Neutralizing EUV Drift (v1.0c) — Auditable Finite-Rank Neutralization for Sub–2 nm Metrology

# Neutralizing EUV Drift (v1.0c) — Auditable Finite-Rank Neutralization for Sub–2 nm Metrology **Preprint (Open)** This note develops an *auditable* and *deployable* finite-rank neutralization method for drift removal in high-precision EUV metrology pipelines (e.g., CD-SEM/overlay/stage logs), with explicit decision gates, reproducibility artifacts, and production change-control. --- ## Overview Modern sub–2 nm metrology pipelines are dominated by slow, structured drift components that bias spectral slope diagnostics on declared fit bands. We formalize drift removal as a registered linear map on a Hilbert space \(H\): - Choose a **registered drift dictionary** \(V=\{v_1,\dots,v_r\}\subset H\) and a **whitening weight** \(W\succ 0\).- Define the **weighted orthogonal projector** \(P_V^{(W)}\) onto \(\mathrm{span}(V)\) and the **neutralizer**\[N_V^{(W)} := I - P_V^{(W)}.\]- Apply the channel-fixed map \(y \mapsto y^{\mathrm{post}} := N_V^{(W)} y\) and evaluate slope/quality metrics on a declared band. The main point is not only correctness (finite-rank removal), but **auditability**: every run is accompanied by registry-fixed configuration, deterministic outputs, and a certificate digest to support third-party verification. --- ## Closed results (what the paper guarantees) ### 1) Structural finite-rank neutralizationIf the drift component lies in \(\mathrm{span}(V)\), then the neutralizer removes it exactly (up to numerical tolerance). When drift is only approximately captured, the residual is controlled by the distance to the dictionary span (weighted geometry). ### 2) Decision policy (paper-fixed PASS/FAIL)We provide a **paper-fixed** acceptance policy (AC1–AC8 style gates) that binds:- a declared fit band,- a declared baseline slope \(\beta_\star\),- negative-control detectability,- injection/leakage constraints,- minimum data/bins requirements,- and reproducibility/certificate requirements. This converts “drift removal” into a reproducible engineering decision rather than an ad-hoc tuning step. ### 3) Auditable artifacts and certificateEach run produces a minimal “dossier” and an integrity stamp (hash/certificate) over:- window parameters,- dictionary and whitening identifiers,- fit-band metadata,- slope estimates and robust uncertainty summaries,- negative-control outcomes,- and decision outcomes. --- ## What is new in v1.0c - **Production lifecycle**: offline calibration → shadow mode → active mode → periodic revalidation → change-control.- **Reference baseline \(R_0\) and competitiveness gap**: require neutrality results to be non-inferior to a declared baseline pipeline and report \(\Delta_{R_0}\) (non-regression guard).- **Channel-fixed dossier placeholders**: standard report figures/templates for CD-SEM, overlay, and stage logs (to be replaced by channel-fixed production figures).- **Audit stability floor**: define a registry-fixed \(\varepsilon_{\mathrm{floor}}\) to avoid spuriously large ratios when metrics are near zero.- **Validation addendum templates**: 1-page scenario-based validation reports suitable for fab review loops. --- ## Scope & non-toy status This work is a **tooling/specification paper**: it aims to be implementable in industrial pipelines with minimal ambiguity. - The neutralizer \(N_V^{(W)}\) is a deterministic linear map defined by a registered dictionary and weight.- The acceptance policy is written as an operational contract (gates + artifacts).- The paper explicitly supports “fail-safe” behavior: if gates are not satisfied, the pipeline defaults to identity or the declared baseline \(R_0\), avoiding uncontrolled dictionary retuning. --- ## Reproducibility package (expected artifacts) A minimal open bundle should include (names are indicative):- `pb_config.json` (parameter box / gates / fit band)- `window_registry.json` (window family and effective scale parameters)- `dictionary.json` (drift atoms + version hash)- `whitening.json` (W-estimator choice + identifiers)- `metrics.csv` (pre/post/negative-control slope & CI, BRF, leakage)- `certificate.json` (hash digest over the above) --- ## Suggested citation If you use this method, please cite: - B. Lee (2026), *Mock Theta Neutralization v2.0d: Full-Stack Neutralization Theorem with Calibrated Exponents, Pipeline, and a Worked Application*, Zenodo, Version v2.0d. DOI: 10.5281/zenodo.18133333. - B. Lee (2026), *Neutralizing the Eisenstein Continuum (v1.8): A First-Principles Tool for High-Precision Arithmetic Quantum Chaos*, Zenodo, Version v1.8. DOI: 10.5281/zenodo.18131871. - B. Lee (2025), *Neutralizing Shadow Terms in BPS and Black Hole Microstate Counts: An Automorphic Projection and L-Value Transduction*, Zenodo, Version v2.6. DOI: 10.5281/zenodo.18143091. --- ## Keywords EUV metrology; drift removal; finite-rank projection; whitening; auditable pipelines; reproducibility; spectral slope; negative control; injection test; change control.