Wanted to do something with quantum computing and was interested in quantum hybrid algorithms

What it does

Applies the traveling salesman problem to the airplane industry and uses a quantum computer to compute the optimal solution

How we built it

  • I took a list of airports, found their latitude/longitude to create a distance matrix
  • Created a graph and mapped the distance matrix to the graph
  • Mapped it to the Ising model then sent it to the quantum algorithm to optimize
  • Take the answer and determined which path to take

Challenges we ran into

  • Figuring out what the functions do and what the variables do in the Qiskit tutorial
  • Trying to read and understand the Qiskit documentation
  • Constant trial and error

Accomplishments that we're proud of

  • Getting the distance matrix from the airports mapped onto the real graph for the quantum algorithm
  • Getting the code to work

What we learned

  • How the math/theory works for the algorithm
  • How to create a distance matrix from scratch

What's next for Airplane Optimizer

  • Create parameters and airspace limits (ie. can't fly over White House, etc.)
  • Have it work for more airports (more nodes)

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