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.
962 B
962 B
| 1 | L | K | best_rho | eve_ser |
|---|---|---|---|---|
| 2 | 8 | 1 | 0.2918601623 | 0.9945244994 |
| 3 | 8 | 10 | 0.6307837307 | 0.9550597921 |
| 4 | 8 | 100 | 0.8190062809 | 0.8147158732 |
| 5 | 8 | 1000 | 0.9077793813 | 0.5723297059 |
| 6 | 8 | 10000 | 0.9535904264 | 0.3866372342 |
| 7 | 8 | 100000 | 0.9757162716 | 0.3157766639 |
| 8 | 8 | 1000000 | 0.9872786315 | 0.2845244539 |
| 9 | 16 | 1 | 0.2228791779 | 0.9990085712 |
| 10 | 16 | 10 | 0.4570522499 | 0.9943536935 |
| 11 | 16 | 100 | 0.6321070191 | 0.9769163907 |
| 12 | 16 | 1000 | 0.7417848118 | 0.9311708657 |
| 13 | 16 | 10000 | 0.8164950053 | 0.8399011082 |
| 14 | 16 | 100000 | 0.8673534005 | 0.7274791752 |
| 15 | 16 | 1000000 | 0.9048131336 | 0.5915534824 |
| 16 | 32 | 1 | 0.1399813941 | 0.999821061 |
| 17 | 32 | 10 | 0.3205750013 | 0.9991354579 |
| 18 | 32 | 100 | 0.4660256564 | 0.996404209 |
| 19 | 32 | 1000 | 0.5620279439 | 0.991343747 |
| 20 | 32 | 10000 | 0.6393936736 | 0.9815239297 |
| 21 | 32 | 100000 | 0.6993164916 | 0.9634132739 |
| 22 | 32 | 1000000 | 0.7479539255 | 0.9349306487 |
| 23 | 64 | 1 | 0.0987436915 | 0.9999096477 |
| 24 | 64 | 10 | 0.2263401688 | 0.9997303409 |
| 25 | 64 | 100 | 0.3389944824 | 0.9991750164 |
| 26 | 64 | 1000 | 0.4155608514 | 0.9981802181 |
| 27 | 64 | 10000 | 0.4757575011 | 0.9967597446 |
| 28 | 64 | 100000 | 0.5299797378 | 0.994275692 |
| 29 | 64 | 1000000 | 0.5741312045 | 0.9910114047 |