docs: credit the L test, FFT indexing, TORO, Niggli, peakfinder8 and SparseCCL

Six methods the pages name or describe carried no citation: Padilla & Yeates
(the L test), Steller, Bolotovsky & Rossmann (the projection/FFT autoindexing
MOSFLM implements), TORO (what ffbidx implements), Krivy & Gruber and the
ITA lattice-character table (the reduction and Bravais assignment), Cheetah's
peakfinder8 (the per-ring background statistics of the adaptive finder) and
Hennequin et al.'s SparseCCL (already credited to traccc, now also to its
authors). Each gets its ACKNOWLEDGEMENT.md paragraph, a References entry in
CPU_DATA_ANALYSIS.md, and a one-line credit at the algorithm. The
Sheriff & Hendrickson / Popov & Bourenkov entry is re-scoped so each claim
sits on the paper that supports it - P&B 2003 is titled, and credited for the
sigma-aware anisotropy estimation its statistic modelling contains, not for
the tensor and its constraints. All DOIs verified against the publishers;
the SparseCCL DOI resolves to IEEE document 9049184 (IEEE blocks content
scraping, so verified by the resolved document id plus two independent
sources).

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EFEJG6WBQv8th4UJFNe53N

image_analysis/spot_finding/AdaptiveSpotFinderCPU.cpp

@@ -23,6 +23,8 @@ AdaptiveSpotFinderCPU::AdaptiveSpotFinderCPU(const AzimuthalIntegrationMapping &
     ring_bits.assign(OutputSize(), 0);
 }
 
+// Per-ring background statistics with iterated peak exclusion following peakfinder8:
+// Barty et al. (2014) J. Appl. Cryst. 47, 1118-1131
 // Accumulate per-ring mean/variance from the raw (photon) image. clip_k <= 0 -> use every valid
 // pixel (first pass); clip_k > 0 -> keep only pixels within clip_k sigma of the current ring mean,
 // which removes the Bragg peaks from the background estimate.