- ...items
- For CSPs, these items are all possible
variable-value pairs.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...items
- The lattice of sets can also
represent problems where each variable can have a different number of
assigned values.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...states
- The ket notation is conceptually similar to the
use of boldface to denote vectors and distinguish them from
scalars.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...becomes
- 66#66 is the transpose of
U with all elements changed to their
complex conjugates. That is 67#67.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...obtained
- I thank J. Gilbert for pointing out this
technique, as a variant of the orthogonal Procrustes problem [24].
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...numerically
- High precision values were obtained from
the FindRoot function of Mathematica.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...algorithm
- The values are given in Online Appendix 1.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...degree
- Using the Mathematica function Rationalize and
the package NumberTheory`Recognize`.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...nogood
- I thank J. Lamping for suggesting
this.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...evaluation
- I thank S.
Vavasis for suggesting this improvement in the classical simulation of
the algorithm.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...problems
- That is, problems
generated by random selection of nogoods without regard for whether they
have a solution.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...point
- This differs slightly from the results for
problems with more specified structure on the nogoods, such as
explicitly removing the necessary nogoods from consideration [50, 53].
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...solubility
- This is a particularly large error for this
theory: it does better for problems with larger constraints or more
allowed values per variable.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...nogoods
- This differs slightly from other studies of
random 3SAT in not allowing duplicate clauses in the propositional
formula.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
- ...solution
- For the values of 245#245 and small problems examined here, there are enough
soluble instances randomly generated that there is no need to rely on a
prespecified solution to efficiently find soluble test
problems.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.