quapps Instance Data Set

quapps Instance Data Set In the quapps package, concrete problem types for quantum optimization are specified, based on the package quark.A detailed description of each of the problem types can be found in the READMEs of corresponding Gitlab repository. We will therefore not explain the problems in more detail here. The instantiated optimization problems of this data set are based on the quapps package and were created with the implemented random generators. In view of the qubit numbers available in the near future, the number of instances was limited to instances that comprise a maximum of 128 variables. This resulted in different different combinations of the defining parameters, such as the size of the graphs or their density: Maximum Cut: numbers of nodes 𝑁 ∈ {8, 16, 32, 64, 128}, densities 𝑑 ∈ {0.4, 0.6, 0.8} (too low densities lead to non-connected graphs, whereas graphs, whereas a density of 1.0 results in a complete graph for which the maximum cut problem for which the maximum cut problem is trivial), and a randomly chosen integer edge weighting between 1 and 5 or no weighting at all, Maximum Colorable Subgraph: node numbers 𝑁 ∈ {8, 12, 16}, densities 𝑑 ∈ {0.4, 0.6, 0.8} and a number of colors from 3 to the maximum possible for the respective graph, Arbitrary Ising model: qubit numbers 𝑁 ∈ {8, 16, 32, 64, 128} and coupling densities 𝑑 ∈ {0.2, 0.4, 0.6, 0.8, 1.0} with an accuracy of 2 decimal places, Prime Factorization: two random prime numbers with a number of 3 to 10 bits per prime number which result in a non-trivial optimization problem, Traveling Salesperson: node numbers from 8 to 12. We created 5 different instances for each parameter configuration. This results in a total of 125 Ising, 244 Maximum Colorable Subgraph, 150 Maximum Cut, 124 Prime Factorization and 25 Traveling Salesperson instances. Additionally we added 96 Flight-Gate Assignment instances from our publication "Flight Gate Assignment with a Quantum Annealer": Flight-Gate Assignment: with 3 to 17 flights and correspondingly 3 to a maximum of 17 gates. The instances can be loaded into your Python script via from quapps.max_cut import MaxCutInstance import quapps.io instance = MaxCutInstance.load_hdf5(filename)