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
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_desweights fromcompute_weights_gattiare degenerate on the sims — a handful of objects carry essentially all the weight.Measurement (grid_1, 1 tile, per sim)
(
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:(All rows still show the m ≈ −1 central value — that's #226, a separate bug. The weight is the error story.)
w_ivbehaves normally, which is what isolates the problem tocompute_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_desneeds to be fixed at source, not swapped forw_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