sem_line_profile — GENERATIVE `sem` op

• Data kinds: none → table (an op determined by its arguments alone — it takes no image or data input)

• Call: import fullseye as fs; fs.ledger.sem_line_profile(line_material='PMMA', substrate='SI', energy_kev: 'float' = 1.0, *, width_nm: 'float' = 40.0, height_nm: 'float' = 40.0, sidewall_deg: 'float' = 88.0, beam_sigma_nm: 'float' = 1.0, x_half_range_nm=None, x_step_nm: 'float' = 1.0, electrons_per_point: 'int' = 200, buried=None, seed: 'int' = 0) -> 'dict' (to call the implementation directly, import sem; sem.sem_line_profile(line_material='PMMA', substrate='SI', energy_kev: 'float' = 1.0, *, width_nm: 'float' = 40.0, height_nm: 'float' = 40.0, sidewall_deg: 'float' = 88.0, beam_sigma_nm: 'float' = 1.0, x_half_range_nm=None, x_step_nm: 'float' = 1.0, electrons_per_point: 'int' = 200, buried=None, seed: 'int' = 0) -> 'dict'; from the registry, opsgenerative.get("sem_line_profile"))

Usage

Monte Carlo line profile of a beam scanned across one line with a trapezoidal cross-section (CD-SEM).

> The detailed description below is the original text — the summary and the headings are translated.

線は y に一様。底辺の幅 width_nm・高さ height_nm・側壁角 sidewall_deg (90 = 垂直)の台形で、材料 line_material が基板 substrate の上に乗る(height_nm = 0 なら平らな基板)。ビームは幅 beam_sigma_nm のガウシアン、位置ごとに electrons_per_point 個を撃つ。buried は基板に埋もれた矩形の列 [(材料名, x0, x1, 上端の深さ, 下端の深さ), ...] [nm]。

Returns

dict

x_nm / 検出器ごとの信号 se_total・inlens・everhart・bse

(電子 1 個あたり)/ eta / profile(pairs: x と inlens)/

真の寸法 width_bottom_nm・width_top_nm・width_mid_nm。

Examples

>>> r = sem_line_profile(energy_kev=1.0, width_nm=30, height_nm=20, x_half_range_nm=30,

... x_step_nm=10, electrons_per_point=40)

>>> r["profile"].shape

(7, 2)

Detailed usage guide

• generative_art family guide

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• poc_virtual_sem_kv_cd_bse — py -3.11 examples/poc_virtual_sem_kv_cd_bse.py

Ops the type connects to (they accept `table` as input)

perpetual_step · perpetual_render

Same category (`sem`)

sem_render · sem_electron_mc · sem_se_universal_curve · sem_yield_curve · sem_cd_measure · sem_image · sem_se_escape_fraction · sem_charging_series

*Provenance: sem.py — GENERATIVE operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

sem_line_profile — GENERATIVE sem op