The quantum programming platform at the Quantum Computer Architecture lab at TU Delft is centered around the OpenQL compiler and QX simulator.

The QCA lab is affiliated to QuTech and the Quantum & Computer Engineering department, as a collaboration between the Faculty of Applied Sciences and the Faculty of Electrical Engineering, Mathematics and Computer Science.

I am a Ph.D. candidate at QuTech and QCA lab, working on Quantum Machine Learning for Genomics. Previously, I completed my M.Sc. in Computer Engineering with thesis on Quantum Algorithms for Pattern Matching on Genomic Sequences.

The development of QML for Genomics is explained in the ARC notebooks. It is an accompanying resource to my Ph.D. thesis.

A set of Jupyter Notebooks for learning various quantum programming platforms. It is meant for the 'already-initiated' - someone who already knows the basics of quantum programming in one platform and wants to compare, migrate or explore the features of another platform.

Most of the materials are derived from various other official or community tutorials of the respective platforms; packaged as a cheatsheet to bootstrap a fast-paced learning. Advanced features are provided as links for exploring in a need-to-know basis.

• ARC_Q4 - TSP formulation
• ARC_Q5 - alpha-QAOA, iQPEA
• ARC_Q6 - random Hamiltonian and Unitary generation for testing
• ARC_Q7 - Max-Cut QAOA OpenQL

These are in the *archives.

• Rigetti - Forest, Grove, QVM, pyquil
• IBM - QISKIT, Terra, Aer, Ignis, Aqua, QExp

• Xanadu - StrawberryFields, PennyLane, Blackbird
• D-Wave - Ocean, Leap
• Google - Quirk
• Microsoft - QSDK, QuantamKatas