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Gatti/DES weights pathological on image sims: N_eff ~1–5% of N, inflates σ(m) ~12× #227
Description
Second finding from the end-to-end image-sim m-bias run (#225), distinct from the additive-subtraction bug: even with a paired (shape-noise-cancelling) estimator, the m-bias error stayed at ±1.5 instead of the expected ~±0.1. The w_des weights from compute_weights_gatti are degenerate on the sims — a handful of objects carry essentially all the weight.
Measurement (grid_1, 1 tile, per sim)
N N_eff (% of N) w: min med max max/med top-10 %wt
1z2z 1684 51.3 3.0% 4.2e-2 1.05e1 4.5e3 426 29%
1p2z 1668 21.2 1.3% 1.3e-3 9.7e0 8.3e3 858 37%
1m2z 1683 29.4 1.7% 2.6e-3 1.1e1 5.6e3 510 40%
1z2p 1685 12.7 0.8% 1.8e-2 9.9e0 1.4e4 1401 55%
1z2m 1675 90.9 5.4% 2.2e-2 9.0e0 3.0e3 332 23%
(N_eff = (Σw)²/Σw²; a healthy shear weight sits at 50–90% of N.) σ(m) scales as 1/√N_eff, so this alone inflates the error ~8–12×, and the dominant few objects also skew the central value:
weight N_eff m1 m2
unit 1563 −0.880 ± 0.124 −1.002 ± 0.113
w_iv 1500 −0.805 ± 0.108 −0.979 ± 0.099
w_des ~28 −2.139 ± 1.533 −0.431 ± 0.332
(All rows still show the m ≈ −1 central value — that's #226, a separate bug. The weight is the error story.) w_iv behaves normally, which is what isolates the problem to compute_weights_gatti — most likely the SNR/size binning going degenerate, or a variance term blowing up, on the sims' narrow magnitude/size range.
Why it can't be side-stepped
For the m-bias to be science-applicable it must be measured under the weight the science analysis actually uses — so w_des needs to be fixed at source, not swapped for w_iv (which serves as the diagnostic proving the estimator and pairing are sound). Possibly related to the broader ngmix-v2.0 weight-map work (inverse-variance weights, shapepipe#604 stream).
— Fable, on behalf of Cail
Activity
martinkilbinger commentedon Jul 6, 2026
DES weights are very noisy for a small number of objects. In the (some) 20x20 grid of SNR and resolution, some pixels might have few or no galaxy for a small number of galaxies/tiles. Might have to run more tiles to see this behaviour go away?
cailmdaley commentedon Jul 7, 2026
@fabianhervaspeters says that we shouldn't be using weights at all for m-bias
feat(image-sims): w_col=None gives unit weights (no-weighting mode, #227
config(image-sims): unweighted global response for sim calibration (#227
Merge image_sims_val (Martin's parallel sim-validation stack) into the …
cailmdaley commentedon Jul 10, 2026
Closing as resolved — no weights anywhere in the sim m-bias is now the standing configuration (
w_col: null,global_R_weight: nullin the image-sims branch config), with w_des retained only as a diagnostic knob.Confirmation from the corrected single-tile baseline (tile 233.293, grid_1, paired unweighted estimator, and the true injected amplitude g = 0.025 — see the amplitude discussion around shapepipe#796): m1 = +0.019 ± 0.022, m2 = −0.015 ± 0.017, c1 = −0.0026 ± 0.0084, c2 = −0.0033 ± 0.0075. The σ(m) ≈ ±1.5 inflation this issue documents is gone; σ(m) ≈ 0.02 on a single tile with noise pairing (shapepipe#803).
The related estimator-flavor question (w_des appearing in the #796 m-bias snippet) is with Fabian on that thread; it doesn't affect this issue's verdict since the chain no longer uses weights anywhere.
— Fable on behalf of Cail
feat(image-sims): declare the sim mask config as an overlay on the da…
feat(image-sims): reconcile multi-weight-scheme m-bias with Phase A r…
Image-simulation m-bias: extracted core + snakemake orchestration (#225)
Record truth pass: image-simulation shear bias
Image-sim mask config keeps only the true reason for an unweighted R
Record truth pass: image-simulation shear bias
Image-sim mask config keeps only the true reason for an unweighted R
Record truth pass: image-simulation shear bias
Image-sim mask config keeps only the true reason for an unweighted R
Record truth pass: image-simulation shear bias
Image-sim mask config keeps only the true reason for an unweighted R