c4f4f7e28f8bb0a7642c57ab5c4509f11d91cb1d
The reported sigma carries the background ring mean's own error as (dI/dbkg)^2 * bkg/n_ring, and the stills ring holds only 244 pixels at r3 = 12 against the rotation default's 408 - so that term is a larger share of the variance here than anywhere else in the program. r3 = 14 takes the ring to 416. What normally stops a ring being widened is crowding, since a neighbour inside the annulus is excluded from it. Stills barely crowd: neighbour occlusion is 0.000% at both radii on six of the seven datasets scored and 0.721% -> 0.678% on the densest, against most reflections having a neighbour within 13 px on rotation. Rotation is left alone at 4,6,13, where the ring already wins by a factor of several. Measured with the new stills harness over six datasets and 72 shells, 10000 images each, resolution range pinned so both arms share shell edges, against a control floor that is bit-identical in every column: <I/sigma> +1.23% median over the 56 signal-bearing shells (44/56) R_meas -0.37 points (39/56) CC1/2 flat (29/56) obs flat R_meas is the number to read here. <I/sigma> improving when the ring is widened is half mechanical - a better background estimate lowers sigma by construction - whereas R_meas has no sigma in it, so it moves only if the intensities themselves got better. A prediction from ring pixel counts alone, made before the run, was 1.6-2.7%; landing at 1.2% with the profile-fit weighting in the way is the mechanism behaving as expected. The larger and more consistent effect is the opposite of the risk this was checked against: reflections discarded for want of a background ring fall from 2.53-2.88% to 1.87-2.25% on all seven datasets, because a wider ring reaches past the module gap that starved the narrow one. Against it: CC1/2 and observation count are flat, and the gain reverses below <I/sigma> of about 4 - median -0.4% and -0.6% in the two weakest bands. Roughly a fifth of that is background curvature, which --background-radial recovers; the rest is not explained. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CHMmeM1d489zvNFT7ZMN2P
Jungfraujoch
Application to receive data from the PSI JUNGFRAU and EIGER detectors.
All documentation is now placed in docs/ subdirectory and for the current version hosted on Jungfraujoch Read The Docs page.
Languages
C++
75.4%
HTML
7.5%
C
6%
TypeScript
4.2%
Cuda
2.2%
Other
4.6%