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WFC3 (UVIS + IR) — per-stage deltas vs the ACS/WFC design

Phase 2. hst_acs_pipeline.md remains the stage-by-stage spec; this page records only what WFC3 changes. Everything below lives in the two adapters (instruments/wfc3_uvis.py, instruments/wfc3_ir.py) — no stage module mentions a detector.

WFC3/UVIS — the ACS-like path

Stage Delta vs ACS
acquire _flc (CTE-corrected) as ACS; references key iref, CRDS subpath references/hst/wfc3
align / drizzle / noise / psf / package unchanged — same recipes, same dials
scale native 0.0396″/pix; adapter recommends output at native scale
saturation ~63 ke- full well (star selection peak cut)

Validation anchor: the published Bayer et al. (arXiv:1803.05952) F390W reduction of SDSS J0252+0039 — output 0.0396″/pix, pixfrac 1.0, noise recipe σ = √(N/W + σ²_sky) with σ_sky ≈ 0.002 e-/s. Our integration script (scripts/reduce_j0252_wfc3.py --channel uvis) reduces the same data with those dials and checks: output units e-/s, empirical σ_sky in that regime, noise-map consistency, WHT uniformity. (Note their correlated-noise treatment is blank-sky realizations, not the scalar R — with pixfrac 1.0 at native scale, R = 1.5; comparisons account for whether R is applied.)

WFC3/IR — the genuinely different path

Stage Delta vs ACS
acquire _flt — no CTE correction exists for the IR channel; iref references
drizzle up-the-ramp fitting in calwf3 already rejects most CRs per read; driz_cr still runs on multi-exposure stacks for the residue (defaults-first) — documented, revisit if IR integrations show over-flagging
scale native 0.128″/pix under-samples the PSF; adapter recommends 0.065″/pix for dithered data (half-native, in the 0.06–0.08 deep-field range). The dial stays user-facing; the fine-grid Casertano branch (s < p) then applies, so R is materially larger — reported per run as always
units _flt IR data are already e-/s (count rates); final_units='cps' unchanged
saturation ~78 ke- effective full well
psf same tiers; STScI focus-diverse ePSF grids exist for IR when tier 2 lands

Coverage audit vs ajshajib/hst-lens (the checklist, not the architecture)

Their three notebooks (Download / IR / UVIS) cover: archive download, per-channel calibrated products, AstroDrizzle combination, and cutouts. Ours adds what they lack: instrument adapters (theirs is notebook-per-channel), provenance (reduction.json), an explicit noise-map recipe with correlated- noise handling, tiered PSF construction with diagnostics, cache/eviction, and loud-failure contracts. Nothing in their steps is absent from our stage graph.

Integration finding — IR pixfrac/coverage (2026-07-08)

Reducing the J0252+0039 F160W snapshot (program 11202) at the recommended 0.065″/pix with the phase-1 default pixfrac 0.8 left 230 zero-weight speckle pixels inside the cutout — the few-dither + fine-grid (s ≈ 0.51 < p) regime — and the finite-noise packaging guard refused to ship the dataset, exactly as designed. pixfrac 1.0 closes coverage at the cost of a larger correlated-noise factor (reported per run, as always). Rule of thumb recorded here: on the IR channel, few-dither data at sub-native output scales needs pixfrac → 1.0 (or a coarser scale dial); the WHT-uniformity diagnostic and the finite-noise guard enforce the trade-off loudly rather than letting a holey dataset through.

Open items

  • IR integration target: discovered via MAST at run time; if no suitable IR lens dataset is reachable, the leg parks as a batched question.
  • Tier-2 PSF for IR (focus-diverse ePSF grids) — with the roadmap's tier-2 work, not phase 2.