slackbuilds_ponce/academic/penaltymodel/README
William PC 6888a39bbc academic/penaltymodel: Added (penalty model solver).
Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>
2022-11-12 10:49:57 +07:00

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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.