torann · ESS · neighbour-selection ablation

Does ESS need recall, or only plausible repellers?

An exact index, corrupted on purpose. 3 seeds per arm, paired by seed, 4 shapes. Recall turns out to have a floor, not a price — and the floor is low.


Verdict

Half the true neighbours can go almost free; all of them cannot go at all. From an empty start, dropping to recall 0.5 while holding locality fixed costs 0.45% Clark-Evans at d=32 and 3.78% at d=8. Dropping to recall 0 costs 17.2% at d=32 and 44.0% at d=8 — collapsing to the uniform null or below it — even when the substituted neighbours are only 5–12% further away.

The filled start — the case ESS is actually for — is uniformly less sensitive. With anchors that cannot be pushed, recall 0.5 costs 0.29% at d=32 and 2.51% at d=8; recall 0 costs 10.4% and 28.3%. Every arm hurts less than it does from an empty start, so the slack above is a lower bound on the slack in production.

So this lands on the branch where a distance ranking is the product. The index must return real nearest neighbours, but it has genuine slack in how many of them are true — which is roughly where the tuner already sits. Redesigning around cost per plausible local neighbour is ruled out: that arm is indistinguishable from random.

Why the earlier evidence looked ambiguous

Two measurements pointed opposite ways. Recall 0.69 at d=32 costs only 1.28% CE against perfect recall, which suggests recall is cheap to give up. But cutting LSH tables to lower recall costs 4.3% CE, which suggests it is not. Both can be true, because fewer tables degrades recall and locality together — the experiment confounds them.

This ablation separates the two. The index is exact throughout, so recall is not a property of the index here; it is imposed. Between the query and the force kernel the neighbour list is replaced by a controlled corruption of it, and the true toroidal-L1 distance of whatever was substituted is passed through. Only the selection changes. Force magnitudes are never confounded with it.

mean ratio below is the delivered neighbour distance over the true k-th distance — the locality knob, made comparable across dimensions. recall is measured against the exact answer the same index computed.

The ladder

Ordered by how local the selection is. Only the first two arms contain true neighbours at all.

1
exact

True k nearest neighbours. The control.

2
top2k

k drawn from the true 2k nearest — half the true neighbours survive, and locality is essentially untouched.

3
rank1-4k

k drawn from ranks k..4k. Not one true neighbour, but the nearest points that are not true neighbours.

4
rank8-16k

k drawn from ranks 8k..16k. Still local relative to n, several times the true neighbour distance.

5
ratio2x

k drawn from everything within 2x the k-th distance — the arm as originally specified.

6
uniform

k uniformly random points. The null.

Clark-Evans regularity

1.0 is the uniform null at every dimension. Higher is more regular — the thing ESS exists to produce.

at or above the uniform nullbelow the uniform null — actively clustereduniform null

d = 32  ·  empty start  ·  0+4000

exact
1.2074
top2k
1.2019
rank1-4k
0.9993
rank8-16k
0.9830 below the null
ratio2x
1.0008
uniform
1.0008

d = 32  ·  filled start  ·  2000+4000

exact
1.1427
top2k
1.1394
rank1-4k
1.0236
rank8-16k
1.0075 below the null
ratio2x
1.0227
uniform
1.0227

d = 8  ·  empty start  ·  0+2048

exact
1.4741
top2k
1.4183
rank1-4k
0.8253 below the null
rank8-16k
0.9440 below the null
ratio2x
1.0083
uniform
1.0042

d = 8  ·  filled start  ·  1024+2048

exact
1.3375
top2k
1.3040
rank1-4k
0.9591 below the null
rank8-16k
1.0098 below the null
ratio2x
1.0459
uniform
1.0379

Separation

The minimum pairwise distance, toroidal L1. This is where the mechanism shows: when the true nearest neighbours are withheld, nothing repels the pairs that are actually touching, and they fuse.

