Quantum Challenge Resources
-
Getting Started
Element - Join the Element community space to connect and form teams.
Project Proposals - team leaders should submit their project proposals using the instructions here.
-
Orientation Modules
Please familiarize yourself with the tools and concepts which you will need to deliver a project for this challenge. You will need to create a GitHub account to submit your project until the deadline. In addition to git, we also recommend that you familiarize yourself with Markdown syntax if this is new to you.
-
Quantum Computing
Introduction
The prospects of quantum computing in computational molecular biology
Unitary Foundation 2024 Quantum Open Source Survey
Quantum Computing Packages and Simulators
Quantum-inspired Computing
Simulated Annealing via GPU-pSAv
Quantum Annealing via QuantRS2
Sampling
Quantum sampling problems, BosonSampling and quantum supremacy
Sampling Problems on a Quantum Computer
Quantum Circuits for the Metropolis-Hastings Algorithm
Quantum Computing for Clinical Research
Quantum computing for clinical research
How can quantum computing be applied in clinical trial design and optimization?
Quantum Clinical Trial Optimization Challenge Winner Presentations – Presented by Ingenii & Aqora
-
Python
Programming expertise is not required, but at least beginner Python programming experience is recommended for participation in code-focused projects of the hackathon. For those looking for a brief, interactive refresher on Python programming, see the GitHub Classroom assignment from the first section on this page. For those without prior Python experience, we recommend you complete an introductory Python course in preparation for the hackathon. Some resources are listed below:
If you have no prior programming experience, you may wish to start with the Python Beginners Guide for Non-programmers by Python Software Foundation.
-
Quantum Computing Tools/Packages
Use of the tools listed on this page is not a requirement. A diverse set of packages and implementations is encouraged. Likewise, multiple teams using the same package is not a problem, in part because implementations can remain private during the course of the challenge and since solutions will still vary considerably. If you would like to see a specific tool listed here, please navigate to the “Improve this page” link at the bottom of the page and open a pull request.
-
QuTip
-
OpenACC
-
quimb
Introducing matrix product states for quantum practitioners
Simulating quantum circuits with tensor networks
Tensor Network Quantum Virtual Machine for Simulating Quantum Circuits at Exascale