Description Quantum computer operating in superconducting qubits can go to the temperature of nearly absolute 0 degree Kelvin. It takes a huge operating cost to build and maintain its superpower. Unless you are a scientist or an engineer in an advacned reseach group or a big company like IBM, Google, Microsoft, you cannot have a taste of what it’s going on physically. It would be wonderful if you could run it on your hands.

I have been working on quantum machine learning by implementing gradient descent for optimized parametrized circuits using pennylane and qiskit, this can tremendously improve the cost and also simplify the quantum gate. The Jupyter Notebook file may be too large so you need to reload it again. Description Implement a circuit that returns |01> and |10> with equal probability. Requirements :The circuit should consist only of CNOTs, RXs and RYs. Start from all parameters in parametric gates being equal to 0 or randomly chosen.

Qiskit Hackathon Challenge Global for 24 hours Team Memeber Suyeon Park from South Korea, Shek Lun Leung (Alan) from Hong Kong, Rohit Chaurasiya from India, Quentin Sieredzki from the US, and Cynthia Vanessa Rios from the US Mentors: Daniel Sierra-Sosa and James Weaver The exceptional team Description Problem Statement: How can we map quantum states and operations to create music notes with different instruments?