at or above the uniform nullbelow the uniform null — actively clustereduniform null

d = 32  ·  empty start  ·  0+4000

exact
6.0752
top2k
5.9403
rank1-4k
3.6295 below the null
rank8-16k
3.6741 below the null
ratio2x
3.9632
uniform
3.9695

d = 32  ·  filled start  ·  2000+4000

exact
4.1058
top2k
4.1058
rank1-4k
3.4952 below the null
rank8-16k
3.6029 below the null
ratio2x
3.6974
uniform
3.6974

d = 8  ·  empty start  ·  0+2048

exact
0.9058
top2k
0.7703
rank1-4k
0.0251 below the null
rank8-16k
0.1833 below the null
ratio2x
0.2981
uniform
0.2959

d = 8  ·  filled start  ·  1024+2048

exact
0.3291
top2k
0.3291
rank1-4k
0.0526 below the null
rank8-16k
0.2033 below the null
ratio2x
0.2371 below the null
uniform
0.2395

Reading the collapse

rank1-4k is the informative arm: its neighbours are only 12% further away than the true ones at d=8, and 5% at d=32. Being nearly-nearest buys nothing. The pairs at risk of fusing are exactly the ones the force law must see, and plausible mid-range repulsion does not compensate for missing them — separation falls 97% at d=8 and 40% at d=32.

The severity is strongly dimension-dependent, and this is the part worth not over-reading. At d=8 a near-miss neighbour list is worse than random — CE 0.8253 against a null of 1.0042 — because it actively holds points together while pushing on the wrong pairs, where random neighbours at least apply an isotropic mean-field pressure. At d=32 that gap nearly vanishes (0.9993 against 1.0008): once recall is zero, every arm lands on the null and how local the substitutes were stops mattering.

The arm as originally specified confirms why it needed replacing. At d=32, ratio2x and uniform agree to four decimal places on every column — the ball of radius 2x the k-th distance has swallowed the entire point set, exactly the concentration argument that governs the rest of this index's design. The rank-window arms were added for that reason: they pin recall at zero while varying locality independently, which is the separation the original design intended but could not achieve at these dimensions.

The full record

d = 32  ·  empty start  ·  0+4000

armrecallmean ratioClark-Evansvs exactseparationepochs
exact1.0001.001.2074 ±0.00156.0752151
top2k0.5001.001.2019 ±0.0021-0.45%5.9403126
rank1-4k0.0001.050.9993 ±0.0014-17.24%3.6295110
rank8-16k0.0001.160.9830 ±0.0039-18.59%3.6741117
ratio2x0.0011.451.0008 ±0.0003-17.11%3.963240
uniform0.0011.451.0008 ±0.0003-17.11%3.969540

d = 32  ·  filled start  ·  2000+4000

armrecallmean ratioClark-Evansvs exactseparationepochs
exact1.0001.001.1427 ±0.00214.1058118
top2k0.5001.001.1394 ±0.0024-0.29%4.1058112
rank1-4k0.0001.041.0236 ±0.0008-10.42%3.4952118
rank8-16k0.0001.141.0075 ±0.0020-11.83%3.6029114
ratio2x0.0011.451.0227 ±0.0003-10.50%3.697427
uniform0.0011.451.0227 ±0.0003-10.50%3.697427

d = 8  ·  empty start  ·  0+2048

armrecallmean ratioClark-Evansvs exactseparationepochs
exact1.0000.991.4741 ±0.00630.9058166
top2k0.5000.991.4183 ±0.0176-3.78%0.7703131
rank1-4k0.0001.120.8253 ±0.0210-44.01%0.0251171
rank8-16k0.0001.460.9440 ±0.0049-35.96%0.1833151
ratio2x0.0091.711.0083 ±0.0029-31.60%0.298138
uniform0.0022.281.0042 ±0.0019-31.88%0.295927

d = 8  ·  filled start  ·  1024+2048

armrecallmean ratioClark-Evansvs exactseparationepochs
exact1.0000.981.3375 ±0.00560.3291110
top2k0.5000.991.3040 ±0.0041-2.51%0.3291106
rank1-4k0.0001.120.9591 ±0.0206-28.29%0.0526128
rank8-16k0.0001.431.0098 ±0.0052-24.50%0.2033125
ratio2x0.0081.721.0459 ±0.0083-21.81%0.237153
uniform0.0022.391.0379 ±0.0054-22.40%0.239551