Prism: Reflectometry Curve-Fitting (Fresnel Equations & Brewster Angle)

Simulates the inverse curve-fitting problem for absolute intensity data. Contrasts a Naive 2-DOF model, a Rigorous 2-DOF model, and a Covariant 5-DOF model to demonstrate the mathematical instability of over-parameterization when analyzing data corrupted by hardware polarization leakage.

System Parameters

Solver Architecture
Defines the degrees of freedom provided to the regression algorithm.
Target Material
True bulk refractive index. Overridden if a specific wavelength is selected.
Hardware Metrology Errors (Hidden from Naive Solver)
Quality of the polarizing crystal (10-6 = Ideal, 10-2 = Poor).
Azimuthal error in the transmission axis.
Mechanical misalignment of the normal baseline.
Gaussian scatter scale multiplier.
Extracted Index (nglass)
--
True Value: --
Extracted Amplitude (A0)
--
True Amplitude strictly 1.0000
Extraction Error (Δn)
--
Deviation from True Index
Absolute Reflectance (Linear Scale)
Brewster Minimum (Logarithmic Scale)
Rp Residuals
Rs Residuals

Fresnel Equations Models

1. Naive Model (2-DOF)

Unlike Variable Angle Ellipsometry (which is ratiometric), reflectometry relies on measuring absolute intensity. If the statistical solver assumes perfect hardware (a Naive Model), it interprets the elevated signal floor near the Brewster minimum as a fundamental change in the material's optical properties. Because the global amplitude parameter (A0) is strictly multiplicative, it cannot mathematically absorb the additive leakage caused by polarization errors (ε and γ). Consequently, the solver is forced to artificially skew the refractive index (nglass) to minimize the mean squared error, resulting in severe extraction inaccuracies and a highly bowed residual signature.

2. Rigorous Model (2-DOF)

In proper metrological practice, hardware constraints (ε, γ, θoff) are characterized independently prior to the sample measurement. By passing these fixed, pre-calibrated values into the theoretical model, the solver successfully decouples the background leakage from the interfacial reflectance. This Rigorous Model reliably extracts the true index, limited only by standard Gaussian noise variance.

3. Covariance Overfitting (5-DOF)

When encountering a poor fit under the Naive assumption, a common analytical mistake is to simply "unconstrain" the hardware parameters and allow the solver to fit them simultaneously alongside nglass and A0. This 5-DOF Covariant Model introduces massive mathematical degeneracy. The parameters ε and γ contribute near-identical additive constants to the intensity minimum, creating a perfectly flat "valley" in the objective function. The gradient descent algorithm falls into this trough and stops prematurely, achieving a visually flat residual line by hallucinating wildly incorrect physical parameters. This demonstrates why over-parameterization destabilizes experimental extraction.