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author William PC <w_calandrini[at]hotmail[dot]com>2022-11-12 10:49:57 +0700
committer Willy Sudiarto Raharjo <willysr@slackbuilds.org>2022-11-12 10:49:57 +0700
commit6888a39bbc641cf96545a8fc39c07eb802ce08c9 (patch)
treea29aa94d019ff8bc9c3fa74d16bc8ff55a325d22 /academic/penaltymodel/README
parent3f50fb224559923f9336365a90dc640e7155eff6 (diff)
downloadslackbuilds-6888a39bbc641cf96545a8fc39c07eb802ce08c9.tar.gz
slackbuilds-6888a39bbc641cf96545a8fc39c07eb802ce08c9.tar.xz
academic/penaltymodel: Added (penalty model solver).
Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>
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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.