This page is: qisk.it/gids

Resources for GIDS Architecture Quantum Computing Workshop:

Title: Quantum Computing Workshop for Classical Developers

Presenter: James Weaver

• James Weaver's presentations slides
  • QiskitBlocks game site qisk.it/blocks
  • Open-source quantum computing software development framework site Qiskit.org
  • Quantum computing textbook that leverages Qiskit qisk.it/textbook

IBM Quantum Experience (where you'll create a quantum game)

Quantum Game Challenge (Build a quantum 8-ball)

1. Optional but recommended if you're new to Qiskit:

• Take the Create your first quantum circuit tutorial (great primer on using Circuit Composer).
• Take the Code your first quantum circuit tutorial (great primer on using Qiskit Notebooks).

2. In the IBM Quantum Experience Circuit Composer, create a three-wire circuit whose measurements are randomly distributed among 000 - 111.
   • View the Statevector and Measurement Probabilities from the Visualizations tab (bar graph image) on the left side of the page.
   • Observe the results when running your circuit on a backend quantum system or simulator. The shortest queues are typically with the 32 qubit simulator ibmq_qasm_simulator in ibm-q/open/main
3. Create the circuit using Python and Qiskit in an IBM Quantum Experience Jupyter notebook.
   • Make the program print out a message unique to each measured state (e.g. state 000 message might be "The quantum 8-ball says it's most likely"). For reference, here are the possible answers from the original Magic 8-Ball.
   • If you'd like some hints, please see this partial solution
   • For reference, here is one possible solution
4. If you have time:
   • Rather than using a simulator, use the from_instruction() and sample_counts() methods of the qiskit.quantum_info.Statevector class. Your circuit should not have measure operations.
   • Expand the circuit to four or five wires.
   • Add various single and multi-qubit gates to the circuit (in the Circuit Composer first if you'd like) and observe their effects on the measurement probabilities and results.