this page is intended to store information and quotation for referenciation and also a small amount of opinionation in humoracious juxtapositation
all quotes herein are true and real and unadulterated and I may be trusted
observations
- qfind's width-exhausting capability is surpassed by JLS's at high speeds and low denominators, both seem to be surpassed by ikpx2 for extremely low denominators (ie. c/2 in rules such as 2×2 where they are hard to find), and LSSS (nonexhaustive though it may be) is good for finding examples of speeds when one doesn't care about width but existence
- despite the fact that it says it is 'adaptive widening,' ikpx2 moving on from a width does in fact imply it has been searched exhaustively (and, due to its concatenation of subsections of different symmetry, in fact means it has searched a superset of the width)
- as far as SAT-solver-utilisers go, ikpx2 is better than LLS due to 'automation of the usage of said SAT solvers'
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ikpx2 is literally just qfind but with ridiculously high deepening, and qfind is just gfind with ridiculously high deepening
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the pecking order for spaceships is definitely ikpx2 > qfind > jls
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Once [qfind's] deepening exceeds like, 50, ikpx2 is unilaterally faster - the only problem is that ikpx2's memory usage is unbounded
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qfind is [expletive] cracked actually i need to study how its lookahead works under a microscope
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- generally, JLS is better than ikpx2 for odd-period diagonal spaceships since it is capable of exploiting diagonal symmetry (not implemented in ikpx2), but ikpx2 is better for even ones since it is capable of diagonal glide-symmetry (apparently, JLS is also, but it only works for oscillators)
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JLS is the only one that understands how to propagate the consequences of a guess to a row that ikpx2 and qfind haven't even considered yet
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- the algorithm JLS uses is DPLL