the quantum teleportation algorithm in both Amazon Braket and Qiskit, with the qBraid SDK, the QuantumFeed team were able to focus their attention on extending their solution to include error estimation and multi-contributor scenarios. We see great potential in their work to include results from various quantum computers provided via the qBraid SDK, Amazon Braket, and IBM Qiskit!


OpenQASM parser

For the more computer science oriented teams the OpenQASM challenge proved to be a favorite. The qBraid OpenQASM challenge winners, Ayushi Dubal and Naresh Chavan implemented a parser that generates OpenQASM 2.0 code which is equivalent to the input Amazon Braket circuit. The parser supports all standard gates, including multi-qubit and parameterised gates. Their solution impressed in its robustness against our autograder and we’re eager to see further contributions in the OpenQASM codebase and community.

1st place: 

Team leader: Ayushi Dubal (Github Repo)

Finally, we’d also like to recognize the second place team for the OpenQASM challenge, PhysicsFeed, for their comprehensive solution which used python files to modularize the OpenQASM parser.

2nd place: 

Team leader: Saaketh Rayaprolu (Github Repo)

Leave a Reply

%d bloggers like this: