Sync the release with the submitted manuscript
Figures, data and code as they stand at submission, including the bibliography record check that verifies every entry against its article in ref/.
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@@ -164,9 +164,10 @@ chk("ratio spans 1.32 to 1.54", round(min(rt), 2) == 1.32
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# the three secrets named in the setup
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chk("secret sizes: per-user direction, perm 256, pad 16",
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all(t in tex for t in ["length-$64$ key direction per user",
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"one permutation of $256$",
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"$16$ pad bits per user"]),
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all(t in " ".join(tex.split())
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for t in ["length-$64$ key direction per user",
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"one permutation of $256$",
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"$16$ pad bits per user"]),
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"searched tex", needs_tex=True)
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chk("no stale d=64 configuration in tex",
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@@ -211,12 +212,17 @@ ks = [int(x) for x in md["learned"]["support99_per_key"].split("/")]
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chk("learned keys degenerate: 5 to 8 of 64 entries",
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min(ks) == 5 and max(ks) == 8 and int(md["learned"]["L"]) == 64,
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md["learned"]["support99_per_key"])
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chk("learned support overlap 0.10",
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round(float(md["learned"]["mean_overlap"]), 2) == 0.10,
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md["learned"]["mean_overlap"])
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chk("degeneracy numbers in tex",
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# independent supports of size a and b out of L overlap by max(a,b)/L
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# on this normalization, so the measured value is the chance level and
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# evidences the concentration rather than any disjointness
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_ch = sum(max(a, b) for a, b in __import__("itertools").combinations(ks, 2))
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_ch /= (len(ks) * (len(ks) - 1) / 2) * int(md["learned"]["L"])
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chk("learned support overlap is at chance, not below it",
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float(md["learned"]["mean_overlap"]) <= _ch + 0.02,
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"measured %s against chance %.3f" % (md["learned"]["mean_overlap"], _ch))
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chk("concentration numbers in tex",
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"$5$ to $8$ of the $64$ entries" in " ".join(tex.split())
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and "only $0.10$ of the smaller of any two such sets" in " ".join(tex.split()),
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and "a digit is decided over a tenth of its period" in " ".join(tex.split()),
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"searched tex", needs_tex=True)
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# --- why the permutation key is granted a shared permutation ---------
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