slackbuilds_ponce/academic/penaltymodel

  One approach to solve a constraint satisfaction problem (CSP) using
an Ising model or a QUBO, is to map each individual constraint in
the CSP to a "small" Ising model or QUBO. This mapping is called
a penalty model.

  Imagine that we want to map an AND clause to a QUBO. In other words,
we want the solutions to the QUBO (the solutions that minimize the
energy) to be exactly the valid configurations of an AND gate. Let z =
AND(x_1, x_2).


  Optional building mode set with environment variables:
  - TESTS=yes, performs tests. Requires: dimod, python3-numpy,
    networkx, python3-scipy, homebase, lapack.