We provide Quantum Programming materials from Microsoft and Quantum Computing Inc.
Quantum Programming Resources
Resources for those interested in Quantum Programming, including Microsoft Azure Q#, IBM Qiskit, and Quantum Computing Inc.
Quantum Game Club projects:
A Quantum Convolutional Neural Network: This project would aim to investigate the capabilities of a quantum convolutional neural network (QCNN) for a standard classification task like digit recognition. By comparing the efficiency and performance of this QCNN with that of a traditional convolutional neural network, this project can provide valuable insights into the potential of quantum computing for convolutional machine learning tasks. Replication of network consensus algorithms using quantum computing. This project aims to create simulation tools used to test network topology and convergence speed of networks. Markov process simulation on quantum computer.
Quantum Game Club’s past projects:
Quantum Prisoner’s Dilemma: The objective for this project is to build an implementation of the Prisoner’s Dilemma game that takes advantage of quantum properties. Besides the two options we see in a classical prisoner’s dilemma, to confess and to not confess, we introduce an additional quantum option that gives both players a better result depending on the level of entanglement.
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YouTube video: https://www.youtube.com/watch?v=uOpv16AWQZI
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Presentation slides: https://docs.google.com/presentation/d/1WSFhnwKHiQzFjkxeTVvzzpQHF06YfOyDEXRW3j_P8Lo/edit?usp=sharing
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Script: https://docs.google.com/document/d/188sDzEHBsOfyUICNZ6bw8oKcsqDrcloyD8X1yd1JyV0/edit?usp=sharing
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GitHub repo: https://github.com/halcdev/quantum-prisoners-dilemma
Quantum Generative Art: This project visualizes the noises in a quantum circuit in the form of our solar system. A machine learning model is used to generate a solar system closer to resembling our real solar system after every iteration.
Quantum Maze solver: this project utilizes QCI Inc.’s Qatalyst quantum optimization tools to find the most optimal solution to a randomly generated maze. The maze is traversed and mapped into a spanning tree and then transformed into a set of linear constraint functions. The constraint functions and an objective matrix are used to optimize the solution using Qatalyst.
Prizes and Awards
Awards:
IQ-PARC Award of Excellence (2022): For significant contributions to quantum technology and quantum programming education through the Purdue Quantum Game Club.
Scholarships:
Summer Undergraduate Research Fellowship (SURF). Quantum Game Club summer projects.
Other resources:
Official Microsoft Resources:
Quantum Katas – Resource for learning Q# and the basics of quantum circuit design.
Quantum Development Workshop -Talk discussing Q# development.
Q# Language Guide – The official resource for Q#.
Quantum Microsoft – Loads of example circuits and explanations.
Official Quantum Computing Inc. Resources:
Some basic concepts:
Here is a great write up https://www.activecyber.net/rise-quantum-computers-current-state-cryptographic-affairs/ highly worth the read
Also here is a super interesting video about quantum mechanics. https://www.youtube.com/watch?v=MzRCDLre1b4
3Blue1Brown is a great channel in general if you find math interesting.