Classify fine-grid SSB mirror reuse once per frequency

The common 3× and 4× views of a full 512 × 512 × 192 × 192 acquisition retain the same fifth-order optics, tilt, depth, complete bright-field support, precision and preprocessing. The paired CUDA correction previously classified native alias boundary columns inside each bright-field iteration. Classify each output frequency before that loop and reuse the boolean. Independent boundary corrections and every nonzero arithmetic operation remain unchanged.

This is restricted to the existing 512-square real-FFT higher-order fine-grid path. Native reconstruction, fitting, Newton refinement, loss diagnostics, MPS and browser rendering are unchanged. There is no new cache, workspace, public API or kernel family.

Matched timing

RTX PRO 6000 Blackwell Max-Q Workstation Edition, CUDA, one prepared session. Ten rounds changed C10 and rotated variant order; medians exclude two warmups. Device synchronization surrounds reconstruction. Transfer and browser work are excluded. The reference includes the previously accepted zero-contribution skip.

Upsampling	Reference	Candidate	Time reduction
3×	48.10 ms	45.42 ms	5.6%
4×	52.50 ms	49.83 ms	5.1%

This is a further backend improvement, not a measured notebook frame rate or 60 fps result. The correction still dominates reconstruction. The separate native-grid loss diagnostic on slider release remains unchanged.

Validation and rejected candidates

All twenty matched outputs are array-identical. Eighty full-data cases over two acquisitions, factors 1, 2, 3, 4 and 8, varied rotation, defocus, astigmatism, tilt and depths from zero to 60 nm are also array-identical.

Skipping phase evaluations for zero aperture weights was faster but changed phase by up to 1.98e-6; it is rejected under the exact-output contract. Skipping inactive-block preparation was exact but produced little gain. Shared coordinate staging was exact and slightly faster in combination, but added shared-memory traffic and about 0.5 ms improvement; the smaller classification change is the accepted implementation. Raw timings and all candidates are retained privately.

Reference kernel SHA-256: 6f5621e3db38aa5e75f300e89ae5b19c1124609417a960924410bd352e8478c9. Candidate kernel SHA-256: 026f16815ffe7e8312a42437863e939fcfd45546b469019e210591fce9d97822. Private evidence: 20261023-ssb-fine-grid-classification.

Browser automation remained disabled in the host application. Slider gestures, FFT display and actual presentation rate are not verified by these measurements.

Installed notebook validation

The installed candidate passed all 31 CUDA wave-average/thick-sample tests in 127.27 seconds. Five repository privacy checks passed. The maintained advanced CUDA tutorial completed from a fresh kernel, including search, rotation comparison and ShowPtycho construction.

Twelve changed-C10 previews per factor then matched all 24 pre-change output hashes exactly. Warm median reconstruction plus GPU-to-host copy was 45.44 ms at 3× and 49.47 ms at 4×; the first observation is excluded. These independent installed-run timings exclude network and browser work. Use the alternating matched table above to quantify the optimization’s speedup.