KiHoLee
3cf3b6c3a7
stage_F was missed in the structured-family regeneration, so sec_brute.csv and sec_sens.csv still carried learned-family results. Re-running it moves the L=16 brute-force point from 0.7495 to 0.5916, which now agrees with sec_brute_cmp.csv rather than contradicting it. make_tables.py bolds the Walsh-Hadamard row the way it already bolds the proposed and invariant rows, since that family is the main configuration.
30 lines
962 B
CSV
30 lines
962 B
CSV
L,K,best_rho,eve_ser
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8,1,0.2918601623,0.9945244994
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8,10,0.6307837307,0.9550597921
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8,100,0.8190062809,0.8147158732
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8,1000,0.9077793813,0.5723297059
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8,10000,0.9535904264,0.3866372342
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8,100000,0.9757162716,0.3157766639
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8,1000000,0.9872786315,0.2845244539
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16,1,0.2228791779,0.9990085712
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16,10,0.4570522499,0.9943536935
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16,100,0.6321070191,0.9769163907
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16,1000,0.7417848118,0.9311708657
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16,10000,0.8164950053,0.8399011082
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16,100000,0.8673534005,0.7274791752
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16,1000000,0.9048131336,0.5915534824
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32,1,0.1399813941,0.999821061
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32,10,0.3205750013,0.9991354579
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32,100,0.4660256564,0.996404209
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32,1000,0.5620279439,0.991343747
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32,10000,0.6393936736,0.9815239297
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32,100000,0.6993164916,0.9634132739
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32,1000000,0.7479539255,0.9349306487
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64,1,0.0987436915,0.9999096477
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64,10,0.2263401688,0.9997303409
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64,100,0.3389944824,0.9991750164
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64,1000,0.4155608514,0.9981802181
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64,10000,0.4757575011,0.9967597446
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64,100000,0.5299797378,0.994275692
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64,1000000,0.5741312045,0.9910114047
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